Categories
AdTech

Overview of China’s Programmatic Advertising Ecosystem

As globalization continues to deepen, international brands are increasingly turning their attention to the vast Chinese market. With the largest number of internet users in the world and a digital advertising market size that ranks at the forefront globally, programmatic advertising, as an essential means of digital marketing, is gaining increasing attention. This article will delve into the development history of China’s programmatic advertising ecosystem, analyze its main players and functions, compare it with the foreign ecosystem, and finally provide strategic recommendations for foreign advertisers entering the Chinese market.

Development History of China’s Programmatic Advertising

Since being hailed as the “Year of Programmatic” in 2012, China’s programmatic advertising has experienced a period of enthusiastic capital pursuit, an outbreak period, and an adjustment period that has attracted industry-wide attention. With advertisers focusing on issues such as traffic fraud and advertising transparency, the industry has gone through a period of calm reflection during the adjustment period to the current refined transformation. The Chinese programmatic advertising market has undergone rapid development and transformation.

Embryonic Stage (2008-2011)

During this period, programmatic advertising began to sprout in China, with many companies starting to try this emerging marketing method. In 2011, Alimama launched the advertising trading platform Tanx, marking the preliminary exploration of China’s programmatic advertising.

Rapid Development Period (2012-2013)

The year 2012 is regarded as the inaugural year for programmatic advertising in China, with a plethora of companies launching DSP products. Google’s advertising trading platform also officially went live in China that year. In the following year, giants such as Tencent, Sina, and Baidu joined the programmatic advertising market, propelling the industry’s rapid development.

Eruption Period (2014-2016)

Driven by capital, the programmatic buying market entered an explosive period. Statistics show that during this time, more than a hundred programmatic buying platforms emerged. However, the market also faced issues like fake traffic, brand safety, and opacity, which gradually attracted industry introspection.

Shuffling Adjustment Period (2017 to Present)

As the market matures and advertisers demand higher transparency, the programmatic advertising market has entered a period of shuffling and adjustment. Companies with outstanding technology, resources, and reputation have begun to stand out, while other platforms face the pressure of being eliminated. Advertisers have started to focus more on the quality of advertising delivery rather than the quantity, with a preference for precise delivery that brings verifiable value.

Photo by Markus Spiske on Unsplash

Main Changes and Trends in China’s Programmatic Advertising Ecosystem

As market demands evolve, advertisers increasingly prefer precise delivery and performance measurement, driving the development of programmatic buying technologies, such as Real-Time Bidding (RTB) and Direct Programmatic Buying. In addition, China’s unique market environment and policy orientation are also shaping the unique development path of the programmatic advertising ecosystem, with the following trends emerging:

  • Increased demand for vertical platform advertising delivery: Advertisers are paying more and more attention to the quality of advertising delivery, with a preference for precise delivery that brings verifiable value.
  • The rise of Connected TV (CTV): With the increase of CTV users, programmatic TV advertising has become a new growth driver in the industry.
  • Improvement of KOL programmatic advertising delivery: Programmatic technology helps advertisers more accurately select KOLs for promotion, achieving systematic and programmatic KOL management.
  • Cross-platform and cross-device advertising delivery: With the advent of the all-screen era, brands have higher requirements for the scenario of digital marketing, and cross-device programmatic advertising delivery will receive more attention.
  • Enhancement of transparency and industry standards: Advertisers are increasingly concerned about industry transparency, and industry norms and standards are being strengthened, with third-party monitoring agencies and high-standard industry norms playing an important role.
  • Focus on brand safety and advertising effectiveness: Advertisers’ focus has shifted from  extensive “quantity” to refined “quality,” with brand safety and advertising effectiveness becoming key topics.
  • Integration of advertising transaction data: To improve the conversion rate of advertising and consumer experience, the integration of data generated in advertising transactions, more efficiently positioning the right target audience and the right delivery opportunity, has become the focus of the next wave of digital transformation.

Main Players in China’s Programmatic Advertising and Brief Introduction

China’s programmatic advertising ecosystem is a diversified and highly integrated system, including Demand-Side Platforms (DSPs), Supply-Side Platforms (SSPs), Advertising Exchanges, Data Management Platforms (DMPs), Programmatic Creative Platforms, Monitoring and Analytics Tools, Programmatic TV, and Programmatic Digital Out-of-Home (pDOOH), among other roles. These platforms and tools, through efficient technical means, have achieved automated purchasing, precise delivery, and data recovery of advertising resources, providing advertisers with one-stop services from strategy formulation to performance evaluation, promoting the digital transformation of the entire advertising industry.

  • DSP (Demand-Side Platform): A platform that helps advertisers or ad agencies to automatically lock in target traffic, purchase advertising space, control budgets, and optimize strategies. YOYI Tech’s Plus platform, covering high-quality advertising resources from mainstream Chinese media, can help advertisers achieve their advertising goals efficiently and economically.
  • Ad Exchange & SSP: Advertising trading platforms and supply-side platforms are responsible for the buying and selling of advertising inventory. For example, HUAWEI Ads, as a newly included platform, covers more than 730 million monthly active users.
  • Trading Desk: A procurement trading platform and technology, providing one-stop automated advertising platform services. YOYI Tech’s OneDesk is a representative TD that integrates various high-quality media and advertising resources.
  • Data Supplier & Data Management: Data provision and management platforms support advertisers in more accurately targeting their audience.
  • Programmatic TV: Programmatic television advertising provides opportunities for the programmatic purchase of television and outdoor advertising.
  • Measurement & Analytics: Monitoring and analytical tools help advertisers evaluate the effectiveness of their advertising.
  • pDOOH: Programmatic outdoor advertising, which leverages technology to automate the placement of outdoor advertising. For example, Asiaray (Ya Shi Wei) and DiDi are newly included platforms.

Photo by Google DeepMind on Unsplash

Differences and Similarities between China’s and Foreign Programmatic Advertising Ecosystems

Compared to foreign ecosystems, China’s programmatic advertising ecosystem also faces challenges in data privacy protection and user choice rights. With the implementation of “privacy protection” mechanisms, the space freely available for the audience identification mechanisms that programmatic advertising relies on to operate is increasingly narrowing. There are some significant differences between China’s programmatic advertising ecosystem and that of foreign countries, as follows:

  • Market Size and Maturity: Although China’s programmatic advertising market is large, it is still in a stage of continuous development and adjustment compared to the more mature markets of Europe and the United States.
  • Technology and Platform Development: China’s programmatic advertising technology ecosystem map shows that the market is adapting to changes in privacy protection mechanisms and audience identification mechanisms, such as OAID replacing IMEI, and IDFA facing more refined authorization for use.
  • Influence of Super Platforms: In China’s programmatic advertising ecosystem, large technology companies like HUAWEI Ads occupy an important position through their closed-loop ecosystem products, which is different from the situation abroad where giants like Facebook and Google dominate and work with many small and medium-sized platforms.
  • Advertising Forms and Innovation: China’s programmatic advertising is exploring new forms such as Programmatic TV and pDOOH, while the development of these fields in foreign markets may be more mature.

Considerations for Foreign Advertisers Entering the Chinese Advertising Market

  • Understand the Market Environment: China’s advertising market has a unique cultural and regulatory environment. Foreign advertisers need to deeply understand these characteristics. An in-depth understanding of Chinese market characteristics and consumer behavior is key to success. For example, Chinese consumers’ dependence on mobile devices is much higher than in other countries, which has an important impact on advertising delivery strategies.
  • Data Compliance: With the strengthening of data privacy protection, advertisers must ensure that their data collection and use comply with Chinese laws and regulations. Strictly comply with Chinese laws and regulations, especially in terms of data protection and privacy. For example, understand and comply with the relevant requirements of the “Cybersecurity Law” and the “Personal Information Protection Law.”
  • Choice of Partners: Choosing experienced and resourceful local partners can help foreign advertisers adapt to the market environment more quickly and achieve effective market penetration.
  • Technical Adaptability: Utilize local Chinese technology platforms and services, such as DSPs and Ad Exchanges, to achieve more precise advertising delivery.
  • Cultural Sensitivity and Localization Strategy: Advertising content needs to consider the sensitivity of Chinese culture to avoid cultural conflicts or misunderstandings. Develop advertising content and marketing strategies that conform to Chinese cultural and social values. For example, respecting Chinese traditional festivals and customs can improve the acceptance and effectiveness of advertising.

Photo by Markus Spiske on Unsplash

The development of China’s programmatic advertising has been diverse and dynamically changing, from initial exploration to current refined operations, with the market continuously maturing and improving. The Chinese programmatic advertising market offers great opportunities for foreign advertisers but also comes with challenges. By deeply understanding the market environment, complying with laws and regulations, formulating localization strategies, and choosing the right partners and technology platforms, foreign advertisers can succeed in this vibrant market.

Categories
AdTech

Introduction to China’s Advertising DMP

A DMP (Data Management Platform) can provide audience targeting for advertising campaigns through demographic labeling and establish user profiles based on campaign data. It manages these labels and facilitates retargeting, thereby helping advertisers or agencies review and optimize their advertising strategies more efficiently.

Classification of DMPs

Based on the ownership of the DMP platform, DMPs are categorized into first-party, second-party, and third-party DMPs.

  • First-Party DMP: Refers to an internal DMP built by large advertisers themselves or with the help of external technology providers. It is used for analyzing and managing user data, providing decision support and user data support for marketing processes and is widely used in industries such as e-commerce, gaming, and travel.
  • Second-Party DMP: Refers to a DMP built by demand-side service providers (usually DSPs) to assist advertisers in better campaign deployment, enhancing effectiveness while increasing the volume of placements, indirectly boosting the advertiser’s spending on the demand-side platform.
  • Third-Party DMP: Refers to a DMP primarily engaged in data transactions, offering services such as data exchange and sales to demand-side entities. It typically requires integration with DSPs before being applied to advertising campaigns. If it involves PC data, a cookie mapping process is also necessary between the DSP and DMP.

Photo by fabio on Unsplash

Classification and Enumeration of Data Suppliers

There are numerous third-party data providers in the market. Here are some of the larger ones:

  • BAT: Alibaba’s e-commerce data, Tencent’s social data, and Baidu’s search data. Generally, these data sources have relatively high barriers to access.
  • Companies with a wealth of valuable offline data: It’s important to highlight offline data, as we live in the real world where online behavior may not truly reflect our intentions. For instance, a user browsing cars online may not necessarily intend to purchase, but a visit to a car dealership suggests a high likelihood of intent. Typical representatives include companies like Zhanhui Zongying, which holds real user activity data from airports, high-speed railways, and the automotive industry chain, and UnionPay Smart, which has offline transaction data from POS machines. Recently, these data-rich companies have been activating data monetization models, offering advertisers superior programmatic advertising solutions through self-built DSPs and unique DMPs.
  • Third-party monitoring companies also hold a large amount of advertising campaign data due to the nature of their business. Typical representatives include companies like MiaoZhen and AdMaster; mobile representatives include TalkingData and Umeng.
  • Media companies also provide demographic data services (such as gender, age, and interests), but the coverage of a single media source is inherently limited.
  • Traditional CRM technology service companies are also present, but integrating CRM data with online data has always been a challenging issue.
  • DSP companies also possess some data, primarily sourced from advertising traffic. Advertising exchanges provide user and media information data such as the current media, position, and IP of the user’s advertisement to help DSPs make better bidding decisions based on user behavior. As a result, DSPs have accumulated a wealth of data based on this advertising traffic and their past advertising performance data. However, since this data is carried within the advertising traffic and much of the RTB traffic is “remnant traffic,” it has a certain degree of fragmentation and may not reflect the entirety of a user’s online behavior. Especially on mobile ADX, unlike PCs, it cannot provide the URL of each ad content page, only the App in which the user’s ad is displayed, and the latitude and longitude obtained is merely the user’s offline location when the App is opened to display the ad, which may not reflect the user’s entire movement trajectory. Therefore, such fragmented data makes it difficult to analyze and label user behavior as continuously and precisely as on the PC side.

Photo by Joshua Sortino on Unsplash

Basic Functionality and Core Process of Data Sample Learning

The most fundamental function of a DMP is to collect various online and offline data through different means and channels. The types of data can be diverse, not limited to advertising campaign data but also including CRM, surveys, third-party, and other data sources. Advertisers focus on different aspects of data from different sources:

  • For First-Party DMP data, advertisers are more concerned with the analytical capabilities of first-party data, such as consumer behavior analysis on official websites and offline, and media attribution analysis.
  • For Second-Party DMP data, advertisers are more concerned with the application of second-party data in advertising campaigns and the impact of media content and categorization on advertising efficiency.
  • For Third-Party DMP data, advertisers focus more on the efficient output methods and connectivity and effectiveness of the data.

Photo by Firmbee.com on Unsplash

The basic functionality of a DMP mainly revolves around various stages such as data collection, cleansing, integration, management, analysis, and application.

Data collection, cleansing, integration, and management focus on aspects such as timeliness, accuracy, reliability, stability, scalability, and automation of data processing.

Data analysis and application focus on the mining of “people” and “patterns” within the data. Creating audience profiles, classifying and tagging data, and providing guidance for marketing and decision-making are key.

Source of featured image: Photo by Jakub Żerdzicki on Unsplash

Categories
AdTech

Introduction to AdX and SSP in China

Overview

Ad Exchange platforms (AdX) integrate advertising resources and networks, facilitating the sale of advertising space through various transaction methods, including programmatic direct buying, preferred deals, and real-time bidding. DSPs can interface with AdX to purchase media ad impressions transparently through different transaction methods, accurately targeting audiences to improve advertising ROI. Theoretically, the role of a Supply-Side Platform (SSP) is to connect with media and then to AdX. However, since the functionality of SSPs is now essentially the same as AdX, we can discuss Ad Exchange and SSP together under the term AdX.

Photo by Kenan Buhic on Unsplash

Common Transaction Models of Domestic AdX

PDB (Programmatic Direct Buying): PDB is the preferred model for the highest quality advertising resources in media. These resources are often in high demand and sought after by advertisers. To secure these premium resources, advertisers typically negotiate a fixed price with the media in advance, reserving these spots exclusively. Unlike traditional advertising, PDB allows for audience targeting, but this targeting is limited to a few broad demographic dimensions.

PD (Preferred Deals): After the highest-quality resources are secured by major brands, there remains a pool of relatively high-quality resources with uncertain impressions. If an advertiser purchases these uncertain volumes at a negotiated price, this model is known as PD. The downside of PD is the uncertainty of resource allocation, but the advantage is that the advertiser does not have to commit to a certain volume of impressions and can target the specific audience they need, preventing waste of advertising resources.

RTB (Real Time Bidding): After the high-quality resources are purchased, there will always be some less desirable resources left that are not favored by advertisers. Media does not want to waste these long-tail and lower-quality resources, so they are put on the open market for smaller advertisers to bid on through RTB. The placement and pricing of these resources are uncertain and determined in real time.

Comparison of AdX Transaction Models

Model Buying Method Requires Advance Order Display Priority Guarantee Volume Resource Quality Resource Placement Reservation Pricing and Volume Guarantee
PDB Fixed CPM/CPD Yes Highest Yes Premium Yes Fixed price, fixed volume
PD Fixed CPM Yes After premium No Relatively good No Fixed price, no volume guarantee
RTB Bid CPM No Remaining traffic No Non-premium No No price or volume guarantee

Classification and Examples of Domestic AdX

AdX platforms are generally classified into public and private AdX based on their ownership of the main media resources.

Public AdX: Public AdX does not own media resources and acts as a typical intermediary matching buyers and sellers. The characteristics of these AdX include large traffic volume and low prices, but the quality of traffic is inconsistent, mainly consisting of long-tail traffic and a small amount of surplus traffic from top vertical media (media that have not established their own AdX).

Private AdX: These AdX platforms belong to major media owners and are centered around the resources of these media. Examples include the AdX of major portal media (Tencent, Sina, Sohu, etc.), video media (YouTube, IQIYI, LeTV, etc.), and emerging mobile media (Xiaomi, Momo, etc.). The traffic quality of these AdXs is relatively better since it is the media’s traffic, and the prices are slightly higher. Sometimes, to reduce the overall buying cost, these AdX may also introduce cheaper external media traffic in addition to their own.

Photo by Marek Piwnicki on Unsplash

AdX as a Key Gatekeeper in Advertising Review

In the advertising placement process, the review of advertising materials and the qualifications of advertisers is a key step that directly affects the efficiency of advertising placement, the quality of advertising, and the reliability of advertising information. The media that ultimately publishes the information is the responsible entity as stipulated by advertising law.

As the most centralized hub of advertising transactions, AdX has become the main gatekeeper for the review process. The review mainly involves the qualifications of advertisers, the upload and review of advertising materials, the review of advertiser qualifications and materials from the DSP side, and the review of advertiser qualifications and materials from the AdX side. Understanding the review entities should provide a basic understanding of whom to consult and appeal to in daily work practice.

KPIs Around AdX

These data indicators are seen from the perspective of AdX and may not be the same as what DSPs see due to network losses:

  • Total available bid requests: Based on the total traffic of AdX, the total number of bid requests can be sent to various DSPs, which is considered as the available inventory of AdX.
  • Filtered request volume: After setting filtering conditions on the AdX self-service platform, the number of bid requests filtered by each DSP, such as filtering certain sizes or websites.
  • Actual request sent: AdX will send the actual number of bid requests to each DSP based on the QPS limits set by the DSP on the AdX self-service platform. This indicator shows how much inventory the DSP can see, and AdX can also evaluate the consumption capacity of each DSP.
  • Actual request rate: The ratio of the actual number of requests sent by AdX to each DSP to the total number of available bid requests. AdX can use this indicator to assess the consumption capacity of each DSP.
  • Number of bids: The number of bids a DSP participates in.
  • Bid participation rate: The proportion of the number of bids a DSP participates in into the actual number of requests sent. AdX can use this indicator to assess the purchasing willingness of each DSP.
  • Number of abandoned bids: The number of bids a DSP has abandoned as seen by AdX (actual request number – number of bids).
  • Abandoned bid rate: The ratio of the number of abandoned bids a DSP has to the actual number of requests sent.
  • Number of valid bids: The number of bids successfully responded to that meet the placement constraints (can be placed) for materials and advertisers.
  • Number of invalid bids: The number of invalid bids due to reasons such as unreviewed advertiser qualifications, banned industries and categories, response timeout, parsing errors, etc. AdX can use this indicator to assess the technical and execution management capabilities of each DSP and assist in reducing this number.
  • Response timeout count: The number of network failures or response timeouts (generally required <100ms) received from a DSP.
  • Response timeout rate: The ratio of the response timeout count of a DSP to the actual number of requests sent. AdX can use this indicator to assess the technical capabilities of the DSP’s Bidder and network conditions.
  • Parsing error count: The number of parsing failures caused by incorrect data packet formats returned by a DSP in the bidding process.
  • Parsing error rate: The ratio of the parsing error count of a DSP’s returned package to the actual number of requests sent.
  • Number of successful bids: The number of advertising exposure opportunities successfully won by a DSP.
  • Bid success rate: The ratio of the number of successful bids a DSP has to the number of bids participated in.
  • Number of failed bids: The number of bids a DSP did not win in the bidding process because the bid was not the highest (valid bid number – number of successful wins).
  • Bid failure rate: The ratio of the number of failed bids a DSP has to the number of bids participated in.
  • Traffic utilization rate: The ratio of the number of successful bids a DSP has to the actual number of requests sent.

Photo by FlyD on Unsplash

Source of featured image: Photo by JESHOOTS.COM on Unsplash

Categories
AdTech

Classification and Introduction of Chinese Demand-Side Platforms

Demand-side platforms provide services for brand advertisers or ad agencies, acting as an automated online advertising purchasing system known as DSP (Demand-Side Platform). DSPs enable advertisers or ad agencies to programmatically select targeted traffic and purchase ad spaces, control budgets, and optimize advertising strategies in real-time. As an integral part of digital marketing and programmatic advertising, DSP platforms offer advertisers an efficient and intelligent way to deploy ads.

Classification of Chinese DSP Platforms and Corresponding Suppliers

Analysis of Entrants

Ad agencies or ad networks transitioning into DSPs: With a wealth of advertiser resources, these companies can directly integrate into the DSP landscape. Their entry can involve building a technical team to develop a DSP, purchasing a DSP technology solution for private deployment, or acquiring a DSP company outright, with representatives such as HaoYe and others.

Ad Exchange or SSP companies expanding into DSPs

These companies, with significant traffic resources, aim to connect directly with advertiser resources. Leveraging existing technical capabilities, they typically develop a DSP in-house, with representatives including Baidu, Alibaba, Tencent, Youku, and more.

Pure-tech companies entering DSPs

Originating from a technical background, these companies have entered the programmatic advertising field rapidly, using their technological edge. Representatives include YOYI Technology and others.

Large-budget advertisers building their DSPs

With ample advertising budgets, these advertisers seek to efficiently utilize their proprietary data to enhance campaign performance and gain transparency over traffic. Their approach can range from developing a technical team for DSP creation to purchasing technology solutions for private DSP deployment. The YOYI Plus team offers a DMP+DSP model, providing large-budget advertisers with a solution for the efficient use of first-party data and transparent execution of programmatic advertising.

Photo by Towfiqu barbhuiya on Unsplash

DSP Types in China

Based on the resources connected and the target of service, DSPs can be further classified into Pure Web DSPs, Mobile DSPs, Cross-screen DSPs, and DSP+.

Pure Web DSPs

Focus on web traffic and services for web-oriented clients, evolving towards cross-screen DSP capabilities.

Mobile DSPs

Concentrate on mobile traffic and advertisers targeting mobile users.

Cross-screen DSPs

A hybrid of PC and mobile DSPs, offering inventory across multiple screens, including computers, smartphones, tablets, etc. YOYI Plus is a leading cross-screen DSP in China with Mobile, PC, OTT, and CTV inventories in hand.

DSP+

Encompasses various specializations such as DSP+advertiser types (e.g., performance DSPs, brand DSPs), DSP+vertical industries (e.g., financial DSPs, e-commerce DSPs), DSP+resource types (e.g., video DSPs). However, performance DSPs now generally serve brand clients as well, making pure performance DSPs rare.

Depending on the background of the DSP owner, such as owning proprietary media or being an advertiser themselves, DSPs can be categorized as follows.

Third-Party Independent DSPs

DSP platforms that bid on traffic from various Ad Exchanges/SSPs. Notable examples include YOYI TECH, FancyDigital, WiseMedia, Domob, etc..

Large Media Proprietary DSPs

Private DSPs are built by large media companies with their traffic. Examples include Tencent DSP, Sina DSP, Youku DSP, Toutiao DSP, etc. These DSPs have competitive advantages due to their unique traffic resources but may face challenges when advertisers seek cross-media frequency control for multi-media campaigns.

Advertiser Proprietary DSPs

Large advertisers, due to the privacy of their business data, cannot apply it to third-party DSP platforms. To activate this data, some advertisers opt to build their DSPs, using their technology and business data for ad deployment, achieving self-operation. Examples include Ctrip DSP, NetEase DSP, etc.

DSPs with Unique DMP Data

Companies like UnionPay with POS transaction data, and Opsmart Technology, with data from large offline traffic scenarios, use DSPs for monetization. These companies are relatively neutral in ad traffic and create value for advertisers through unique data, which is their core driving force.

Trading Desk (TD)

A Trading Desk, similar to a DSP, provides an integrated technical solution for managing multiple DSP platforms. Advertisers can manage campaigns across various DSPs through a TD, including budget allocation, strategy adjustment, and performance reporting. TDs typically serve brand advertisers who often advertise across multiple DSP suppliers, involving overall budgeting, frequency control, and unified campaign management.

TDs can be categorized into Agency Trading Desks (ATDs), Independent Trading Desks (ITDs), and Brand Trading Desks (BTDs).

Agency Trading Desks (ATDs)

Trading desks within 4A agencies serving multiple brand advertisers, such as Xaxis, Accuen, AOD, and Changrong.

Independent Trading Desks (ITDs)

Similar to ATDs they serve multiple ad agencies or direct clients, like YOYI OneDesk, Chinapex, and Fuge.

Brand Trading Desks (BTDs)

Trading desks are built in-house by advertisers or with technology providers for internal use, such as the Yili Trading Desk.

Photo by Bertrand Gabioud on Unsplash

Selection and Evaluation Criteria for Chinese DSP Suppliers

Before advertising deployment, it’s crucial to select and evaluate DSP suppliers effectively. A good supplier can make advertising efforts much more effective, while a poor choice can lead to inefficiencies and potential fraud.

Key considerations when choosing a DSP include traffic, performance, product, service, and pricing. Traffic refers to media resources, performance is tied to technical capabilities, data strength, and algorithmic prowess. The product backend focuses on the ad deployment and management interface. Service is related to the company’s background and service capabilities, while pricing models determine the cost-effectiveness of the DSP. Advertisers can assign different weights to these factors, score them, and ultimately select a DSP with strong comprehensive capabilities as a partner.

  • Media Resources: The advantages of DSP media resources, including featured media, ad types, and volume.
  • Technical Capabilities: Including DSP functional modules and hardware equipment. Functional modules assess precise targeting capabilities and technical highlights; hardware equipment refers to data center and server resources, verifying the DSP’s authenticity.
  • Data Strength: Measures whether the DSP has sufficient data to support precise ad deployment, either from its data or third-party DMP data.
  • Algorithmic Capabilities: Examines whether the DSP has an algorithmic optimization model to automatically adjust and optimize ads, reducing manual workload while ensuring campaign effectiveness.
  • Product Backend: Evaluates the completeness, maturity, stability, and usability of the DSP’s ad deployment backend.
  • Company Background: Provides an overview of the DSP company to assess reliability, including company introduction, team members, awards, patents, and the ability to serve major clients.
  • Service Capabilities: Assesses the professionalism (including data analysis, reporting, and emergency service capabilities) and stability of the DSP execution team.
  • Pricing Models: Media pricing, service fees, and pricing transparency are also critical for advertiser evaluation.

YOYI Plus, as a leading DSP in China, has cross-screen delivery capabilities for various traffic terminals including PC, mobile, OTT, and CTV, covering over 80% of media traffic in China. With robust audience data and tagging capabilities, it helps brands acquire precise public domain advertising traffic more efficiently, enhancing brand exposure and ad interaction effects.

Source of featured image: Photo by Priscilla Du Preez 🇨🇦 on Unsplash

Categories
AdTech

Interpretation of Advertising Monitoring Indicators in China

Advertising effectiveness monitoring indicators are crucial for advertisers to determine the effectiveness of advertisements and how to optimize them. The commonly used advertising monitoring indicators by Chinese advertisers mainly include four major categories: traffic indicators, interaction indicators, conversion indicators, and cost indicators.

Traffic Indicators

Ad Impressions

The total number of times an advertisement is displayed on a specific website within a designated time period. High exposure means the advertisement has a wide reach, but it is also important to avoid ineffective exposures. This indicator cannot measure whether users have actually seen the advertisement, as it can be affected by factors such as page scroll speed, which affects the visibility of the advertisement.

Photo by Choong Deng Xiang on Unsplash

Unique Impressions

Unique impressions refer to the number of exposures after excluding multiple exposures by the same user, which is mainly achieved by excluding duplicate cookies.

Calculating the ratio of ad impressions to unique impressions (Impression/Unique Impression) is one of the simple ways to identify ad fraud. A high ratio indicates that some users are repeatedly visiting in large numbers, suggesting that the website may have abnormal traffic and is suspected of having machine-generated traffic.

Viewable Impressions

Viewable impressions are based on the visibility of the advertisement. The IAB (Interactive Advertising Bureau) stipulates: For PC-side image advertisements, 50% of the pixels are displayed for more than 1 second, and for PC-side video advertisements, 50% of the pixels are displayed for more than 2 seconds, which can be considered viewable impressions. Additionally, for larger ad formats, 30% of the pixels displayed for more than 1 second can be considered 1 viewable impression.

The internet advertising pricing model related to this indicator is CPMv (cost per mille viewable impression), which is the cost for a thousand viewable impressions. The new CPM selling method used by Tencent mentioned earlier is CPMv. This selling method excludes data for advertisements that have not been actually watched, which can ensure the fairness, authenticity, and effectiveness of advertising transactions to a certain extent, help advertisers improve advertising effectiveness, save advertising budgets wasted on poor media resources or content, and improve ROI, thus being welcomed by advertisers.

Clicks

Clicks are the metrics used to measure user behavior after ad exposure. Clicks are the key actions that link front-end advertisements with back-end landing pages, reflecting the audience’s interest in the advertisement. Factors affecting clicks include two aspects: first, the accuracy of ad placement, and second, the quality of ad creativity.

Click-Through Rate (CTR)

The ratio of clicks to impressions (Click/Impression), the click-through rate allows for a horizontal comparison of the effectiveness of different advertisements and is the most direct and persuasive quantitative indicator reflecting the effectiveness of online advertising. Factors affecting the click-through rate include: the number of impressions, which only becomes relatively stable after reaching a certain quantity, objectively reflecting the effectiveness of the advertisement; the accuracy of ad placement, the higher the proportion of the target consumer group reached, the higher the click-through rate; the attractiveness of ad creativity, the stronger the visual impact and the more attractive the content, the higher the click-through rate.

Page Views (PV)

Page views are a commonly used indicator for website traffic statistics. A request from the user’s end to open a page is considered one page view. Page views are one of the commonly used traffic indicators for monitoring ad landing pages. To a certain extent, they can reflect the degree to which the interests and desires of the ad audience are stimulated and can reflect a certain advertising effect.

Visits

Visits are commonly used in website traffic analysis to describe a series of user behaviors within a certain period of time or in the process of achieving a certain goal. The mainstream view is that visits refer to the number of times users visit a website.

Visits can be used for the calculation of CPV (Cost Per Visit), which is the cost per visit. In practical applications, it is rarely used as a billing method in settlements between media and advertisers, but rather as an indicator for advertisers to measure the ROI of marketing activities.

Unique Visitors (UV)

Unique visitors are used to measure the number of website visitors. According to the “China Mobile Internet Advertising Standards,” a device visiting a website within a specified time period is counted as one visitor, and the same device will only be counted once within the specified time period.

Compared with other traffic indicators, unique visitors are centered on a user as a measure, which can help advertisers more accurately identify the audience affected by advertising activities, and can also be used to identify simple traffic fraud. Unique visitors can be used for CPUV (Cost Per Unique Visitor), which is the cost per unique visitor. However, like CPV, it is often not used as a billing method in advertising transactions between advertisers and media, but rather as an ROI indicator set by advertisers according to the goals of the advertising campaign.

Photo by Claudio Schwarz on Unsplash

Interaction Indicators

Traffic indicators describe the arrival of users for advertisements and landing pages, while interaction indicators describe the depth of user participation. Compared with traffic indicators, the standardization of interaction indicators is relatively low.

Bounce Rate

Bounce rate refers to the ratio of users who, after clicking on an advertisement and entering the advertiser’s promoted page, do not generate further clicks and choose to leave directly. In internet marketing, the bounce rate can be used to measure the quality of external traffic and the attractiveness of website content to the audience. The higher the quality of external traffic and the more accurate the front-end advertising, the more target users can be attracted, and the lower the bounce rate of users after entering the website.

2nd-Click Rate

When a first-level website page is clicked and opened, any additional clicks generated by the user on the page are called “2nd-clicks,” and the number of 2nd-clicks is referred to as “2nd-click volume.” The ratio of “2nd-click volume” to page views is called the page’s “2nd-click rate.”

Visit Depth (PV/V)

Visit depth (PV/V) is an average number, referring to the number of times a specific web page is exposed to a visitor during a single visit, calculated as page views divided by visits. The higher the visit depth, the more pages a visitor browses in one visit, the more information they get, and the greater the value of these visits to advertisers.

Visit Duration

Visit duration (Time on Site) is also an average number, a measure of the length of visits, specifically the average time spent per visit, calculated as total visit time divided by visits. Theoretically, the longer the visit duration, the better the interactive effect of the advertisement.

Conversion Indicators

Conversion indicators are the most valuable category of indicators for businesses as they directly reflect the benefits that advertising activities bring to the enterprise, and thus are increasingly valued by advertisers.

Conversion rate refers to the ratio of the number of times users complete specific actions (such as purchases, registrations, etc.) to the number of clicks, and is a key indicator for evaluating the effectiveness of advertisements. Specific actions for conversion include:

Sales-related conversion indicators

Offline: The number of store visits

Online: The number of orders placed and purchases completed

App-related conversion indicators

Downloads

Active users

Registrations Users

Retention

In-app purchases

Cost Indicators

Cost Per Thousand Impressions (CPM)

Refers to the cost per thousand impressions when advertising is placed, reflecting the cost of advertising placement.

Cost Per Click (CPC)

Refers to the cost per click when advertising is placed, reflecting the cost of advertising placement.

Cost Per Conversion (CPA)

Refers to the cost per conversion action when advertising is placed, reflecting the cost of advertising placement.

Advertising Monitoring Fields

The following are fields involved in the advertising monitoring process in China, covering data from multiple aspects such as users, devices, advertising activities, geographic locations, and network environments. Through the analysis of these data, advertisers can comprehensively understand the display, click-through, and conversion effects of advertisements, optimize advertising placement strategies, and improve the ROI (Return on Investment) of advertisements.

Field Name Data Format Meaning Value
user_id string Unique identifier for the user Used to distinguish different users
user_id_type string Type of user identifier, such as device ID, email Helps to understand the source of user_id
req_time bigint Request time, records the timestamp of the user’s ad request Used to analyze user behavior and ad display timeliness
ip string User’s IP address Used for geographical analysis and user identity verification
cookie string Cookie data from the user’s browser Used to track user’s online activities and ad effectiveness
source string Traffic source Identifies the channel or platform the ad traffic comes from
campaign_id string Unique identifier for the ad campaign Used to distinguish and analyze different ad campaigns
order_id string Order ID Used to track transactions and conversions related to the ad
url string Target URL of the ad display or click Used to analyze ad effectiveness and user behavior
os string Operating system information of the user’s device Used for device and platform compatibility analysis
ad_ip string IP address of the ad server Used to track the source of ad requests
idfa string Advertising identifier for iOS devices Used for mobile ad tracking
idfa_md5 string MD5 encrypted form of IDFA Used for privacy protection and data matching
idfa_sha1 string SHA1 encrypted form of IDFA Used for privacy protection and data matching
imei string International Mobile Equipment Identity for Android devices Used for device identification
imei_md5 string MD5 encrypted form of IMEI Used for privacy protection and data matching
imei_sha1 string SHA1 encrypted form of IMEI Used for privacy protection and data matching
android_id string Unique identifier for Android devices Used for device identification
android_id_md5 string MD5 encrypted form of Android ID Used for privacy protection and data matching
android_id_sha1 string SHA1 encrypted form of Android ID Used for privacy protection and data matching
mac_md5 string MD5 encrypted form of device MAC address Used for device identification and privacy protection
android_advertising_id string Advertising identifier for Android devices Used for ad tracking
ad_timestamp bigint Timestamp of the ad event Used to accurately record the time of ad display and click
oaid string Open Advertising Identifier Used to replace traditional device identifiers and enhance privacy protection
callback_url string Callback URL Used for server-to-server notifications and data transmission after ad click
user_agent string User agent string of the user’s browser Used to identify device and browser information
brand string Device brand information Used for market analysis and device performance evaluation
network_type string Network type, such as WiFi, 4G Used to analyze the network environment of the ad display
csite string Content site Identifies the specific site or app location where the ad is displayed
stype string Ad type, such as display ad, video ad, etc. Used for categorization and effectiveness analysis
extend string Extension field Used for storing other custom data
open_udid string Open Unique Device Identifier Used for device identification and ad tracking
plan_id string Ad plan ID Used to distinguish and manage different ad plans
platform string Ad serving platform, such as mobile, PC, etc. Used to distinguish the platform where the ad is served
publisher_id string Publisher ID Used to distinguish different ad publishers
adzone_type string Type of ad placement, e.g., banner ads, interstitial ads Used for classification and performance analysis
adzone_id string Ad placement ID to distinguish different ad display positions Used to distinguish different ad display positions
province_id string Province ID for geographical analysis Used for geographical analysis
city_id string City ID for geographical analysis Used for geographical analysis
county_id string County ID for more detailed geographical analysis Used for more detailed geographical analysis
traffic_type string Type of traffic, e.g., organic traffic, paid traffic Used for traffic quality analysis
adx_id string Ad Exchange Platform ID Used to distinguish and manage different ad exchange platforms.
app_package string App Package Name Used for identifying and analyzing different mobile applications
main_domain string Main Domain Used for analyzing the domain source of ad display
num int Number of Ad Requests Used for statistics and analysis of ad request volume
log_type string Log Type, such as display log, click log, etc. Used for classification and analysis
sub_customer_id string Sub-Customer ID Used for multi-level customer management and analysis
session_id string Session ID Used for tracking a user’s single visit behavior
order_type string Order Type, such as purchase, registration, etc. Used for conversion analysis.
creative_id string Creative ID Used to distinguish and manage different ad creatives
app_id string App ID Used for identifying and analyzing different mobile applications
app_name string App Name Used for identifying and analyzing different mobile applications
ref_url string Reference URL Used for analyzing traffic sources
creative_type string Creative Type, such as images, videos, etc. Used for classification and performance analysis
id string General ID Used to identify the uniqueness of the record
ad_id string Ad ID Used to distinguish and manage different ads
customer_id string Customer ID Used to distinguish and manage different ad customers
device_name string Device Name Used for device identification and analysis
browser_name string Browser Name Used for identifying the browser used by the user
bizdate string Business Date Used for statistics and analysis by date
bizhour string Business Hour Used for statistics and analysis by hour
data_source string Data Source Used to distinguish and analyze different data collection channels

In the area of advertising monitoring, some fields may be more commonly seen in the Chinese internet environment, mainly due to China’s unique advertising technology standards, device identifiers, and certain characteristics of some application markets:

Photo by Carlos Muza on Unsplash

oaid: Open Advertising Identifier, a device identifier introduced by Chinese device manufacturers to replace traditional identifiers and enhance privacy protection.

android_id: In China, many devices and advertising networks rely on this identifier.

open_udid: Open Unique Device Identifier, which is quite common on some Chinese advertising platforms and applications.

mac_md5: Although used globally, in the Chinese market, this field is often used for device identification.

imei, imei_md5, imei_sha1: IMEI is globally universal, but in China, especially in early advertising monitoring, it is common to see the use of IMEI and its encrypted forms.

idfa, idfa_md5, idfa_sha1: Although IDFA is a global standard for Apple devices, it is also frequently used in iOS advertising tracking in China.

ad_timestamp: The timestamp of the advertising event, universally used globally, but the format and specific implementation may vary by region.

app_package: The application package name, used to identify applications in China’s unique app markets.

app_name: The application name, which often appears in Chinese advertising monitoring to identify specific applications.

province_id, city_id, county_id: These geographical location identifiers are especially common in Chinese advertising monitoring, used for fine-grained regional analysis.

bizdate, bizhour: Fields used for statistics by date and hour, frequently used in Chinese advertising reports and analysis.

adzone_id, adzone_type: The type and ID of the advertising space, these fields are very common on Chinese advertising platforms for ad space management and analysis.

How to Read Advertising Monitoring Reports

Compare Data

Compare data from different time periods, platforms, and ad formats to identify areas of excellent performance and areas that need improvement.

Pay Attention to Trends

Observe the trends in data changes to predict future development trends, providing a basis for adjusting advertising strategies.

Deep Dive

For data that performs poorly, delve deeper into the underlying reasons, such as whether the advertising content, target audience, and placement platform are appropriate.

How to Use Advertising Monitoring Data to Optimize Advertising Strategies

Adjust Advertising Content

Based on user feedback and data analysis, optimize advertising copy, images, videos, and other elements to improve the attractiveness and conversion rate of advertisements.

Precisely Target the Audience

Understand the interests, needs, and behavioral habits of the target audience through data analysis to formulate more precise advertising placement strategies.

Optimize Placement Platforms and Timing

Choose more suitable advertisingplatforms and time slots based on data performance to increase the exposure and click-through rate of advertisements.

Control Advertising Budget

Allocate the advertising budget reasonably according to ROI and advertising effects to ensure the maximization of the input-output ratio.

Advertising monitoring reports are not only a set of data reports but also a valuable marketing guide. By deeply analyzing advertising monitoring data, we can better understand the performance of advertising activities, identify optimization space, and enhance advertising effectiveness.

Categories
AdTech

How Do We Monitor Advertising in China?

In China, the rapid development of the internet industry has become a thing of the past. Faced with increasingly precious traffic, brands and advertisers need to put in more effort to “explore” and manage. Advertising monitoring naturally becomes an indispensable part of the advertising placement industry chain. Through advertising monitoring, advertisers can understand the effectiveness of their placements and further optimize strategies to gradually improve the return on investment. This article will explore how advertising monitoring is implemented in the Chinese market and what the current state of advertising monitoring is like.

What to monitor?

In China, advertisers also focus on the exposure, clicks, and in-app interaction effects of advertisements.

Exposure Monitoring: Also known as “impression monitoring,” it is usually the channel vendors who pass the data back to the advertisers.

Click Monitoring: Monitoring the number of clicks, which can be collected by the advertisers themselves or passed back by the channel vendors through data transmission.

In-App Monitoring: Refers to the monitoring of behaviors/events within the APP, such as basic PV, UV, APP activation/registration/login, etc., and user retention on the next day, 7 days, 30 days, pay rate, ARPU value, etc. These data are generally collected through the integration of third-party monitoring companies’ SDKs within the app, and the interfaces provided by different apps will vary.

Photo by Farzad on Unsplash

Advertising Monitoring Process

To monitor the effectiveness of advertisements, advertisers fill in the corresponding monitoring address when creating the smallest unit of an advertisement, which is the creative. The monitoring URL generally includes the following macros: creative ID or advertisement ID identifier, user device identifier, IP, UA, operating system, etc., and special ones may include CLICKID, CALLBACK.

The entire monitoring process can be roughly divided into three steps:

  1.  Advertisers/ad agencies place advertisements with media outlets. When users browse and click on the advertisements, the media will report the data to the advertiser or a third-party advertising monitoring platform. Common third-party platforms include: Umeng, adMaster, and Miaozhen.
  2.  After users click on the advertisement, they enter the landing page and participate in the advertising activities, such as downloading and launching the APP. After completing a series of operations, the APP uploads the user data to the advertising monitoring platform through the corresponding interface. Of course, other interactive media such as websites and H5 can also monitor the interaction data from the source of the advertisement through tracking codes and embedded points.
  3.  After attribution through certain methods, the user’s relevant data will be associated with the channel merchant and ultimately fed back to the advertiser/ad agency.

Photo by Milad Fakurian on Unsplash

Data Reporting Methods for Advertising Monitoring: SDK & API

Advertising data monitoring in China is mainly implemented through SDK and API methods. The technical principles of the two are the same, both collecting user information and transmitting it back to the monitoring platform’s server for comparison. For example, when a user clicks on an advertisement link with tracking parameters, the monitoring platform collects the user’s IP, operating system version, device model, and other information through the link and stores it.

If a user clicks on an advertisement and is redirected to the App Store to download and activate the APP online, the APP will also collect all the user information stored by the monitoring platform.

Then, by matching the information collected when clicking on the link with the information collected after downloading and activating, subsequent conversion and other indicators can be monitored.

The SDK method is simple, easy to use, and powerful. Media outlets integrate SDKs into their Apps, and after completing certain development work, they can meet the vast majority of the needs of third parties and advertisers, with high accuracy and real-time performance.

The API method is flexible, versatile, and applicable to both Apps and mobile web pages. However, it requires media outlets to undertake some development work in accordance with API monitoring standards. API monitoring is divided into two types: C2S (Client to Server) API and S2S (Server to Server) API.

C2S, or Client to Server, refers to the terminal issuing a request instruction to the order placement proxy server. After the terminal receives and completes the instruction, it sends the completed instruction to the third-party monitoring proxy server, which conducts accurate traffic monitoring through mutual counting. Under the C2S model, user actions are directly reported to the third-party monitoring platform’s server, ensuring the timeliness and accuracy of the data. Renowned brand advertisers such as AdMaster and Nielsen often prefer this method to ensure seamless traffic authenticity verification.

S2S, or Server to Server, refers to the terminal issuing a request instruction to the order placement proxy server and then sending the completed instruction back to the order placement proxy server, which in turn sends the data to the third-party monitoring proxy server. This design may affect the timeliness of monitoring data while protecting user privacy, as it requires additional steps. Media outlets sometimes opt for S2S as an alternative strategy due to concerns over data security and may not support C2S monitoring.

C2S is more accurate and can reduce media cheating, commonly used by brand advertisers, but C2S requires client releases for each monitoring, making the implementation more complex.

Click Monitoring Methods: Synchronous Monitoring & Asynchronous Monitoring

Synchronous monitoring integrates the monitoring code with the landing page link. When a user clicks on an advertisement, they first visit the monitoring link, jump to the monitoring company’s server, and then jump to the landing page. Synchronous monitoring ensures the immediacy of the monitoring but may affect the user experience. In addition, synchronous monitoring does not support the transmission of parameters such as IDFA.

Asynchronous monitoring, on the other hand, directly redirects users to the landing page after clicking on the advertisement, with the media server sending a monitoring request to the monitoring company’s server. The asynchronous mode ensures a good user experience, but data transmission may be delayed. Moreover, since the request is sent by the server, the visits collected by the monitoring company all come from the same IP segment. If the client is targeting a specific city, determining the region solely based on the IP can lead to significant geographical discrepancies.

Current State of Advertising Monitoring

The mainstream third-party advertising media monitoring tools in China are TrackMaster introduced by AdMaster and AdMonitor introduced by Miaozhen. However, some dominant media outlets refuse third-party monitoring:

  1.  The first kind is top-tier vertical media, mainly out of concern for protecting their own data, fearing that clients obtaining the data will affect the media’s valuation and traffic value.
  2.  The second kind is dominant internet platforms, which often provide their own developed monitoring tools to clients.

Brands and advertisers must monitor advertising to better understand the effects, prevent data fraud, and continuously optimize the media mix, timing, geography, and creativity using the data obtained. The choice of monitoring mode depends on factors such as the brand’s demand for traffic authenticity, user privacy protection, and system compatibility between both parties. As the market evolves, China’s advertising monitoring methods may continue to evolve to adapt to the ever-changing advertising environment.

Source of featured image: Photo by Andrew Garrison on Unsplash

Categories
AdTech

Programmatic Advertising in China 101

China’s programmatic advertising market has seen unprecedented prosperity since 2012, a year that is also dubbed as the “Year One” of programmatic advertising in China. With the flourishing development of the internet traffic market, China’s programmatic advertising ecosystem has become increasingly mature, gradually meeting advertisers’ needs for fine-group screening of quality customers, comprehensive control and constant adjustment of the advertising process, following customer trends to lock media platforms, and recalling high-potential customers for repeated exposure. This article will provide a complete practical guide based on China’s programmatic advertising market.

01 Planning Phase

Step 1: Define Objectives

Before clarifying the objectives, brands often complete the analysis of the consumer portrait for the promoted product, competitive advertising analysis, and summary of product selling points. With the support of the above information, the brand needs to define the goals of programmatic advertising, whether it is to enhance brand exposure, improve customer awareness, or enhance purchase conversion.

Domestic traffic vendors and media types are diverse and numerous, with a vast array of conversion models and indicators. Advertisers and their agencies need to set targets that are specifically tailored to their advertising needs and platform indicators. Taking the AIPL model indicators of Alibaba, a top-tier e-commerce platform in China, as an example:

Aware: Within the last 15 days, passively interacted with the brand, including behaviors such as exposure & clicks, browsing (limited to one day), watching, etc.

Interest: Within the last 15 days, actively engaged with the brand, including behaviors like membership, followership, interactions, browsing, favorites/add to cart, claiming trial products/samples, etc.

Purchase: All consumers who have purchased brand products in the last two and a half years (2*365 days + 180 days), including those who made pre-sale deposits, scanned codes for Taobao eggs after purchase, used offline cloud POS payment consumers, made purchases via iStore mini-program, scanned codes for Taobao eggs after purchase, included consumers who purchased on Taoxian, including those who bought Tmall u-first samples) minus “Loyalty” consumers.

Loyalty: Consumers who have had positive comments/positive follow-up reviews or have purchased the brand’s products at least twice within the past 365 days.

Photo by Glenn Carstens-Peters on Unsplash

Step 2: Refine Audience Strategies

Audience strategies are often rooted in product features, brand tone, and combined with past advertising experiences. It is even possible to seek recommendations from local media, third-party advertising agencies, and traffic platforms. The premise of programmatic advertising effectiveness is the brand’s reasonable segmentation of user groups, so that in the process of traffic purchase and expansion, it can better hit the brand’s target audience. Specific classification methods can refer to the “4W1H” model.

Who: Refers to user attributes, judging what type of user it is based on attributes (gender, age, region, income, interests, etc.), such as student groups who love affordable makeup, white-collar workers who like to watch fashion bloggers’ videos, users with a high-level VIP status, etc.

When: Refers to the time corresponding to user behavior, from which the user’s visit duration, frequency, interval, etc., can be calculated. For example, first-time visits to the official website, not logged in for 30 days, purchased within 15 days, etc.

Where: Refers to the user’s source, such as entering through an ad click, through a friend’s share, or through a search engine, etc. Users from different sources represent different groups. For example, those who enter through search keywords belong to an active group of users, which is more in line with the advertiser’s needs; while those who enter by clicking on ads may be interested because of the attraction of the ad content, etc.

What: Refers to the user’s behavior, such as what type of ads they have clicked on, what content they have visited, what products they have purchased, etc.

How: Refers to the user’s quality, which can be measured by visit depth, number of behaviors, order amount, etc. For example, a user who has browsed 50 different product pages, a user who has made a total of 20 orders within a year, a user with an order amount of more than 100,000 yuan in 30 days, etc.

Step 3: Develop Media Strategy

In the face of numerous media resources, it is particularly important to formulate an appropriate media strategy before advertising, which depends on the objectives. The principle of formulating a media strategy is “positive, high coverage, and strong exposure,” and to design the media around advertising forms, page environments, media quality, advertising area, screen position, to meet the KPI requirements.

Advertising Forms: The form of advertising to some extent determines the user experience and interaction form. Common forms in programmatic advertising include banner image ads, video ads, native ads, etc.

Page Environment: Refers to the state of the page where the advertisement is placed, including page content, the number of page advertisements, etc. Especially when placing brand advertisements, advertisers usually require that the page content must be positive, in line with the brand image, and must not contain pornographic and vulgar, politically sensitive information, etc.. Moreover, the number of page advertisements should not be too many. An environment full of advertisements on the entire page will cause trouble for users and seriously affect the user experience, causing users to have a negative impression of the page and the advertisements within the page.

Media Quality: When formulating a media strategy, attention should be paid to the quality and quantity of the media. Quality refers to whether the media’s traffic scale and user groups are of high quality and in line with the advertiser’s needs. In addition, it is necessary to consider the category of these media (such as entertainment), channels (such as TV series), historical data of advertising positions (such as click-through rate), etc. Quantity refers to the media traffic being large enough to ensure sufficient user coverage and meet the advertiser’s budget.

Advertising Area: The ratio of advertising size and the proportion of advertising area on the page are also very important. If the advertising size is too small or the proportion of the entire page is too low, it is difficult to be discovered by users; non-standard size ratios will increase the cost of material production.

Screen Position: The screen position where the advertising position is located determines the probability of the advertisement being seen. The first screen is generally better than the non-first screen, and the effect of the last screen advertisement may be the worst. However, for some pages with high-quality content, the exposure probability of the second screen or even the third screen will also be high.

Step 4: Develop Creative Solutions

The first step in creating creativity is to grasp the form of creativity and the way users interact. The form of creativity refers to what file form the material is presented in, such as images, text, graphics and text, Flash, video, forms, or others. At present, video creativity and post creativity (such as information streams) have the best effects, which are related to the characteristics of the advertising space. The price of such advertising spaces is also a bit higher than that of ordinary advertising spaces.

User interaction refers to the specific operations of users on the material, such as clicking to switch dynamic creativity, filling in registration information on the creativity, expanding the material after clicking on the advertisement, and even submitting information by voice.

In the process of advertising, both the created creativity and the landing page need to undergo A/B testing or multi-version testing, using data to determine which version to adopt in the end. The premise of the test is to keep the test environment and the test volume of multiple versions as consistent as possible.

02 Execution Phase

Step 1: Advertising Preparation

The preparatory work before advertising mainly includes uploading qualifications for review, creating creativity for review, and deploying advertising monitoring, etc.

Qualifications are the necessary proof documents for advertisers to carry out advertising activities (such as business licenses, ICP filing screenshots, organization codes, etc.).

In terms of creativity, traffic parties will also have certain requirements for the effectiveness and legality of the content, so the media needs to review the creativity. Common review scopes include size, sound, etc.

In addition, advertisers generally use third-party monitoring during the advertising process, so there is also the deployment work of monitoring codes, etc. Optimization strategies need to add code in the advertiser’s game promotion page or SDK (or S2S docking), so that the DSP platform can adjust strategies according to different user behavior trajectories.

A good job in the early preparation work does not mean that the ads can be directly placed without manual intervention. Advertising activities should also be gradually increased in multiple stages to ensure the final effect. Programmatic advertising in China can be generally divided into four stages: technical docking test, strategy test, strategy optimization, and stable extension, each with a corresponding time period, and should be flexibly adjusted according to the actual situation of the project.

Photo by NMG Network on Unsplash

Technical Docking Test Phase: This phase usually lasts for 1 to 3 days, mainly to check whether the work in the preparation phase runs well, such as whether the statistical monitoring code is deployed correctly, whether S2S docking can correctly return data, etc.

Strategy Test Phase: This phase usually takes 3-7 days to verify whether the media strategy formulated in the advertising strategy is reasonable and whether the media effect has reached the expected level. Based on the test data, corresponding grade divisions are made for different AdX/SSP, different media, different advertising spaces, etc., so as to better allocate the budget in the later stage.

Strategy Optimization Phase: This phase usually lasts for about 1 week to 1 month. On the basis of optimization and adjustment in the early test phase, further optimization of the media is carried out, and the crowd strategy and creative strategy formulated in the advertising strategy are continuously optimized. During the strategy optimization phase, the fluctuation of advertising effects is generally large, which is a normal phenomenon. During this phase, various strategy combinations are usually tried, and the effects of different combinations may vary greatly. The goal of this phase is to quickly screen out the optimal combination of “media + audience group + creativity”, so that the advertising effect reaches a stable change and regular fluctuation trend, such as the effect of the weekend is better than working days, the effect of the evening peak period is better than the daytime, etc.

Stable Extension Phase: This phase is usually more than 1 month according to the brand’s needs. After the stable effect is achieved in the strategy optimization phase, the volume of traffic can be increased according to the budget. Especially in the RTB bidding model, the volume and price of traffic will fluctuate due to the different degrees of market competition, hence the operator needs to be able to find problems in time and take actions.

Step 2: Official Launch

After the qualification and material review are passed, the executor needs to add various advertising campaigns according to the planning plan of the advertising proposal and set up corresponding campaign.

Basic Settings

Bid Setting: Set the upper limit of the price that can be borne, generally in the form of CPM, to control the cost within an acceptable range. Some DSP can support bidding according to CPC or CPA (the algorithm replaces manual dynamic control of CPM bidding).

Budget Control: Set the budget according to the media budget plan provided by the advertiser/advertising agent to avoid excessive consumption. The budget is divided into daily budget, weekly budget, monthly budget, and total budget. Some DSP can also control the level of exposure and the number of clicks, corresponding to daily exposure, total exposure, or daily clicks, total clicks, etc. In addition, there are also settings for budget allocation, such as setting differentiated budgets for different regions, different creatives, etc.

Date and Time: Set the date or time period according to the advertising schedule, or there is no limit. Date and time can be set according to the online habits of the target audience. The date or the daily advertising time period will have an impact on the effect, such as weekends, evening peak periods.

Advertising Speed: The Advertising speed is divided into uniform speed and rapid speed. Some advertisers hope that the advertising budget can be as distributed as possible in each time period or every day, and the activity can be set to “uniform speed”.

Frequency Control: Set the total number of times a specific advertisement is seen by the same user within a set time, or the total number of times a certain advertising material is seen within a set time.

Media Settings

Transaction Model: Select the transaction model, including RTB open bidding, PDB direct purchase, etc.

Ad Exchange: Choose the channel for advertising, such as Baidu Bes, Alibaba Tanx, Tencent AdX, etc.

Media Category/Channel: Select the category of media or a specific channel under a single medium, such as financial, entertainment, sports, and other media categories, or TV drama, movie, technology, sports, and other channels under Youku media.

Media URL: Set specific media root domain names (e.g., qq.com), second-level domains (e.g., news.qq.com), or specific URL addresses.

Placement Size: Choose the placement size and arrange corresponding size materials. Generally, popular ad spaces or commonly used high-quality ad spaces are selected.

Ad Position: Choose the specific ad position, such as WeChat Search Super Brand Zone.

Ad Position Type: Choose the type of ad placement, such as banner, information game, OTV, etc.

Ad Viewability: According to the advertiser’s requirements for viewability, the operators can only target media resources with a viewability higher than a certain value, or conversely, they can exclude media resources with a viewability lower than a certain value and not place ads on this part of the media resources.

Page Ad Slot Quantity: Since the number of ad slots on the page will affect the user experience, it may indirectly cause the user to have a negative impression of the page’s ads. Therefore, when placing ads, you can control the number of ad slots on the page, such as only targeting pages with up to 3 ad slots.

Screen Order: Choose the screen order where the ad space is located, such as the first screen, the second screen, etc. Generally, it is necessary to exclude the bottom of the page such as the tail screen and other positions where users generally cannot see this ad space.

Page Content: Choose to place ads based on designated page keywords, video content direction, such as only placing pages containing baby-related keywords, or only placing workplace drama video ads, and brand can also directly specify TV drama names for directional advertising.

Target Audience Settings

Advertisers can collect people who have seen, clicked on, and visited the official website during the advertising process, and retarget them or use them as the seed segment for look-alike extensions. The target audience may include people with needs, potential needs, and even those who have made purchases, as well as those who are using the product/service or the lost audience.

Creative Settings

Creative and landing page settings: Set up the creative and corresponding landing pages for different advertising campaigns. It should be noted that some AdX will require the landing page to support HTTPS.

Display rules: Set the rules for the order in which the creative is displayed to the same person multiple times. The general rules for the order in which users see the creative are loop rotation, sequential display, etc. For example, if you need to display creative A, B, C to the same user, with a frequency limit of 6 times a week, the order in which a user sees the creative can be AABBCC, ABCABC, etc.

Other Settings

Third-party monitoring: Set the exposure monitoring code and click monitoring code of the third-party monitoring platform.

Brand protection: Select the brand safety supplier that the DSP platform has connected and fill in the corresponding information.

Anti-fraud: Set up to filter fraudulent traffic. Some DSP platforms have anti-fraud mechanisms themselves, but some advertisers will also find third-party anti-fraud suppliers for traffic filtering in order to ensure the effectiveness and reduce waste.

03 Review Phase

Based on the actual feedback data during the advertising period, the brand can summarize the experience and guide subsequent campaigns through comparison, attribution, segmentation, and intersection.

Photo by Jonas Leupe on Unsplash

Media optimization: Make the optimal media combination according to the media crowd matching degree, media overlap degree, and media saturation degree. Media matching degree refers to the ratio of the advertiser’s target audience that can be covered in the media; Media overlap degree refers to the ratio of the target audience that overlaps between multiple media; Media saturation degree refers to the ratio of the target audience that has been covered in the media to the total target audience of the media.

Creative Optimization: The match between the ad’s creative and its intended message plays a significant role in determining the effectiveness of an ad campaign. Ad matching refers to how well the creative aligns with the ad’s appeal.

Frequency Adjustment: Identify the optimal frequency by analyzing data from groups exposed to different levels of ad impressions, and establish reasonable frequency capping.

Audience Adjustment: Depending on the scale of the target audience and their conversion outcomes, you can correspondingly increase or decrease the targeting of audience segments.

Viewable Exposure Optimization: Optimize based on data from ad viewability, analyzing visibility metrics across various ad placements, regions, times, and browsers (for instance, visibility might be lower in certain areas or browsers due to differences in audience characteristics or internet connectivity issues). Filter out those with low viewability and fine-tune the advertksk g with various campaign settings to form the best combination.

Source of featured image: Photo by Mario Calvo on Unsplash

Categories
AdTech Digital Marketing Marketing

101 of YOYI TECH programmatic advertising

Yoyi Tech, through its programmatic advertising platform, offers a range of features and capabilities that position it as a leader in the Chinese digital advertising landscape. Here are the key aspects of Yoyi Tech’s programmatic advertising:

Key Features of Yoyi Tech’s Programmatic Advertising

1. Comprehensive Audience Targeting

Yoyi Tech specializes in precision targeting technology, allowing advertisers to reach specific audience segments based on various criteria, including demographics, interests, and behaviors. This capability enhances the effectiveness of ad campaigns by ensuring that ads are shown to the most relevant users .

2. Integration of Online and Offline Data

Yoyi’s platform integrates multi-channel data, combining online and offline consumer interactions. This holistic view enables brands to maximize their return on investment (ROI) by understanding customer behavior across different touchpoints .

3. Rich Ad Formats

The platform supports a variety of ad formats, including display, video, and mobile ads. This versatility allows advertisers to choose the most effective format for their target audience and campaign objectives .

4. Real-Time Optimization

Yoyi Tech employs advanced algorithms for real-time optimization of ad placements and bidding strategies. This ensures that campaigns can adapt quickly to changing market conditions and user behaviors, improving overall performance .

5. Cross-Screen Capability

Yoyi’s programmatic platform enables cross-screen audience targeting, allowing advertisers to engage consumers across multiple devices—desktop, mobile, and smart TVs—enhancing brand impact and engagement .

6. Data Management Platform (DMP) Integration

The platform integrates with data management systems to leverage first-party and third-party data for improved targeting and personalization. This integration helps advertisers make data-driven decisions that enhance campaign effectiveness .

7. Access to Extensive Inventory

Yoyi Tech claims to reach up to 80% of China’s media inventory, providing advertisers with a broad range of opportunities to place their ads across various publishers and platforms .

8. Dynamic Creative Optimization

Yoyi utilizes AI capabilities for dynamic creative optimization, allowing advertisers to tailor ad content in real-time based on audience interactions and preferences. This feature helps maintain user interest and improves engagement rates .

Yoyi Tech’s programmatic advertising solutions are characterized by advanced targeting capabilities, integration of comprehensive data sources, real-time optimization features, and a wide array of ad formats. These elements collectively enhance the effectiveness of advertising campaigns in China’s competitive digital landscape, making Yoyi Tech a significant player in the programmatic advertising space.

How does YOYI’s dataset contribute to the development of programmatic advertising models

Yoyi’s dataset plays a crucial role in the development of programmatic advertising models by providing rich, actionable insights that enhance targeting, optimization, and overall campaign effectiveness. Here are the key contributions of Yoyi’s dataset to programmatic advertising:

1. Comprehensive Audience Insights

Yoyi’s extensive dataset includes demographic, behavioral, and psychographic information, which allows advertisers to build detailed audience profiles. This data enables precise targeting, ensuring that ads reach the most relevant users based on their interests and behaviors .

2. Data Integration Across Channels

Yoyi integrates online and offline data sources, creating a unified view of customer interactions across multiple touchpoints. This holistic approach allows for better understanding of the customer journey, enhancing the ability to tailor advertising strategies effectively .

3. Dynamic Audience Segmentation

The platform utilizes advanced algorithms to segment audiences dynamically based on real-time data. This capability ensures that advertisers can adjust their targeting strategies quickly in response to changing consumer behaviors and market conditions .

4. Predictive Analytics

Yoyi employs machine learning techniques to analyze historical data and predict future customer behaviors. By identifying patterns such as purchase propensity and churn risk, advertisers can prioritize high-value segments in their campaigns, optimizing ad spend for maximum impact .

5. Real-Time Optimization

With access to real-time data, Yoyi’s programmatic models can continuously optimize ad placements and bidding strategies. This responsiveness helps improve campaign performance by ensuring that ads are served at the right time and context .

6. Enhanced Creative Personalization

The dataset supports dynamic creative optimization, allowing advertisers to tailor ad content based on audience insights. This personalization increases engagement rates by delivering relevant messages that resonate with specific user segments .

7. Multi-Touch Attribution

Yoyi’s platform enables multi-touch attribution analysis, helping advertisers understand the effectiveness of various touchpoints throughout the customer journey. This insight allows for better allocation of advertising budgets across channels based on performance metrics .

Conclusion

Overall, Yoyi’s dataset significantly enhances the capabilities of programmatic advertising models by providing deep insights into audience behavior, enabling real-time adjustments, and fostering personalized ad experiences. These features collectively contribute to more effective advertising strategies that drive engagement and conversions in a competitive market like China.

Categories
AdTech China Marketing Digital Marketing DSP Marketing Products

How do short video platforms like Douyin and Kuaishou influence video programmatic advertising

Short video platforms like Douyin and Kuaishou have significantly influenced video programmatic advertising in China through various mechanisms that enhance user engagement and drive advertising effectiveness. Here are the key ways these platforms impact the landscape:

1. Massive and Engaged User Base

Both Douyin and Kuaishou boast substantial daily active users—over 400 million for Douyin and around 300 million for Kuaishou. This vast audience provides advertisers with extensive reach, allowing brands to target diverse demographics effectively. The high engagement levels on these platforms mean that ads are more likely to be viewed and interacted with compared to traditional media channels .

2. Content-Driven Advertising

Douyin and Kuaishou prioritize creative, entertaining, and authentic content. Advertisers can create video ads that blend seamlessly with user-generated content, making them less intrusive and more appealing to viewers. This approach enhances user experience, as ads that resonate with the platform’s culture tend to perform better in terms of engagement .

3. Advanced Targeting Options

Both platforms utilize sophisticated algorithms to analyze user behavior and preferences, enabling advertisers to deploy advanced targeting strategies. Advertisers can reach niche audiences based on interests, browsing habits, and demographic information, ensuring that their messages are relevant and timely . This precision targeting is crucial in a competitive advertising environment.

4. Integration with E-Commerce

Kuaishou has made significant strides in integrating e-commerce features into its platform, allowing users to purchase products directly during video streams. This capability enhances the effectiveness of video programmatic advertising by providing a seamless shopping experience that can lead to higher conversion rates. Douyin is also developing similar functionalities, making it easier for brands to convert views into sales .

5. Interactive Ad Formats

The platforms offer various interactive ad formats, such as live-streaming ads and branded challenges, which encourage user participation and engagement. For instance, live-streaming on Kuaishou fosters a sense of community and connection between hosts and viewers, which can lead to higher trust and increased sales conversions .

6. Real-Time Feedback and Analytics

Advertisers benefit from real-time analytics provided by these platforms, allowing them to monitor campaign performance closely. This data-driven approach enables brands to adjust their strategies quickly based on viewer interactions and preferences, optimizing ad spend and improving overall effectiveness .

7. Cultural Relevance

Both Douyin and Kuaishou reflect cultural trends and consumer interests in China. Advertisers who align their messaging with current trends or popular content on these platforms can enhance their brand’s relevance and appeal, leading to better engagement outcomes .

In summary, Douyin and Kuaishou significantly shape video programmatic advertising in China by providing vast audiences, promoting creative content integration, enabling advanced targeting options, facilitating e-commerce interactions, offering interactive formats, delivering real-time analytics, and fostering cultural relevance. These factors collectively enhance the effectiveness of advertising campaigns on these platforms.

Categories
AdTech China Marketing Digital Marketing DSP Marketing Products

What are the key factors driving the popularity of video programmatic advertising in China

The popularity of video programmatic advertising in China is driven by several key factors that reflect the unique characteristics of the market and consumer behavior. Here are the main drivers:

1. Rapid Growth of Mobile Internet Users

China has seen a dramatic increase in mobile internet users, reaching over 829 million. This growth has shifted content consumption predominantly to mobile devices, making video ads particularly effective as they align with how users engage with media on their smartphones and tablets .

2. Rising Demand for Video Content

Video content consumption is surging in China, with platforms like Douyin (TikTok) and Kuaishou leading the way. As users increasingly prefer video over other formats, advertisers are adapting by investing more in video programmatic advertising to capture audience attention effectively .

3. Enhanced Targeting Capabilities

AI-driven programmatic advertising allows for precise audience targeting based on user data and behaviors. This capability enables advertisers to deliver relevant video ads to specific demographics, increasing engagement and conversion rates .

4. Cost-Effectiveness and Efficiency

Programmatic buying automates the ad purchasing process, reducing costs and improving efficiency. Advertisers can optimize their budgets by targeting specific audiences without the inefficiencies associated with traditional media buying methods . This efficiency is particularly appealing in a competitive market.

5. Integration with E-Commerce

The rise of live e-commerce and shoppable video ads has created new opportunities for advertisers. Platforms often allow users to purchase products directly while watching videos, enhancing user engagement and driving sales simultaneously . This seamless integration between content and commerce is a significant factor in the growth of video programmatic advertising.

6. Improved User Experience

Video ads can be more engaging than static formats, providing richer storytelling opportunities that resonate with viewers. The ability to create immersive experiences helps brands connect emotionally with their audience, leading to higher retention and engagement rates .

7. Innovative Ad Formats

The development of interactive and innovative ad formats, such as augmented reality (AR) and virtual reality (VR) experiences within video ads, has also contributed to their popularity. These formats capture user interest more effectively than traditional ads .

8. Support from Major Platforms

Dominant players like Baidu, Alibaba, and Tencent have developed their own programmatic advertising technologies, providing robust infrastructure for video programmatic buying. Their extensive reach ensures that advertisers can access large audiences through targeted video campaigns .

In summary, the combination of a growing mobile user base, increasing demand for video content, advanced targeting capabilities, cost-effectiveness, integration with e-commerce, and support from major platforms are all key factors driving the popularity of video programmatic advertising in China.

Categories
AdTech China Marketing Digital Marketing DSP Marketing Products

How does AI-driven programmatic advertising improve user engagement in China

AI-driven programmatic advertising significantly enhances user engagement in China through several innovative strategies and technologies. Here are the key ways in which it achieves this:

1. Personalized Advertising Experiences

AI enables advertisers to analyze vast amounts of user data, allowing for highly personalized marketing messages tailored to individual preferences and behaviors. This personalization increases the relevance of ads, making users more likely to engage with the content. For instance, platforms like Alibaba utilize AI to recommend products based on users’ browsing history and purchasing patterns, leading to higher engagement rates .

2. Dynamic Content Optimization

AI-driven programmatic advertising allows for real-time adjustments to ad content based on user interactions. This means that if an ad is not performing well, it can be modified on-the-fly to better suit the audience’s preferences. This responsiveness keeps the content fresh and engaging, reducing ad fatigue among users .

3. Contextual Targeting

By leveraging AI, advertisers can deliver ads that are contextually relevant to the content being consumed by users. This method ensures that ads appear in environments where they are most likely to resonate with the audience, such as video ads on platforms like Douyin (TikTok) or Youku. Contextual relevance enhances user engagement by aligning ads with user interests at the moment they are consuming related content .

4. Enhanced User Insights

AI tools provide deeper insights into consumer behavior and preferences, enabling advertisers to refine their targeting strategies continuously. By understanding what drives user engagement, brands can create more compelling campaigns that resonate with their target audiences, ultimately leading to higher interaction rates .

5. Interactive and Engaging Formats

AI facilitates the creation of interactive ad formats that engage users more effectively than traditional static ads. For example, AI scene marketing platforms can integrate brand exposure directly into video content, allowing for seamless interactions where users can purchase products while watching videos. This immersive experience significantly boosts user engagement .

6. Efficient Retargeting Strategies

AI-driven programmatic advertising excels in retargeting users who have previously interacted with a brand but did not convert. By serving tailored ads based on past behaviors, advertisers can re-engage potential customers effectively, enhancing conversion rates and overall engagement .

7. Utilization of Rich Media

The rise of video content consumption in China makes programmatic video advertising particularly effective. AI helps optimize video ads for specific audiences and contexts, ensuring that they capture attention and encourage interaction. As users increasingly engage with video content on platforms like Kuaishou and Douyin, this strategy becomes crucial for maintaining high engagement levels

In summary, AI-driven programmatic advertising improves user engagement in China by delivering personalized, relevant, and interactive experiences that resonate with consumers’ interests and behaviors. This approach not only enhances the effectiveness of advertising campaigns but also fosters stronger connections between brands and their audiences.
Categories
AdTech China Marketing Digital Marketing DSP Marketing Products

Why need AI-Driven programmatic advertising in China

AI-driven programmatic advertising is increasingly essential in China for several reasons, reflecting the unique challenges and opportunities within the market. Here are the key factors that highlight the need for this approach:

1. Efficiency and Cost-Effectiveness

Programmatic advertising automates the buying and selling of ad space through AI and machine learning, significantly reducing the time and resources required compared to traditional advertising methods. This efficiency translates into lower costs for advertisers, allowing them to allocate their budgets more effectively across various channels .

2. Enhanced Targeting Capabilities

With the vast amount of data available in China, AI-driven programmatic advertising enables precise audience targeting. Advertisers can segment audiences based on demographics, behaviors, interests, and contextual factors, ensuring that ads reach the most relevant users. This capability helps improve engagement rates and return on investment (ROI) .

3. Adaptation to Mobile Consumption Trends

China has a massive mobile user base, with over 829 million mobile internet users consuming content primarily through their smartphones. Programmatic advertising is particularly effective in this environment, allowing advertisers to deliver targeted ads on mobile platforms where consumer attention is concentrated .

4. Dynamic Content Optimization

AI technologies enable real-time adjustments to ad content and placements based on performance data. This dynamic optimization means that advertisers can quickly respond to changing consumer behaviors and preferences, enhancing the effectiveness of their campaigns .

5. Improved User Experience

AI-driven advertising can enhance user experience by reducing irrelevant ads and improving ad relevance. By analyzing user data, AI can help deliver personalized content that resonates with individual consumers, leading to higher engagement and satisfaction.

6. Integration with Emerging Technologies

The integration of AI with other technologies such as blockchain, augmented reality (AR), and virtual reality (VR) is beginning to reshape advertising in China. These innovations allow for more immersive and interactive ad experiences, which can capture consumer interest more effectively than traditional formats .

7. Data-Driven Insights

AI facilitates advanced analytics that provide advertisers with deeper insights into campaign performance and consumer behavior. These insights allow for better decision-making and strategy adjustments, ultimately improving campaign outcomes .

8. Competitive Advantage

As competition intensifies in the Chinese market, leveraging AI-driven programmatic advertising can provide brands with a significant edge over competitors who rely on traditional methods. The ability to adapt quickly to market changes and consumer preferences is crucial in a fast-paced environment

In summary, AI-driven programmatic advertising addresses many of the pain points faced by advertisers in China today, including inefficiencies in traditional models, the need for precise targeting, and the demand for engaging content tailored to mobile users. As the digital landscape continues to evolve, adopting these advanced technologies will be essential for brands aiming to succeed in this dynamic market.

Categories
AdTech China Marketing Digital Marketing DSP Marketing Products

What specific targeting options does Yoyi DSP offer for niche audiences

Yoyi DSP offers a range of specific targeting options designed to help advertisers effectively reach niche audiences. Here are the key targeting features available:

1. Behavioral Targeting

Yoyi DSP allows advertisers to target users based on their online behaviors, such as browsing history, engagement with previous ads, and interaction with specific content. This enables brands to reach audiences who have shown interest in similar products or services.

2. Demographic Targeting

Advertisers can define their target audience based on demographic factors like age, gender, income level, and education. This granular approach helps in reaching specific segments that are most likely to convert.

3. Interest-Based Targeting

Yoyi DSP enables targeting based on user interests and preferences. Advertisers can create segments around particular hobbies, lifestyles, or topics that resonate with their niche offerings.

4. Contextual Targeting

This feature allows ads to be displayed on websites or within content that is contextually relevant to the advertised product. For example, an ad for outdoor gear can appear on travel blogs or adventure-related content, ensuring it reaches an audience likely to be interested.

5. Geographic Targeting

Advertisers can focus on specific geographic areas to reach local audiences or regions where their products are most relevant. This is particularly useful for businesses that cater to localized markets.

6. Retargeting Options

Yoyi DSP provides robust retargeting capabilities, allowing advertisers to reconnect with users who have previously interacted with their brand but did not convert. This includes serving ads to users who visited a website or engaged with a specific product.

7. Custom Audiences

Advertisers can create custom audience segments using first-party data from their own customer databases. This allows for highly tailored campaigns that align closely with existing customer profiles.

8. Lookalike Audiences

Yoyi DSP can identify and target new users who share similar characteristics and behaviors with existing customers. This expands the reach while maintaining relevance to the niche market.These targeting options make Yoyi DSP a powerful tool for advertisers aiming to connect with niche audiences effectively, enhancing engagement and conversion rates through precise and relevant ad placements.

Categories
AdTech China Marketing Digital Marketing DSP Marketing Products

What unique features does Yoyi DSP offer compared to iPinYou

Yoyi DSP and iPinYou are two prominent demand-side platforms (DSPs) in China, each with unique features that cater to different aspects of digital advertising. Here’s a comparison highlighting their distinctive offerings:

Unique Features of Yoyi DSP

  1. Data Management Platform (Data Bank):
    • Yoyi DSP has developed a comprehensive Data Bank that allows clients to collect and analyze first-party data from various campaigns. This platform provides insights into consumer behavior, enabling advertisers to optimize their strategies effectively
  2. Integrated Ad Formats:
    • Yoyi offers a unified platform that integrates multiple ad formats, including display, video, and mobile ads. This allows advertisers to manage all their campaigns from a single interface, streamlining the process and improving efficiency.
  3. Focus on Full Funnel Tracking:
    • Yoyi emphasizes tracking the entire consumer journey, from ad exposure to conversion. This capability helps advertisers understand the effectiveness of their campaigns at various stages and adjust strategies accordingly.
  4. Advanced Audience Targeting:
    • Utilizing AI-driven algorithms, Yoyi DSP provides sophisticated audience segmentation and targeting capabilities. This enhances the precision of ad placements and improves overall campaign performance.
  5. Historical Data Utilization:
    • Yoyi leverages historical data for predictive analytics, allowing advertisers to make informed decisions based on past campaign performances and trends.

Unique Features of iPinYou

  1. Strong RTB Technology:
    • iPinYou is known for its robust real-time bidding (RTB) capabilities, which allow for quick and efficient bidding processes on ad impressions across various platforms.
  2. Dynamic Creative Optimization:
    • iPinYou focuses on dynamic creative optimization, enabling advertisers to tailor their ads in real-time based on audience interactions and preferences. This feature enhances engagement by delivering more relevant ad content.
  3. Extensive Audience Profiling:
    • The platform provides advanced audience profiling tools that help advertisers identify and target specific consumer segments effectively. This enhances the effectiveness of campaigns by reaching the right audiences.
  4. Partnerships for Enhanced Inventory Access:
    • iPinYou has established partnerships with various publishers and ad exchanges, giving it access to a broad inventory of ad placements, which is crucial for maximizing reach and effectiveness.
  5. Multi-dimensional Reporting:
    • The platform offers comprehensive reporting features that provide insights into campaign performance across multiple dimensions, allowing for better optimization and strategy adjustments.

Summary

While both Yoyi DSP and iPinYou offer valuable services in the digital advertising space, Yoyi stands out with its integrated Data Bank and full funnel tracking capabilities, making it particularly strong in data utilization and campaign management. In contrast, iPinYou excels in real-time bidding technology and dynamic creative optimization, focusing on delivering highly relevant ads through extensive audience profiling. Each platform has its strengths tailored to different advertising needs within the Chinese market.

Categories
AdTech China Marketing Digital Marketing DSP Marketing Products

Top 5 AI-Driven DSP in China

Here are five notable AI-driven demand-side platforms (DSPs) in China, including Yoyi DSP, which exemplifies the integration of artificial intelligence in digital advertising:

1. Yoyi DSP

Yoyi DSP is a leading platform that utilizes AI algorithms for programmatic advertising. It focuses on optimizing ad placements and targeting through data analysis, helping advertisers reach their desired audiences effectively. Yoyi DSP’s machine learning capabilities enhance campaign performance by continuously learning from user interactions.

2. Baidu DSP

Baidu’s DSP leverages its extensive search and user data to optimize advertising campaigns. The platform employs AI for precise audience segmentation and real-time ad placement adjustments, ensuring high engagement rates and maximizing return on investment for advertisers.

3. Alibaba DSP

Alibaba’s advertising platform integrates AI to analyze consumer behavior across its vast ecosystem, including e-commerce and cloud services. This allows for targeted advertising that resonates with specific demographics, utilizing machine learning to refine campaign strategies dynamically.

4. Tencent DSP

Tencent’s DSP benefits from its social media networks, such as WeChat and QQ, to deliver highly personalized ads. The platform uses AI to analyze user interactions and preferences, enabling advertisers to create more relevant and engaging campaigns.

5. Kuaishou DSP

Kuaishou, known for its short-video content, employs AI-driven analytics to optimize video ad placements. The platform analyzes viewer behavior and trends to deliver personalized ads that align with user interests, significantly improving ad effectiveness.These platforms illustrate the growing trend of AI integration in digital advertising in China, enhancing targeting precision and overall campaign performance.

How does Yoyi DSP compare to other leading AI-driven DSP companies in China

Yoyi DSP is a prominent player in China’s demand-side platform (DSP) market, but it faces stiff competition from several other leading companies. Here’s a comparison of Yoyi DSP with some of its key competitors:

Yoyi DSP Overview

  • Founded: 2007
  • Focus: Specializes in precision targeting technology and internet marketing services.
  • Capabilities: Offers both impression-based and performance-based advertising solutions. It has developed a robust network of top publishers in China and utilizes AI for audience targeting and campaign optimization.
  • Unique Features: Yoyi has integrated multiple ad formats (video, mobile, display) into a unified system and launched a data management platform (Data Bank) to enhance data utilization for advertisers.

Comparison with Other Leading DSPs

Feature/Company Yoyi DSP iPinYou Tencent DSP Alibaba DSP Kuaishou DSP
Founded 2007 2008 1998 1999 2011
Market Position Major player in China Largest DSP in China Strong presence in social media Significant in e-commerce Emerging player in video ads
Technology RTB, AI-driven targeting Advanced RTB technology, cloud computing, audience profiling
2
AI for social media targeting AI for cross-platform solutions AI for video ad optimization
Client Base Over 300 top brands Serves over 200 brands Extensive user base via WeChat Extensive e-commerce partnerships Focused on short-video content
Ad Formats Video, mobile, display Primarily display ads Social media ads E-commerce ads Short videos
Data Management Data Bank for first-party data Proprietary audience profiling Strong data integration capabilities Comprehensive data analytics Limited data capabilities

Key Insights

  • Market Leadership: iPinYou is recognized as the largest DSP in China, leveraging advanced real-time bidding (RTB) technologies and extensive audience profiling capabilities. This positions it as a formidable competitor to Yoyi
  • Integration with Social Media: Tencent’s DSP benefits from its integration with social media platforms like WeChat, allowing it to deliver highly personalized ads based on user interactions. This gives Tencent an edge in consumer engagement.
  • E-commerce Focus: Alibaba’s DSP excels in leveraging its vast e-commerce ecosystem to provide targeted advertising solutions that are particularly effective for retail brands. This specialization contrasts with Yoyi’s broader focus on various ad formats.
  • Video Advertising Growth: Kuaishou is rapidly emerging as a strong competitor by focusing on video advertising, capitalizing on the popularity of short-form video content among users. This niche may attract advertisers looking to engage younger audiences effectively.

In summary, while Yoyi DSP is a significant player with strong technological capabilities and a diverse client base, it contends with well-established competitors like iPinYou, Tencent, Alibaba, and Kuaishou, each leveraging unique strengths in the rapidly evolving digital advertising landscape in China.

Categories
AdTech China Marketing Digital Marketing Growth Marketing

A Comprehensive Guide to Digital Marketing, Content Marketing, Advertising, and User Growth for International Tourism Companies in China

As China continues to grow as a leading global market, international tourism companies are increasingly looking to tap into the vast potential of Chinese consumers. However, to successfully penetrate this market, it is crucial to understand the unique dynamics of Chinese digital marketing, content marketing, advertising, and user growth strategies. This comprehensive guide explores how international tourism companies can effectively localize their marketing efforts in China, with a focus on industry-specific strategies, real-world examples, and data-driven insights.

1. The Digital Landscape in China

Before delving into strategies, it’s essential to grasp the distinctive digital ecosystem in China. Unlike in Western markets, where Google, Facebook, and Instagram dominate, China has developed its own robust digital infrastructure. The primary players in the Chinese digital landscape include:

  • WeChat: More than just a messaging app, WeChat is a super-app used for social networking, payments, booking services, and much more. With over 1.2 billion monthly active users, WeChat is indispensable for any digital marketing strategy in China.

  • Alipay: Similar to WeChat, Alipay started as a mobile payment platform but has since evolved into a comprehensive lifestyle app with over 1 billion users.

  • Baidu: The primary search engine in China, equivalent to Google in the West, Baidu is critical for SEO and SEM strategies.

  • Weibo: A microblogging platform akin to Twitter, Weibo is widely used for brand awareness, user engagement, and influencer marketing.

  • Douyin (TikTok): The leading platform for short-form videos, Douyin is essential for capturing the attention of younger demographics.

  • Xiaohongshu (Little Red Book): A social commerce platform, Xiaohongshu is especially popular among Chinese consumers for product recommendations and reviews.

Understanding and leveraging these platforms is key to creating a successful digital marketing strategy in China.

2. Digital Marketing Strategies for International Tourism Companies

2.1. Website Localization

For international tourism companies, a well-localized website is the cornerstone of any successful digital marketing campaign in China. This process goes beyond mere translation; it involves adapting the website to cater to the cultural and technical preferences of Chinese consumers.

  • Language and Cultural Adaptation: Simplified Chinese is the standard, but more than language, content must resonate with Chinese cultural values. This includes using culturally relevant images, symbols, and narratives that appeal to local sensibilities.

  • Mobile Optimization: Given that most Chinese consumers access the internet via mobile devices, ensuring that your website is mobile-optimized is crucial. Google AMP (Accelerated Mobile Pages) is less relevant here, while the focus should be on WeChat’s built-in browser compatibility.

  • SEO and Baidu: Unlike Google, Baidu’s algorithms favor websites hosted within China, written in Simplified Chinese, and compliant with local regulations. Incorporating Baidu-specific SEO strategies, including proper keyword usage and meta tags in Chinese, is essential.

Case Study: Booking.com

Booking.com provides a solid example of website localization done right. When entering the Chinese market, they localized their website content, optimized it for mobile, and ensured it was hosted within China. They also created a dedicated WeChat mini-program, enabling seamless mobile booking and payments directly within the app. This localized approach significantly improved Booking.com’s visibility and user engagement in the Chinese market.

2.2. Social Media Marketing

Social media platforms in China are integral to digital marketing, offering unique opportunities for tourism companies to engage with potential travelers.

  • WeChat Official Accounts: Creating an official WeChat account allows tourism companies to post updates, share content, and directly engage with followers. Through WeChat’s mini-programs, companies can also facilitate bookings, provide customer service, and offer promotions.

  • Weibo Marketing: Weibo’s open network allows for broader brand exposure. Companies can leverage Weibo for content sharing, trend monitoring, and influencer collaborations to enhance brand visibility.

  • Douyin Campaigns: Douyin’s short-form video format is perfect for showcasing travel destinations in a visually appealing manner. Engaging users through challenges or hashtags can create viral content that significantly boosts brand awareness.

Case Study: AirAsia

AirAsia leveraged WeChat and Weibo to execute a comprehensive social media strategy in China. They used WeChat for personalized customer interactions and to offer exclusive promotions. On Weibo, they ran contests and collaborated with influencers to amplify their reach, successfully driving significant traffic to their booking platforms.

3. Content Marketing Strategies

Content marketing is an effective tool for educating and engaging potential travelers. However, the content must be carefully tailored to fit Chinese tastes and consumption habits.

3.1. Storytelling with Localized Content

Chinese consumers are particularly receptive to narratives that reflect their values and aspirations. For tourism companies, this means crafting stories that resonate with themes of family, luxury, tradition, and modernity.

  • Cultural Relevance: Content should highlight aspects of your destinations that appeal to Chinese tourists, such as unique cultural experiences, luxury offerings, or famous landmarks. Incorporate Chinese holidays and travel trends into your content calendar.

  • Visual Content: Chinese consumers favor visual content, so high-quality images and videos should be central to your strategy. Platforms like Douyin and Xiaohongshu thrive on visually appealing, short-form content that is easily shareable.

Case Study: Marriott International

Marriott International has excelled in content marketing by creating localized stories that cater to Chinese travelers. They launched campaigns featuring popular travel destinations like Bali and Tokyo, with content focusing on luxury experiences and family vacations, aligning with Chinese travelers’ preferences. They also utilized Xiaohongshu for influencer partnerships, where influencers shared their experiences at Marriott hotels, driving engagement and bookings.

3.2. User-Generated Content (UGC)

Chinese consumers place a high level of trust in peer recommendations, making user-generated content a powerful tool for tourism marketing.

  • Encouraging UGC: Promote campaigns that encourage users to share their travel experiences on platforms like Xiaohongshu and Weibo. Offering incentives such as discounts or features on official channels can motivate users to contribute.

  • UGC Curation: Curating and sharing UGC on your official platforms can enhance credibility and provide authentic insights into your offerings.

Case Study: Trip.com

Trip.com effectively harnesses UGC by encouraging travelers to share their experiences on Xiaohongshu. They run campaigns where users can post reviews and photos of their trips, with the chance to be featured on Trip.com’s official account. This strategy not only boosts engagement but also builds trust among potential travelers.

4. Advertising Strategies for Tourism in China

In China, digital advertising is essential for reaching a wider audience, but it requires a nuanced approach to be effective.

4.1. Programmatic Advertising

Programmatic advertising allows for automated, real-time bidding on ad inventory across various platforms, ensuring targeted ad placements that reach the right audience.

  • Baidu Advertising: Baidu offers various programmatic advertising options, including display ads, native ads, and search ads. By leveraging Baidu’s data on user behavior, companies can target ads more effectively.

  • Tencent Ads: Through Tencent’s advertising platform, companies can place ads across WeChat, QQ, and other Tencent-owned properties. These ads can be highly targeted based on demographics, interests, and behavior.

Case Study: Expedia

Expedia has successfully used programmatic advertising in China by partnering with Baidu and Tencent. They ran targeted campaigns on Baidu using search and display ads, focusing on users searching for international travel. On WeChat, they used personalized ads to reach users based on their travel interests, driving significant traffic to their mobile booking platform.

4.2. Video Advertising

With the rise of video consumption, particularly on platforms like Douyin and Youku, video advertising has become a crucial component of digital marketing in China.

  • Short-Form Video Ads: Douyin’s short-form video ads are highly engaging and can quickly capture the attention of users. Tourism companies can create immersive videos showcasing destinations, itineraries, or travel experiences.

  • OTT Advertising: Over-the-top (OTT) advertising on platforms like iQIYI and Youku allows brands to reach consumers through smart TVs and mobile devices. These ads are particularly effective for reaching affluent, tech-savvy consumers.

Case Study: Singapore Tourism Board

The Singapore Tourism Board used video advertising on Douyin to promote Singapore as a top travel destination. They created a series of short, engaging videos that highlighted Singapore’s unique attractions, culture, and culinary experiences. The campaign was highly successful, generating millions of views and significantly boosting interest in Singapore among Chinese travelers.

5. User Growth Strategies in the Chinese Market

Achieving sustainable user growth in China requires a deep understanding of local consumer behavior, preferences, and digital habits.

5.1. Mobile-First Approach

China is a mobile-first market, and ensuring that your marketing strategies are optimized for mobile devices is crucial for user growth.

  • WeChat Mini Programs: WeChat mini programs are lightweight apps within the WeChat ecosystem that offer various functionalities without the need for a separate app download. Tourism companies can use mini programs for booking, customer service, and promotional activities.

  • Mobile Payments Integration: Integrating mobile payment options like Alipay and WeChat Pay into your digital platforms is essential. These payment methods are widely used and trusted by Chinese consumers, and offering them can significantly enhance the user experience.

Case Study: TripAdvisor

TripAdvisor has effectively adopted a mobile-first approach in China by integrating with WeChat and Alipay. They developed a WeChat mini program that allows users to browse and book hotels, restaurants, and attractions directly within the app.

They also implemented Alipay as a payment option, making transactions seamless for Chinese users. This mobile-first strategy has helped TripAdvisor increase its user base and engagement in the Chinese market, proving the importance of adapting to local mobile preferences.

5.2. Data-Driven Personalization

Personalization is a critical factor in driving user growth in China. Chinese consumers expect personalized experiences tailored to their interests and preferences, making data-driven marketing essential.

  • Behavioral Targeting: By leveraging data from WeChat, Alipay, and other platforms, tourism companies can create highly targeted marketing campaigns. This involves analyzing user behavior, such as browsing history, purchase patterns, and social interactions, to deliver personalized recommendations and offers.

  • AI and Machine Learning: Implementing AI and machine learning algorithms can help tourism companies predict user behavior and automate the personalization process. This allows for real-time adjustments to marketing strategies, ensuring that users receive the most relevant content and offers.

Case Study: Hilton Hotels

Hilton Hotels has effectively used data-driven personalization to grow its user base in China. They employed AI-driven marketing automation tools to analyze user data and deliver personalized offers to their customers. For example, Hilton used behavioral data to recommend specific hotels and travel packages based on users’ past searches and bookings. This personalized approach significantly increased engagement and conversions, demonstrating the power of data-driven marketing in the Chinese market.

5.3. Community Building and Engagement

Building a loyal community of users is essential for sustained growth in China. Chinese consumers value community and social interaction, making it crucial for tourism companies to foster a sense of belonging among their users.

  • WeChat Groups and Communities: Creating and managing WeChat groups dedicated to specific interests or destinations can help tourism companies engage with their audience on a deeper level. These groups allow for direct communication, feedback collection, and the sharing of exclusive content and promotions.

  • Loyalty Programs: Implementing loyalty programs that reward repeat customers can enhance user retention and encourage word-of-mouth marketing. These programs can be integrated into WeChat or mobile apps, allowing users to easily track and redeem their rewards.

Case Study: Cathay Pacific Airways

Cathay Pacific has successfully built a strong community in China through its WeChat platform. They created exclusive WeChat groups for frequent flyers, offering members access to personalized travel advice, special promotions, and early access to sales. Additionally, Cathay Pacific’s loyalty program, which is integrated into their WeChat mini program, allows members to earn and redeem points seamlessly. This community-centric approach has helped Cathay Pacific cultivate a loyal customer base in China.

6. Overcoming Challenges in the Chinese Market

Despite the immense opportunities, international tourism companies face several challenges when entering the Chinese market. Understanding and addressing these challenges is crucial for success.

6.1. Regulatory Compliance

China’s regulatory environment is complex and constantly evolving. International companies must navigate a range of regulations, from data privacy laws to advertising standards.

  • Data Localization: China’s cybersecurity law requires that personal data collected from Chinese users be stored within the country. International companies need to ensure compliance with these regulations by hosting data on local servers.

  • Content Censorship: The Chinese government strictly controls online content, and companies must be cautious about the content they publish. Content that is politically sensitive, culturally inappropriate, or violates local norms can lead to fines, platform bans, or reputational damage.

Case Study: Airbnb

Airbnb faced significant challenges with regulatory compliance when entering the Chinese market. To comply with local laws, Airbnb agreed to store user data on local servers and share it with Chinese authorities upon request. They also implemented strict content moderation to ensure that listings and user reviews adhered to Chinese regulations. While these measures were necessary for market entry, they also required Airbnb to adapt its global practices to align with local standards.

6.2. Competition from Domestic Players

The Chinese market is highly competitive, with strong domestic players that have a deep understanding of local consumer behavior. International companies must find ways to differentiate themselves and compete effectively.

  • Local Partnerships: Partnering with local companies can provide international brands with valuable market insights and help them navigate the competitive landscape. These partnerships can also enhance credibility and trust among Chinese consumers.

  • Innovation and Differentiation: To stand out, international tourism companies must offer unique experiences or services that domestic competitors cannot easily replicate. This could involve leveraging global expertise, offering exclusive international travel packages, or introducing innovative technologies.

Case Study: KLM Royal Dutch Airlines

KLM Royal Dutch Airlines successfully differentiated itself in the Chinese market by focusing on innovative customer service. They were one of the first international airlines to offer customer support via WeChat, providing real-time assistance and personalized services to Chinese travelers. KLM also partnered with local travel agencies to offer exclusive European travel packages tailored to Chinese preferences. This combination of innovation and local collaboration helped KLM establish a strong presence in the competitive Chinese market.

6.3. Cultural Differences

Cultural differences can pose significant challenges for international tourism companies, particularly in areas such as communication, customer service, and marketing.

  • Cultural Sensitivity: Understanding and respecting Chinese cultural norms is crucial for building trust and rapport with consumers. This includes being aware of cultural taboos, preferences, and expectations in both marketing and customer interactions.

  • Localized Customer Service: Providing customer service that meets the expectations of Chinese consumers is essential. This may involve offering support in Mandarin, understanding local payment methods, and accommodating cultural preferences in service delivery.

Case Study: Disney Resorts

Disney Resorts encountered cultural challenges when opening Shanghai Disneyland. Initially, some of the park’s offerings did not resonate well with local visitors, who found them too Westernized. Disney quickly adapted by introducing more culturally relevant experiences, such as incorporating Chinese holidays and traditions into the park’s programming. They also trained staff to provide service that aligns with Chinese hospitality standards. These adjustments helped Disney overcome initial cultural barriers and achieve success in the Chinese market.

7. Measuring Success and Optimizing Strategies

To ensure the effectiveness of digital marketing, content marketing, advertising, and user growth strategies in China, it is essential to continuously measure success and optimize efforts.

7.1. Key Performance Indicators (KPIs)

Defining and tracking relevant KPIs is critical for evaluating the success of marketing campaigns in China. Common KPIs for tourism companies may include:

  • Conversion Rate: The percentage of users who complete a desired action, such as booking a trip or signing up for a newsletter.

  • Customer Acquisition Cost (CAC): The cost of acquiring a new customer, which should be optimized to ensure a profitable return on investment.

  • Engagement Rate: The level of interaction with content, including likes, shares, comments, and video views, which indicates how well the content resonates with the audience.

  • Return on Advertising Spend (ROAS): The revenue generated from advertising campaigns relative to the amount spent, which helps assess the effectiveness of ad placements and targeting.

Case Study: Accor Hotels

Accor Hotels uses a data-driven approach to measure the success of its digital marketing efforts in China. They track KPIs such as conversion rates, CAC, and ROAS to optimize their campaigns continuously. By analyzing these metrics, Accor can identify underperforming areas and make data-backed adjustments to their marketing strategies, ensuring they achieve their business objectives in the Chinese market.

7.2. A/B Testing and Continuous Optimization

A/B testing is a valuable method for optimizing digital marketing campaigns in China. By comparing different versions of ads, landing pages, or content, companies can identify what works best for their audience and make informed decisions about future strategies.

  • A/B Testing on WeChat: Testing different versions of WeChat ads or mini-program features can help determine which approach drives the highest engagement and conversions.

  • Content Optimization on Douyin: Testing various video formats, lengths, and content styles on Douyin can reveal what resonates most with viewers, allowing for continuous improvement of video marketing efforts.

Case Study: China Eastern Airlines

China Eastern Airlines uses A/B testing to optimize its WeChat marketing campaigns. They test different ad creatives, targeting options, and promotional offers to see which combinations yield the best results. Through continuous A/B testing, China Eastern has been able to refine its marketing strategies, resulting in higher engagement and conversion rates.

8. Conclusion: Strategic Recommendations for Success

Entering the Chinese market requires a well-planned and localized approach, especially in the competitive tourism industry. By understanding the unique digital landscape, leveraging local platforms, and adopting culturally relevant strategies, international tourism companies can effectively connect with Chinese consumers and drive business growth.

Here are some strategic recommendations for international tourism companies looking to succeed in China:

  • Invest in Localization: Ensure that all digital assets, from websites to marketing materials, are fully localized to meet the preferences and expectations of Chinese consumers. This includes language, cultural relevance, and mobile optimization.

  • Leverage Local Platforms: Focus on Chinese platforms like WeChat, Douyin, and Xiaohongshu for social media marketing, content distribution, and advertising. These platforms offer the best opportunities for reaching and engaging with your target audience in China.

  • Adopt a Data-Driven Approach: Use data analytics to inform your marketing strategies and personalize user experiences. Continuously monitor KPIs and optimize campaigns based on data-driven insights.

  • Foster Local Partnerships: Collaborate with local companies, influencers, and agencies to enhance your market presence and credibility. Local partnerships can provide valuable insights and help navigate the complexities of the Chinese market.

  • Embrace Innovation: Stay ahead of the competition by adopting innovative marketing techniques, such as AI-driven personalization, programmatic advertising, and immersive video content. Experiment with new technologies and platforms to differentiate your brand.

  • Understand and Respect Cultural Differences: Pay close attention to cultural nuances in communication, customer service, and marketing. Tailoring your approach to align with local customs and expectations is essential for building trust and loyalty among Chinese consumers.

  • Commit to Compliance: Stay informed about the latest regulatory requirements in China, particularly around data privacy and content standards. Ensure that your business operations, data storage, and marketing practices are fully compliant with Chinese laws to avoid legal issues and maintain a good reputation.

9. Future Trends in Digital Marketing for the Chinese Tourism Industry

As the digital landscape in China continues to evolve, it’s important for international tourism companies to stay ahead of emerging trends. By anticipating and adapting to these trends, companies can maintain a competitive edge in the Chinese market.

9.1. The Rise of Metaverse and Virtual Tourism

The concept of the metaverse is gaining traction in China, with major tech companies like Tencent and Alibaba investing heavily in virtual reality (VR) and augmented reality (AR) technologies. This trend presents new opportunities for tourism companies to create immersive travel experiences.

  • Virtual Tours: With VR, potential travelers can explore destinations virtually before booking their trips. This not only enhances the user experience but also helps in converting leads into bookings by providing a tangible preview of the travel experience.

  • Metaverse Partnerships: Partnering with metaverse platforms can allow tourism companies to create branded virtual spaces where users can interact with their offerings. For example, a hotel chain could create a virtual hotel in the metaverse where users can “stay” and explore, offering a taste of the actual experience.

Case Study: Marriott International

Marriott International has begun exploring the possibilities of virtual tourism by launching VR experiences for potential guests. Users can take virtual tours of Marriott properties, experiencing the rooms, amenities, and surroundings in an immersive way. This not only serves as a powerful marketing tool but also aligns with the growing trend of digital interactivity in China.

9.2. AI-Powered Customer Interactions

Artificial intelligence is playing an increasingly significant role in customer interactions in China. AI-powered chatbots, voice assistants, and recommendation engines are becoming commonplace, offering personalized and efficient service to customers.

  • Chatbots on WeChat: AI chatbots can handle customer inquiries 24/7, providing instant responses and assistance. They can also guide users through booking processes, recommend travel packages based on user preferences, and even upsell additional services.

  • Voice Assistants: With the rise of voice search in China, integrating voice assistants into customer service can enhance user experience. This is especially relevant for Chinese consumers who are becoming accustomed to interacting with digital services via voice commands.

Case Study: Ctrip

Ctrip, one of China’s leading online travel agencies, uses AI-powered chatbots to enhance customer service. These chatbots can answer questions, manage bookings, and offer personalized travel suggestions based on user data. The implementation of AI has significantly improved Ctrip’s customer service efficiency and user satisfaction.

9.3. Sustainable Tourism Marketing

As environmental concerns grow globally, sustainable tourism is becoming increasingly important to Chinese consumers, especially among younger generations. Tourism companies that emphasize sustainability in their marketing can attract environmentally conscious travelers.

  • Eco-Friendly Travel Packages: Promoting eco-friendly travel options, such as carbon-neutral flights or accommodations that use renewable energy, can resonate with Chinese consumers who are concerned about the environment.

  • Sustainability Content: Sharing content that highlights your brand’s commitment to sustainability, such as partnerships with conservation organizations or efforts to reduce the environmental impact of tourism, can enhance your brand image.

Case Study: TUI Group

TUI Group, a global leader in tourism, has embraced sustainable tourism as a key part of its strategy in China. They promote eco-friendly travel packages and have partnered with environmental organizations to offset carbon emissions from their tours. By emphasizing their commitment to sustainability, TUI has been able to attract a segment of Chinese consumers who prioritize responsible travel.

10. Conclusion: The Path Forward for International Tourism Companies in China

China’s tourism market offers immense potential for international companies, but it requires a deep understanding of the local digital landscape, consumer behavior, and cultural nuances. By adopting a localized approach to digital marketing, content marketing, advertising, and user growth, international tourism companies can successfully navigate the complexities of the Chinese market and achieve sustainable growth.

The key takeaways for success in China include:

  1. Embrace Localization: Tailor every aspect of your marketing strategy to align with Chinese preferences, from language and content to platform selection and payment methods.

  2. Leverage Data: Utilize the wealth of data available from Chinese platforms to drive personalization and optimize your marketing efforts in real time.

  3. Engage with Local Platforms: Focus on Chinese social media and e-commerce platforms to reach and engage with your target audience effectively.

  4. Build Trust Through Compliance: Ensure that your operations are fully compliant with Chinese regulations to avoid legal issues and build trust with consumers.

  5. Differentiate Through Innovation: Stay ahead of the competition by embracing new technologies and innovative marketing techniques that resonate with Chinese consumers.

  6. Respect Cultural Differences: Understand and respect the cultural differences that influence consumer behavior in China, and tailor your approach accordingly.

As the Chinese tourism market continues to evolve, international companies must remain agile and responsive to emerging trends and challenges. By continuously refining their strategies and staying informed about local developments, tourism companies can unlock the full potential of the Chinese market and establish a strong, enduring presence.

Keywords and SEO Considerations

To ensure that this article ranks well on both Google and Bing, it’s important to incorporate relevant keywords and follow SEO best practices. Here are some suggested keywords and phrases:

  • China digital marketing

  • Chinese tourism market

  • Content marketing in China

  • Advertising strategies in China

  • User growth in China

  • Localizing for Chinese consumers

  • WeChat marketing

  • Douyin advertising

  • Chinese social media platforms

  • Regulatory compliance in China

  • AI in Chinese tourism

  • Sustainable tourism in China

In addition to incorporating these keywords, it’s important to:

  • Use Headers and Subheaders: Organize the content with clear headers and subheaders to improve readability and SEO.

  • Optimize for Mobile: Ensure that the content is easily readable on mobile devices, as mobile usage is prevalent in China.

  • Include Internal and External Links: Link to relevant articles, case studies, and industry reports to provide additional value and context to readers while boosting SEO.

  • Use Alt Text for Images: If including images, use descriptive alt text to improve accessibility and SEO.

By following these guidelines, this article can effectively reach and engage decision-makers and marketing professionals in the international tourism industry who are looking to enter or expand in the Chinese market.

Categories
AdTech China Marketing Marketing

What are Advertisers’ Favorite Advertising Formats in China?

What are Advertisers’ Favorite Advertising Formats in China?

Blog

发布时间:2024-07-15   作者:

Due to the distinct software usage habits of Chinese consumers, email advertising, which garners significant attention in overseas markets, simply doesn’t work in China. The reason is straightforward: unless for work or travel bookings like flights, trains, or hotels, Chinese consumers rarely check their emails. Therefore, to advertise in China, it’s wise to observe how local and international advertisers, who have been in the Chinese market for years, place their ads. This article will introduce the most favored advertising formats among advertisers in the Chinese market, along with the corresponding media resource.

According to CNNIC statistics, as of June 2023, the scale of mobile phone netizens in China reached 1.076 billion people, with 99.8% of netizens using mobile phones to access the internet. The extremely high coverage rate of mobile terminals among netizens determines that mobile advertising is an inescapable topic in the battle for online attention. Currently, 96.7% of enterprises place ads on mobile platforms, 46.7% on PC platforms, and 13.3% on OTT platforms. It can be said that mobile advertising has become a battleground for advertisers to attract traffic and capture user attention.

Drilling down to ad types, according to the “2023 China Online Advertising Market Research” released by the research consulting institution iResearch platform, 90% of enterprises consider information stream ads as one of the main types of advertising, making it the most mainstream form of advertising. Search ads come in second with an 83.3% share, followed by banner ads (56.7%) and splash ads (50%).

Believing that the above-mentioned large-scale advertising types in the Chinese market are not unfamiliar to foreign advertisers, YOYI will introduce to you the characteristics of these popular advertising types and which media have these resources.

Feed Ads

Introduced by Facebook, feed ads are also very popular in Chinese social media. Feed ads are widely present in the user friend dynamics of social media, information media, or audio-visual media, in the form of pictures, graphics and text, videos, etc., and can be targeted through tags, according to one’s own needs, choose to increase exposure, UV, or app downloads, etc. The following are common feed advertising platforms in China:

Information platforms include: Toutiao, Qutoutiao, Sohu, Phoenix, Yidianzixun, Zhihu, etc.

Short video platforms include: Douyin, Kuaishou, Momo, etc.

Social media platforms: Tencent QQ, WeChat Moments, etc.

Search Engine Advertising

Search engine advertising refers to advertisers determining relevant keywords based on the content and features of their products or services, writing advertising content, and independently pricing and placing ads. When users search for keywords placed by advertisers in search engines, the corresponding ads will be displayed (when there are multiple users purchasing the same keywords, they will be displayed according to the bidding ranking principle), and the advertiser will be charged according to the bid for that keyword when the user clicks, with no charge for no clicks.

Search engines commonly used by Chinese users include: Baidu, Sogou, 360, Google.

The famous Chinese social media platform WeChat has also launched a built-in search feature called “Search” and its corresponding ads can also be considered a form of search advertising.

Banner Ads

Banner ads are rectangular advertising spaces that span across web pages, apps, H5, and mini-programs at a fixed position, usually at the top or bottom, and are often in the form of pure images, pure text, or a combination of images and text. When users click on these banners, they are typically linked to the web pages, apps, or form pages that the advertiser wants them to visit.

In China, banner ad spaces are commonly found on popular media and information websites such as Toutiao and NetEase News. In addition, some commonly used video apps such as Youku, iQiyi, LeTV, and Mango TV also set up banner ad resources. During major promotional periods in China, such as the 618 promotion, some apps will also set up special banner ad spaces, such as Zhihu.

Splash Ads

Splash ads refer to static images, animated pictures, or video-style advertising materials displayed on the startup page of an app, with a fixed display time, generally 5-15 seconds. After the display is completed, it automatically closes and enters the main page of the app. Splash ads can incorporate interactive elements, such as touching the screen for interaction, rotating the phone to adjust the display form, and strategically guiding to further enhance the user’s advertising browsing experience and increase the desire to interact. The characteristics of splash ads include the quality of the position, full-screen display, strong targeting, mandatory exposure, and huge traffic.

Video apps such as Youku, iQiyi, LeTV, and Mango TV will set up splash ads. In addition, UGC social apps like Zhihu; learning apps such as Youdao and Youdao Cloud Notes; photo editing apps like Meitu Xiuxiu; travel-related apps such as Gaode Map, Ctrip, and Tongcheng, all have splash ads.

Video Ad Spots

Video ad spots, also known as video interstitial ads, are a popular form of advertising among fast-moving consumer goods advertisers and advertisers accustomed to traditional media. They often appear before, after, or at fixed time points during online video playback.

Video apps such as Youku, Tencent, iQiyi, Wasu, Sohu, LeTV, Fengxing, and Baidu Video all have video ad spot positions.

Incentive Ads

Incentive video ads refer to a form of advertising that integrates video ads into the APP application, combining video ads with the content of the APP application. Users can receive rewards for watching video ads.

Incentive ads are commonly seen in gaming apps, where players can earn rewards such as coins or points after clicking on and watching video ads.

Interstitial Ads

Interstitial ads refer to ads that pop up in specific interfaces and at specific times within an app, available in both full-screen and pop-up formats. They can be closed directly or after a certain period of display, and the ad revenue is considerable. This form of advertising has a strong visual impact and supports both image and video materials.

For example, in video apps, when users pause video playback, interstitial ads will pop up in full-screen or half-screen formats to convey advertising information to users. Some gaming apps may choose to pop up when users briefly stop gaming operations, cleverly avoiding affecting the normal user experience.

If you wish to efficiently and swiftly captivate Chinese consumers, you need to cautiously experiment with different advertising formats and find an effective and cost-moderate advertising combination. YOYI suggests that you could start with the most popular advertising formats, of course, based on the premise of selecting suitable creatives and content for your brand.

Measure

Measure

Categories
AdTech Digital Marketing Marketing

How Do We Monitor Advertising in China?

How Do We Monitor Advertising in China?

Blog

发布时间:2024-07-29   作者:

In China, the rapid development of the internet industry has become a thing of the past. Faced with increasingly precious traffic, brands and advertisers need to put in more effort to “explore” and manage. Advertising monitoring naturally becomes an indispensable part of the advertising placement industry chain. Through advertising monitoring, advertisers can understand the effectiveness of their placements and further optimize strategies to gradually improve the return on investment. This article will explore how advertising monitoring is implemented in the Chinese market and what the current state of advertising monitoring is like.

What to monitor?

In China, advertisers also focus on the exposure, clicks, and in-app interaction effects of advertisements.

Exposure Monitoring: Also known as “impression monitoring,” it is usually the channel vendors who pass the data back to the advertisers.

Click Monitoring: Monitoring the number of clicks, which can be collected by the advertisers themselves or passed back by the channel vendors through data transmission.

In-App Monitoring: Refers to the monitoring of behaviors/events within the APP, such as basic PV, UV, APP activation/registration/login, etc., and user retention on the next day, 7 days, 30 days, pay rate, ARPU value, etc. These data are generally collected through the integration of third-party monitoring companies’ SDKs within the app, and the interfaces provided by different apps will vary.

Advertising Monitoring Process

To monitor the effectiveness of advertisements, advertisers fill in the corresponding monitoring address when creating the smallest unit of an advertisement, which is the creative. The monitoring URL generally includes the following macros: creative ID or advertisement ID identifier, user device identifier, IP, UA, operating system, etc., and special ones may include CLICKID, CALLBACK.

The entire monitoring process can be roughly divided into three steps:

  1. Advertisers/ad agencies place advertisements with media outlets. When users browse and click on the advertisements, the media will report the data to the advertiser or a third-party advertising monitoring platform. Common third-party platforms include: Umeng, adMaster, and Miaozhen.

  2. After users click on the advertisement, they enter the landing page and participate in the advertising activities, such as downloading and launching the APP. After completing a series of operations, the APP uploads the user data to the advertising monitoring platform through the corresponding interface. Of course, other interactive media such as websites and H5 can also monitor the interaction data from the source of the advertisement through tracking codes and embedded points.

  3. After attribution through certain methods, the user’s relevant data will be associated with the channel merchant and ultimately fed back to the advertiser/ad agency.

Data Reporting Methods for Advertising Monitoring: SD& APIK 

Advertising data monitoring in China is mainly implemented through SDK and API methods. The technical principles of the two are the same, both collecting user information and transmitting it back to the monitoring platform’s server for comparison. For example, when a user clicks on an advertisement link with tracking parameters, the monitoring platform collects the user’s IP, operating system version, device model, and other information through the link and stores it.

If a user clicks on an advertisement and is redirected to the App Store to download and activate the APP online, the APP will also collect all the user information stored by the monitoring platform.

Then, by matching the information collected when clicking on the link with the information collected after downloading and activating, subsequent conversion and other indicators can be monitored.

The SDK method is simple, easy to use, and powerful. Media outlets integrate SDKs into their Apps, and after completing certain development work, they can meet the vast majority of the needs of third parties and advertisers, with high accuracy and real-time performance.

The API method is flexible, versatile, and applicable to both Apps and mobile web pages. However, it requires media outlets to undertake some development work in accordance with API monitoring standards. API monitoring is divided into two types: C2S (Client to Server) API and S2S (Server to Server) API.

C2S, or Client to Server, refers to the terminal issuing a request instruction to the order placement proxy server. After the terminal receives and completes the instruction, it sends the completed instruction to the third-party monitoring proxy server, which conducts accurate traffic monitoring through mutual counting. Under the C2S model, user actions are directly reported to the third-party monitoring platform’s server, ensuring the timeliness and accuracy of the data. Renowned brand advertisers such as AdMaster and Nielsen often prefer this method to ensure seamless traffic authenticity verification.

S2S, or Server to Server, refers to the terminal issuing a request instruction to the order placement proxy server and then sending the completed instruction back to the order placement proxy server, which in turn sends the data to the third-party monitoring proxy server. This design may affect the timeliness of monitoring data while protecting user privacy, as it requires additional steps. Media outlets sometimes opt for S2S as an alternative strategy due to concerns over data security and may not support C2S monitoring.

C2S is more accurate and can reduce media cheating, commonly used by brand advertisers, but C2S requires client releases for each monitoring, making the implementation more complex.

Click Monitoring Methods: Synchronous Monitoring & Asynchronous Monitoring

Synchronous monitoring integrates the monitoring code with the landing page link. When a user clicks on an advertisement, they first visit the monitoring link, jump to the monitoring company’s server, and then jump to the landing page. Synchronous monitoring ensures the immediacy of the monitoring but may affect the user experience. In addition, synchronous monitoring does not support the transmission of parameters such as IDFA.

Asynchronous monitoring, on the other hand, directly redirects users to the landing page after clicking on the advertisement, with the media server sending a monitoring request to the monitoring company’s server. The asynchronous mode ensures a good user experience, but data transmission may be delayed. Moreover, since the request is sent by the server, the visits collected by the monitoring company all come from the same IP segment. If the client is targeting a specific city, determining the region solely based on the IP can lead to significant geographical discrepancies.

Current State of Advertising Monitoring

The mainstream third-party advertising media monitoring tools in China are TrackMaster introduced by AdMaster and AdMonitor introduced by Miaozhen. However, some dominant media outlets refuse third-party monitoring:

  1. The first kind is top-tier vertical media, mainly out of concern for protecting their own data, fearing that clients obtaining the data will affect the media’s valuation and traffic value.

  2. The second kind is dominant internet platforms, which often provide their own developed monitoring tools to clients.

Brands and advertisers must monitor advertising to better understand the effects, prevent data fraud, and continuously optimize the media mix, timing, geography, and creativity using the data obtained. The choice of monitoring mode depends on factors such as the brand’s demand for traffic authenticity, user privacy protection, and system compatibility between both parties. As the market evolves, China’s advertising monitoring methods may continue to evolve to adapt to the ever-changing advertising environment.

Measure

Measure

Categories
AdTech China Marketing Marketing

Understanding the Unique Advertising Formats in China to Avoid Ineffective Advertising

In the dynamic landscape of digital advertising, China’s advertising ecosystem has developed unique characteristics that set it apart from the global market. This article delves into specific advertising formats that are not commonly seen abroad but have gained significant attention in China. Furthermore, we analyze popular advertising strategies that have made a splash internationally but remain largely unknown in the Chinese market. By examining these differences, this article will help brands to better understand which advertising formats in the Chinese advertising market will be more conducive to business growth.

 

Elevator Advertising

China is one of the most populous countries in the world, with a high urban population density, especially in residential communities and commercial office buildings. Elevators, as necessary facilities in high-rise buildings, provide a high-frequency exposure opportunity for advertising as a large number of people pass through them every day.

The widespread application of digital advertising screens makes elevator advertising more dynamic and colorful, and even achieves precise push and interactivity, enhancing the attractiveness of advertising. Compared with traditional television, radio, or large outdoor advertising, elevator advertising has a relatively low cost and is more flexible in placement, which can be selectively placed based on specific attributes of the target audience. In addition, the space inside the elevator is relatively closed, and there are fewer interference factors in the display of advertisements. Passengers often have nothing to do when waiting for or riding in the elevator, which increases the attention and memory of the advertisement.

Advertisers can achieve precise placement after understanding the characteristics of the residents or office workers of the target building, including age, gender, occupation, and other information, and combine creative content with memorable points, using multimedia forms such as video and sound to improve the expressiveness and interactivity of elevator advertising. By using QR codes, NFC, and other technologies, online and offline connections are realized to guide the audience to further interact.

Splash Screen Advertising

Splash screen advertising is mainly used to display previously cached advertising content (pictures, animations, videos) or re-requested advertising when an APP is opened. While displaying the advertising content, some preparatory operations of the application can also be done. The implementation process is not complicated and is more commonly used in mobile advertising in China.

Most foreign APPs are simple and direct. Users do not like to see an advertisement that is unrelated to the software after opening the APP, such as YouTube, Facebook, etc., which are all directly a logo screen. However, some domestic APPs are in a monopolistic position, and users have no choice. But too frequent advertisements will directly affect the user experience. If there is a splash screen advertisement that makes users wait for 3 to 5 seconds every time the application is launched, it will make people feel annoyed and may even uninstall the APP, so publishers need to reasonably set the number and interval of advertisements to balance revenue and user experience.

Some mobile apps in China with splash screen advertising include: CTV apps such as Mango and iQiyi; UGC social apps such as Zhihu; Knowledge apps such as Youdao and Youdao Cloud Notes; Photo editing apps such as Meitu Xiuxiu; Travel apps such as Gaode Map, Ctrip, and Tongcheng, etc.

Lock Screen Advertising

The implementation of lock screen advertising is relatively more complex, requiring a background service to listen to the system’s boot, unlock, lock screen, and other broadcasts to replace the system’s lock screen interface with advertising content. It also uses the notification bar, and desktop widgets as advertising spaces, but all require the user to apply for authorization to disturb the user. With the update of the Android system, the management of background resident tasks will only be more stringent. Compared with other forms of advertising, such as TV and outdoor advertising, lock screen advertising has a lower cost and is easy to measure the effect, so it is favored by advertisers.

Chinese users spend a long time on the mobile Internet every day on average, and frequent lock and unlock operations increase the exposure opportunities of lock screen advertising. Chinese users have a relatively high acceptance of lock screen advertising, especially when it can provide some instant information or small rewards.

Foreign Google Play has strict policy constraints, in addition to applications specifically developed for the lock screen function, other applications are not allowed to provide advertising or features that profit through the device’s lock screen. Therefore, lock screen advertising is not common abroad.

When advertisers place lock screen advertising, they need to pay attention to designing simple and attractive advertising content to ensure that users can quickly grab attention before unlocking. At the same time, avoid designing advertisements that are too cumbersome or interfere with normal use, and control the frequency of advertising display to avoid causing user dissatisfaction.

Email Advertising

This article will also examine some advertising phenomena that have caused a sensation on the international stage but have not yet had a significant impact in China. Among them, email advertising, which is a favorite of foreign advertisers, finds it difficult to win the market in China for the following reasons:

Photo by Hack Capital on Unsplash

The popularity of social media

In China, social media platforms such as WeChat, Weibo, QQ, Xiaohongshu, and others are very popular. People are more inclined to use these platforms for communication and to receive information, rather than email.

E-commerce Ecology

China’s e-commerce ecosystem has developed rapidly, and consumers are more accustomed to receiving promotional information directly through online shopping platforms, which usually appear in the form of app push notifications or text messages.

Advertising Regulations

China’s internet advertising regulations have strict stipulations for email advertising, requiring senders to comply with relevant laws and regulations, which increases the operational cost and compliance requirements of email advertising.

User Habits

Chinese users generally rely less on email, and many may not check their mailboxes frequently, resulting in relatively lower open and conversion rates for email advertising.

Mobile First

Most of China’s internet users spend their time on mobile devices, and the email client experience on mobile devices is usually not as good as on PC, which also reduces the frequency of users receiving advertising through email.

Therefore, for advertisers, from the perspective of interactive effects, SMS advertising and mobile advertising in China can perfectly replace email advertising.

Categories
AdTech Digital Marketing Marketing

AI in Advertising: Everything You Need to Know

Wondering how to get started with AI? Take our on-demand Piloting AI for Marketers Series.


Learn More

Artificial intelligence, including generative AI, is used in advertising today to do everything from generate ad creative and copy to optimize ad budgets and predict advertising campaign performance. You can even use AI to scale up ad creative almost instantaneously or spy on your competition’s ad strategy.

In fact, modern advertising runs on AI…

Almost every ad you see online relies on AI to reach your eyes and ears in real-time. Today’s leading ad platforms, like Google Ads and Meta Ads, use AI to sell, target, and place ads micro-second by micro-second across vast ad network that span millions of digital destinations, apps, and experiences.

That means AI literally dictates who sees your ads and how much you spend to reach audiences on just about every popular ad platform out there.

(For example, Meta’s AI uses ad frequency and relevancy to determine the price and display rate of your ads on Facebook and Instagram.)

So, AI literally determines if your ads succeed or fail.

This creates a huge challenge—and a big opportunity—for advertisers.

First, the challenge…

Today’s AI-powered ad platforms give you the ability to run thousands of ad variations to micro-segmented audiences at scale. But human ad professionals aren’t equipped to take advantage of these superpowers. 

We can’t keep up with all the data generated by these platforms or process it fast and well enough to move the needle in our campaigns. And we simply don’t have the resources and bandwidth to create thousands of ad variations on the fly to test each and every moment.

And it shows…

Instead of unlocking our true potential in digital advertising, we launch a handful of simple campaigns with some basic optimization. These campaigns usually underperform.

Now, here’s where the opportunity comes in:

You don’t have to try (and fail) to keep up with AI-powered ad platforms on your own. You can actually use AI to help you…keep up with AI.

Today, advertisers have access to powerful, off-the-shelf AI tools that can do things like: generate nearly unlimited creative assets, micro-target audiences, scale up campaigns and budgets, conduct thousands of tests, and even run campaigns autonomously. 

So, let’s take a look at how to actually understand and adopt these tools in your own advertising.

What Is AI for Advertising?

You don’t need to know everything about AI to use it in your advertising—you just need to know these basics.

The best definition of AI comes from Demis Hassabis, founder of AI company DeepMind, which was acquired by Google. He says:

AI is the “science of making machines smart.”

That means making machines that can do intellectual tasks that humans can do. Tasks like: read, write, and understand text; see and identify objects; move around obstacles; hear and understand language; and sense the external environment.

Machines are able to do all of these things thanks to AI.

That’s because AI allows machines to learn. Unlike traditional technology, AI can actually detect patterns in data, then learn to make predictions from those patterns. It can then learn from its outcomes to make better and better predictions over time.

Once trained by humans, AI can go learn and improve on its own. The more data you give an AI system, the better it can learn and improve.

Whether you know it or not, you use AI dozens or hundreds of times each day.

Gmail and Google Docs use AI to understand what you’re typing, then predict what you want to type next. Every time you (and millions of others) use this feature, you train the AI to get better and better at predictive text.

Self-driving cars use AI to detect obstacles and drive safely. Every mile they drive gives them more data to improve their driving abilities.

Siri and Alexa use AI to understand voice commands and predict what responses make the most sense. Every time you talk to them, they learn to improve the quality of their responses.

In fact, AI isn’t just one technology. It’s an umbrella term that encompasses a range of smart technologies like these that can learn and improve on their own. Some AI technologies you might hear about are: machine learning, computer vision, natural language generation (NLG), natural language processing (NLP), deep learning, neural networks, and speech recognition. There are dozens of others, too.

You don’t need to know every term to be successful with AI. You just need to understand that AI-powered technology has the revolutionary ability to learn and improve on its own.

The ability to learn and improve on its own is why AI gives you a huge competitive advantage in advertising.

Why Do You Need AI for Advertising?

AI is an absolute must if you want to win in the new landscape of modern programmatic advertising.

Thanks to the internet and programmatic advertising, we now have the ability to reach consumers across hundreds of digital platforms. We also have the ability to target them based on hundreds and thousands of demographic and behavioral data points. We can even test hundreds or thousands of different ads to see what they respond to best.

Unfortunately, humans aren’t good at managing any of this.

Make no mistake, we’re great at being strategic and creative. This served us well in the Mad Men days of advertising, when a smart idea and clever slogan meant your ad campaign would succeed. Today, we are still integral to strategizing and creating unforgettable ads.

But we’re not good at the rest of it. We can’t analyze all the data we now have quickly enough to take action to improve campaigns. We can’t manage hundreds or thousands of ad, targeting, and budget variations to get the best results. And we certainly can’t find new customer opportunities in a sea of data.

AI can do all of these things and more. That’s why forward-thinking companies are using AI to:

  • Allocate advertising budgets, both across channels and audiences

  • Adjust advertising budgets automatically to hit KPIs

  • Find new advertising audiences and conversion opportunities

  • Build richer audience profiles

  • Determine and hit campaign goals

  • Gain insight into competitors’ ad spend, creatives, and strategies

  • Create ad copy

  • Create visual ad creative

  • Hyper-personalize ad messages and images to individual consumers

  • Hyper-personalize ad targeting

  • Predict ad performance before launching campaigns

  • And much more

Top Use Cases for AI in Advertising

There are dozens of use cases for AI in advertising—here are some of the most powerful ones.

There are literally hundreds of use cases for AI in advertising. Here are a handful of the most valuable ones that forward-thinking players in the advertising industry are using today.

Buy and Place Programmatic and Digital Ads

Today’s advertising relies on programmatic to target and deliver ads in real-time across the internet. AI is critical to the infrastructure that underlies advertising products on many platforms, though you may not always see it. Modern programmatic platforms often use AI to manage real-time ad buying, selling, and ad placement.

In fact, all digital advertising exchanges and platforms use artificial intelligence to regulate the purchase and sale of advertising in real-time. That includes programmatic exchanges, third-party networks, and advertising on platforms like Facebook, Instagram, and Snapchat.

You won’t find these exchanges, services, and platforms revealing how their AI algorithms work anytime soon though. But that’s the point: Even behind the scenes, artificial intelligence dictates how your ad spend gets used, who sees your ads, and how effective your overall campaigns are. That means if you run paid advertising, you need to understand the terminology around artificial intelligence and ask the right questions about how the AI used by ad platforms may be affecting your spend.

A very basic example of this is:

Facebook advertising, specifically ad frequency and relevance score. These two numbers are key pieces of data that Facebook’s algorithms use-without human involvement-to dictate how much you pay and how your ads are displayed.

You might think showing your ad more frequently is good. But it’s not. As Social Media Examiner puts it:

Traditional advertising research has shown that optimal ad frequency is at least three exposures within a brand purchase cycle. Traditional advertising schools say that you need to “hit” your audience with the same ad as many times as possible. However, repeat exposure on Facebook might actually hurt your campaign.

That’s because Facebook’s algorithms take into account user feedback. If you show your ad too often, and it’s rated poorly by users, your relevance score may go down. “In most cases,” says Social Media Examiner, “the higher the frequency, the lower the relevance score.”

A high relevance score means your ad is more likely to be shown to a target audience than the other ads you’re competing with. That translates into better performance and lower costs.

In modern advertising, you need to try to understand the algorithm as much as you understand your audience.

Optimize Advertising Budget and Performance

Performance optimization is one of the key use cases for AI in advertising. Machine learning algorithms are used by commercially available solutions to analyze how your ads perform across specific platforms, then offer recommendations on how to improve performance.

In some cases, these platforms may use AI to intelligently automate actions that you know you should be taking based on best practices, saving you significant time. In other cases, they may highlight performance issues you didn’t even know you had.

In the most advanced cases, AI can automatically manage ad performance and spend optimization, making decisions entirely on its own about how best to reach your advertising KPIs and recommending a fully optimized budget.

In another case, there exists at least one platform that allocates ad dollars automatically across all channels and audiences, so human beings can focus on higher-value strategic tasks, rather than manual guesswork about what works and what doesn’t.

Your ad targeting matters just as much as, if not more than, your ad copy and creative.

Thanks to platforms like Facebook, LinkedIn, Amazon, and Google, you have a seriously robust set of consumer data with which to target audiences, both through desktop and mobile advertising. But manually doing so isn’t always efficient.

AI can help here. We know of at least a few AI systems that look at your past audiences and ad performance, weigh this against your KPIs and real-time performance data coming in, then identify new audiences likely to buy from you.

Create and Manage Ads for You

AI-powered systems exist that will actually partially or fully create ads for you, based on what works best for your goals. This functionality is already present in some of the social media ad platforms, which use some intelligent automation to suggest ads you should run based on the links you’re promoting.

AI tools today excel at generating all different types of marketing language, and that includes the short, punchy copywriting that often succeeds in digital advertising. These systems leverage natural language processing (NLP) and natural language generation (NLG), two AI-powered technologies, to write ad copy that performs as well or better than human-written copy—in a fraction of the time and at scale.

We often see brands have great success having their human copywriters work hand-in-hand with AI counterparts, with each refining the other’s copy and giving each other ideas. The result is something that’s better than human or machine ad copywriters can produce on their own.

Generate Ad Variations Automatically

Using AI, you can generate ad variations automatically. That means you can take a single ad, give it to an AI tool, and it will spin that ad off into a number of different variations. Those variations could include different ad sizes and formats to adhere to different platforms. Or, they may include different designs and creative based on all the various campaign ideas you and your team have come up with. 

No matter what variations you produce, one thing is constant:

You no longer need to do this type of work manually.

Generate Images and Videos for Ad Creative

AI is getting increasingly good at generating images and videos for your ads.

Popular image and video generation tools are wowing audiences online as people share stunningly creative, artistic, and photo-realistic results using off-the-shelf technology. In just a year or two, these tools have grown in sophistication by leaps and bounds. We’re quickly approaching a world where you no longer have to spend a huge amount of time, money, and energy creating breathtaking visuals that capture an audience’s attention.

Personalize Ads Based on What Motivates Consumers

With AI, you can actually highly personalize your advertisements based on what motivates consumers. AI solutions exist today that can understand the language and content that motivates different types of people, then automatically adjust your ad content to reflect those motivations.

For instance, User A may respond better to language that emphasizes discounts and value, while User B may respond better to language that gets them excited and joyful. AI can actually tell the difference, then tailor your generic advertising message in different ways to appeal to each of these users.

Predict the Effectiveness of Ads in Advance

AI’s predictive capabilities unlock a number of superpowers, including in advertising. Using AI trained on vast amounts of proprietary ad data, we can begin to predict how effective our ads will be before they even launch.

That’s because AI can extract signals from millions of successful campaigns, then apply these to new ones. In the past, we’d simply guess at what ad elements would appeal most to our target audience. Now, we have the ability to get far more predictive using AI.

Run Ad Creative and Messaging Tests at Scale

It’s likely you’ve run some type simple A/B test at some point in your advertising career. But with AI, we can do far more robust testing of ad creative and messaging—and we can do it at scale.

AI tools today allow us to test hundreds or thousands of ad copy and creative variations quickly and automatically. AI’s ability to handle data-intensive tasks at scale makes it a perfect complement to human advertisers who aren’t very good at this task.

The result?

AI can do testing at scale for us, then we can focus on using the insights from those tests to create better campaigns that resonate with more humans.

Spy on the Competition’s Ad Strategy

As an advertiser, you don’t operate in a vacuum. Even with a winning campaign, you still face stiff competition from the other advertisers trying to either reach your audience with unrelated offers or actively competing in your market. AI can give you a leg up when it comes to the competition.

AI tools exist today that allow you to essentially spy on your competitor’s ad strategy. These tools use AI to develop a full picture of which ads your competitors are running on which platforms, as well as how much they’re spending and what offers they’re promoting.

Analyzed in aggregate, this information can reveal exactly what your competitor is up to—and give you the insights you need to outmaneuver them.

Real-World Examples of AI in Advertising

AI advertising is reshaping how brands do business.

But AI’s potential in advertising isn’t just theoretical…

Forward-thinking brands are using the technology today to increase advertising productivity and performance.

Equipment Company Attracts Top Talent Using AI Advertising

HOLT CAT is a heavy equipment company that was interested in attracting talent across a specific line of business. Limited talent was delaying work for customers and slowing down new sales. HOLT CAT turned to AI to create an ad campaign that could attract talent quickly and effectively.

Using employee data and AI-powered ad platform AiAdvertising, HOLT CAT was able to personalize ad messages to appeal to top candidates for open positions. Using the tool, they were also able to get clarity on exact ROAS, and lower their cost per hire by 20%. Not to mention, the company hired 270 new people since the start of the campagin—and, on average, 40% of those hires report being influenced to join the company by the advertising.

One of World’s Largest Investment Firms Uses AI to Boost Ad Conversion Rates by 15%

Vanguard, one of the world’s largest investment firms ($7 trillion in assets under management), turned to AI language platform Persado to conduct highly personalized advertising.

The company’s Vanguard Institutional business faces a heavily regulated advertising environment, and was only able to run ads on LinkedIn. Due to regulations of what companies could and couldn’t say in ads, the financial services ad landscape lacked easy ways to stand out.

Using AI from Persado, Vanguard was able to hyper-personalize its ads and test them at scale to see exactly what approaches resonated with consumers—a level of personalization and testing impossible without AI. As a result, the company saw conversion rates go up by 15%.

Ecommerce Company Gets 3,000% Return on Ad Spend Using AI

In one high profile example we covered, an AI advertising system helped an ecommerce company achieve a 3,000% return on ad spend—while reducing costs.

Entrepreneur Naomi Simson, a host on Shark Tank Australia, owns a company called RedBalloon, which sells gifts and experiences online (think: an experience-focused Groupon). She was spending $45,000 per month on ad agencies alone to run digital advertising for the brand. She was paying over $50 to acquire a single customer at the time.

Desperation drove her to investigate every possibility. She found an AI tool for advertising called Albert. The tool uses sophisticated AI to analyze ad campaigns, then manage targeting, testing, and budgets.

The tool was able to do things humans couldn’t. In one day alone, it tested 6,500 variations of a Google text ad and learned from the experiment. Over time, the tool was so effective at learning from data to improve performance that it skyrocketed RedBalloon’s return on ad spend. At one time, the company was getting a whopping 3,000% return on ad spend. They also cut marketing costs by 25% thanks to improved efficiency.

Top AI Advertising Tools

Here are some of the top AI advertising tools to look into for smarter, scalable ad campaigns.

So, which AI tools do you actually use to get real-world results?

There are literally thousands of them to explore. Here are just a few AI advertising tools and solutions you can start testing in your own ad campaigns.

Persado

Persado uses hyper-personalized AI generated content in ads to boost conversion rates across LinkedIn ads, Facebook ads, and other types of advertising and content creation.

Thanks to applying machine learning to their vast proprietary database, Persado understands what language resonates most with different types of consumers. Their solution then automatically personalizes your standard marketing and ad copy to tailor it to the language that motivates each user most.

The result?

Highly personalized ads that create significant uplift in performance (and revenue), because you’re speaking to consumers in the language they prefer—their own.

Emotiva

What if you could use artificial intelligence to measure someone’s attention and response to ads—just by analyzing their facial expression?

Emotiva uses proprietary machine learning to accurately measure emotions and attention levels. That means you can use AI to determine which ads are most effective based on how people actually feel about them and how they actually pay attention to them. It’s like cracking a secret code that tells you precisely what works and what doesn’t.

Pathmatics

Pathmatics uses AI to bring transparency and insight to advertising.

The tool shows you exactly how your ads perform across channels and gives you competitive intelligence about how your competitors’ ads perform, fueling ideas for effective creative and placement.

Using the Pathmatics’ AI technology, you can literally see exactly what ads your competitors are running in real time and get a complete picture of their ad strategy.

Omneky

Omneky is an AI ad platform that generates personalized ad content at scale.

Using this generative AI tool, you can generate thousands of optimized ads quickly, then precisely target each one to different audiences. Omneky can even determine which creative resonates most, so you can improve your ad content moving forward. The tool works with platforms like LinkedIn, Reddit, TikTok, Youtube, Facebook, Snapchat, and Instagram.

Celtra

Celtra automatically uses AI to generate variations of your ad creative at scale.

Celtra will take a single piece of creative you’ve produced, then spin off countless variations for different platforms, formats, and styles. This makes it easy to literally generate thousands of assets automatically.

(Seriously, if you’re creating variations of ads manually, you shouldn’t be.)

OneScreen

OneScreen uses AI for out-of-home ad delivery, targeting, and measurement. The company’s machine learning algorithm automatically optimizes which content and ads get shown to audiences, taking the guesswork out of out-of-home advertising.

GumGum

GumGum uses computer vision technology to learn from images and videos across the web, then help you place ads in the exact spots consumers will see them.

AiAdvertising

AiAdvertising is an AI-powered ad agency that takes the guesswork out of getting ROI from your ads. The company uses proven tools and strategies to help you maximize both budget and performance across your ad campaigns.

In turn, marketers and advertisers get more predictable, scalable, and effective campaigns, thanks to the power of human experts combined with intelligent machines.

Measure

Measure

Exit mobile version