借助Adjust解锁ChatGPT Ads推广活动营销监测

This article centers on Adjust's newly launched marketing measurement support solution for ChatGPT Ads, sharing practical insights and step-by-step guidance for marketers testing this new ad channel.

1. Since its launch, ChatGPT has grown into a top global traffic platform and officially launched its official ad inventory, ChatGPT Ads, opening up an entirely new user acquisition path for marketers. The core pain point for early advertisers testing this channel is the lack of accurate performance measurement.

2. To connect ChatGPT Ads measurement via Adjust, users first need to create a ChatGPT Ads account and obtain access to OpenAI Ad Manager, then complete a four-step configuration within Adjust: select the partner and bind your app, enter your API Key and Pixel ID, map conversion events, and apply a URL template.

3. After campaigns go live, Adjust delivers real-time conversion data, and also supports automatic data aggregation and automated bid and budget management. Interested parties can contact Adjust's China marketing team to get started.

This article outlines new marketing opportunities and actionable implementation plans for brands looking to expand into new user acquisition channels, with key takeaways as follows:

1. New incremental marketing opportunity: ChatGPT has become a top global traffic platform, and with the launch of ChatGPT Ads, brands can directly reach high-intent users on the platform, opening up an entirely new user acquisition channel for mobile apps and brand awareness campaigns. This is a prime opportunity for brands to capture early-stage traffic dividends.

2. Solving the core pain point of new channels: The biggest challenge of testing a new channel is performance measurement. After integrating ChatGPT Ads, Adjust enables brands to track multi-dimensional metrics including impressions, clicks and conversions, accurately attribute installs and conversions generated by promotions, unify attribution across all channels, and calculate campaign ROI clearly.

3. Added efficiency support: Adjust also provides brands with capabilities including automatic ad spend collection, rule-based bid and budget control, and creative upload, helping simplify campaign management, optimize performance, and control trial-and-error costs.

This article offers new opportunities, risk mitigation solutions and practical guidance for sellers looking to expand into incremental user acquisition channels, with key takeaways as follows:

1. New incremental market opportunity: ChatGPT Ads is a newly launched official ad channel still in its early growth stage, with relatively low traffic competition. It enables sellers to reach high-intent users on the platform, making it an incremental new track for user acquisition worth testing and布局ing early.

2. Risk mitigation solution: The biggest risk of a new channel is unmeasurable performance, which easily leads to wasted budget. Adjust's integration solution enables sellers to implement full-funnel measurement from impressions to post-install conversions, unify attribution across channels, and receive real-time conversion data, helping sellers optimize campaigns based on data and protect ROI.

3. Implementation guidance: Adjust has released a complete configuration workflow, and also supports automated campaign management. Sellers looking to test this channel can directly contact Adjust's China team for onboarding, with a relatively low barrier to entry.

This article provides new directions and insights for factories pursuing digital transformation and expanding online channels for their owned brands, with key takeaways as follows:

1. New customer acquisition opportunity for business: Large AI models have developed a mature advertising ecosystem. As a global leading large model platform, ChatGPT has launched an official advertising channel, which enables factories to directly reach end consumers or high-intent B-end clients, breaking through the limits of traditional offline distribution and legacy acquisition channels and opening up a new customer acquisition path.

2. Insights for digital transformation: The core difficulty for factories building online marketing and owned brand e-commerce is advertising performance measurement. Third-party professional measurement tools have now quickly adapted to emerging AI ad channels, so factories do not need to build complex measurement systems in-house to test this opportunity. They can leverage mature third-party solutions to lower transformation barriers and control trial-and-error costs.

3. Efficiency advantages: Adjust's solution supports automatic ad spend collection and bid and budget control, helping factories reduce labor input for marketing operations. It is well-suited for factories testing new channels with an asset-light model to validate market feedback.

This article shares the latest developments in the app marketing industry and actionable insights for all types of marketing service providers, with key content as follows:

1. New industry development trend: Large AI models have completed their transformation from tool products to traffic marketing platforms. The launch of ChatGPT Ads marks the accelerated commercialization of large model traffic, and AI advertising has become a new incremental track for the marketing industry. More large model providers are expected to follow suit and launch advertising businesses, creating considerable market potential.

2. Current core pain points for clients: The core pain point for advertisers testing ChatGPT Ads is the lack of mature performance measurement and attribution capabilities. They cannot accurately compare conversion efficiency between this channel and other channels, nor calculate clear campaign ROI, which hinders large-scale ad spend on the channel.

3. Reference for solution building: Leading third-party measurement provider Adjust has already completed rapid adaptation to this new channel, enabling full-funnel measurement, unified attribution, conversion forwarding and automated campaign management via API integration. This provides a clear reference direction for all types of marketing service providers looking to enter this new track and meet client demand.

This article provides strategic insights for the operation and development of all types of advertising and traffic platforms, with key takeaways as follows:

1. Core advertiser demand for emerging platforms: After emerging AI traffic platforms launch advertising businesses, the most core demand from advertisers is access to industry-standard performance measurement and attribution, which enables clear assessment of channel value and straightforward cross-channel performance comparison. This is the core factor influencing advertiser willingness to spend.

2. Reference for platform partnership direction: Emerging ad platforms do not need to build a complete in-house measurement and attribution system. By partnering with professional third-party measurement providers, they can quickly close capability gaps, meet core advertiser demands, lower the barrier for advertisers to test the channel, and improve the platform's appeal to advertisers. The partnership between Adjust and ChatGPT Ads is a典型 win-win model.

3. Insights for operation and management: Emerging ad platforms need to open up API interfaces to enable third-party service providers to connect for conversion forwarding, data collection, campaign management and other functions, and improve ecosystem capabilities. This is the only way to quickly attract advertisers to onboard and scale the platform's advertising business.

This article captures the latest developments in AI large model commercialization and the digital marketing industry, providing new research materials and directions for researchers, with key insights as follows:

1. New industry development trends: As the world's leading general-purpose large model, ChatGPT has achieved advertising commercialization less than one year after its launch, with the official rollout of its ad inventory ChatGPT Ads. This marks that the traffic monetization business model for large model platforms has been formally validated, and large models have evolved from technical products into commercially viable traffic-entry platforms. This is a key milestone in AI industry development.

2. New industrial division of labor and business model: The development of the large model advertising ecosystem has spawned a new industrial division of labor: large model platforms provide traffic, third-party measurement providers deliver technical services such as cross-channel unified attribution and full-funnel measurement, and advertisers pay to acquire users. This forms a clear collaborative model, representing a new business model形态 in the digital marketing space.

3. New research directions: The conversion efficiency, user behavior characteristics and ROI performance of emerging AI ad channels, as well as the role positioning of third-party measurement providers in this new ecosystem, have all become new research topics in the fields of digital marketing and AI commercialization.