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ChatGPT will show product carousels while creating images for users. These ads appear on the screen during the generation process. They sit below the picture being made by the AI. The company calls this a new display ad format. Users in the United States are the first to see these changes. OpenAI plans to launch this test later this month. An initial group of advertisers will join the program soon.
This change happens inside the chat interface where users talk to the bot. The loading screen is no longer just a spinner or a progress bar. It now hosts commercial content alongside the creative work. This means users see ads while waiting for their image to finish. The ads are labeled clearly as advertising to avoid confusion. They do not mix with the actual output of the model.
The goal is to monetize the time users spend waiting. Waiting can be a long process when generating complex images. Advertisers want to reach people during these idle moments. This format fills the empty space that usually appears in the UI. It turns a passive wait into an active viewing experience for shoppers.
How the ads are shown
The new display ads appear below the image ChatGPT is generating, either as a carousel or a row of product images.
OpenAI is launching the test later this month with an initial group of advertisers.
The company calls this a new display ad format.
Users in the United States are the first to see these changes.
These carousels show products in use or experiences tied to them. The design focuses on visual appeal and immediate relevance. A carousel allows users to swipe through multiple items easily. This mimics the experience found on social media platforms like Instagram. Users can scroll horizontally to see more options without leaving the chat.
The separation between the ad and the generated image is strict. OpenAI keeps the two distinct areas clearly visible to each other. The AI output remains at the top of the screen. The advertising content sits in a dedicated zone below it. This layout prevents users from mistaking an ad for their own creation. It also ensures that the brand message does not get lost in the noise.
Advertisers can choose how many images appear in their carousel. They might select three, five, or ten products to display. The system handles the sorting and shuffling of these items automatically. This keeps the feed fresh and prevents users from seeing the same set twice. It adds an element of surprise to the browsing experience.
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Users must interact with the ads to engage with them fully. Clicking on a product link takes them to a landing page. This is where the actual sale or sign-up happens. The ad itself acts as a bridge between the chat and the store. It leverages the context of the image being generated above it. For example, if someone asks for a dog photo, they might see pet food ads.
The placement strategy relies on high engagement during idle time. People often stare at screens while waiting for results to load. This is a prime opportunity for attention capture. The ads are not intrusive pop-ups that block the view. They sit in a natural flow of the interface design. This makes them feel less like interruptions and more like suggestions.
Tools for advertisers
OpenAI is also expanding its measurement tools for its advertising platform.
Advertisers can send conversion data to ChatGPT Ads through Hightouch, Tealium, and LiveRamp.
Attribution providers like AppsFlyer, Adjust, and Branch are joining the mix.
Through Haus, Measured, and WorkMagic, OpenAI is testing geo-based experiments to gauge actual ad impact.
These tools help brands track how many people buy after seeing an ad. Conversion data tells the story of a customer's journey from click to purchase. Hightouch connects this data to CRM systems for deeper analysis. Tealium manages the flow of information across different digital properties. LiveRamp provides identity resolution to link users across devices.
AppsFlyer and Adjust are known for mobile attribution tracking. They measure how often a user installs an app after clicking an ad. Branch helps track in-app events like purchases or profile completions. These partners ensure that OpenAI knows which ads drive real value. Without them, the company would only see clicks, not sales.
OpenAI is testing geo-based experiments to understand regional performance better. Haus and Measured allow brands to run A/B tests in specific countries. WorkMagic helps visualize the data from these experiments quickly. This approach lets advertisers see what works in New York versus London. It avoids wasting money on campaigns that do not convert locally.
Brand safety is a major concern for companies running digital ads. The company is running pilot programs with DoubleVerify and Integral Ad Science. These partners evaluate the ad environment without accessing real user conversations. They scan the chat context to ensure it fits the brand's guidelines. This prevents ads from showing up next to sensitive or inappropriate topics.
Select advertisers can set negative keywords to keep their ads from showing up in unsuitable conversations.
For instance, a baby product company might block ads during discussions about violence.
This feature gives brands more control over where their message appears.
It protects the reputation of the brand from association with harmful content.
Advertisers must define these rules carefully before launching a campaign.
The measurement stack is designed to be comprehensive and accurate. No single tool can tell the whole story of an ad's impact. Combining several providers creates a robust picture of performance. This reduces the risk of missing key insights or misinterpreting data. It builds trust between the advertiser and the platform.
Background on ChatGPT ads
OpenAI has been running ads in ChatGPT since February.
The program is now active in more than 40 countries around the world.
It has reached an annualized revenue run rate of $1 billion from ads alone.
The company aims to hit $100 billion in ad revenue by 2030.
This massive revenue target shows how serious OpenAI is about monetization. The $1 billion figure proves the current model works at scale. It generates significant income without relying solely on subscriptions. This diversifies the company's financial structure and reduces risk. Investors and partners see this as a sign of long-term stability.
The ad program targets a massive global audience every week. OpenAI states that ChatGPT reaches 1.2 billion people weekly. This number includes users across all devices and regions. It dwarfs the reach of most traditional digital advertising channels. Advertisers can access a demographic that is highly engaged with AI. They do not have to compete for attention in crowded feeds.
Earlier this year, only about 5 percent of users were paying for a subscription.
This means most users are still free or using freemium tiers.
The ad network captures the majority of this non-paying traffic.
It monetizes the base layer before moving up to premium subscribers.
This strategy maximizes revenue from the largest possible user base.
The expansion into 40 countries shows a commitment to global growth. Localized ads allow brands to speak directly to regional cultures. A fashion brand in Brazil can show different products than one in Japan. This granularity increases the likelihood of conversion and relevance. It respects local preferences and shopping habits.
The revenue run rate is an annualized figure that projects future earnings. It is not a total lifetime value but a consistent yearly pace. Reaching $1 billion annually indicates a mature and sustainable business model. It suggests that the platform can handle high volumes of traffic efficiently. The infrastructure supports millions of ad impressions per day without breaking.
Subscription adoption remains low compared to the massive user base. This creates a huge opportunity for alternative monetization methods. Ads fill the gap left by fewer paying customers. They provide a steady stream of income even if subscriptions drop. This balance keeps the company financially healthy during economic shifts.
Why it matters
The business impact is clear as OpenAI expands its ad network globally.
Advertisers gain access to 1.2 billion weekly users across 40 countries.
OpenAI aims to hit $100 billion in ad revenue by 2030.
This new format fills the image generation loading screen with product carousels.
For engineers and managers, this signals a shift toward heavy monetization. The platform is no longer just a chatbot; it is an ad network. Teams must now consider how ads affect user experience and retention. Privacy teams will face new challenges regarding data collection and context scanning. Product teams may need to redesign interfaces to accommodate carousels smoothly.
The reach of 1.2 billion people weekly makes this a high-stakes environment. Missing a trend here could mean losing market share to competitors. Advertisers expect fast results and precise targeting from the platform. The ability to run geo-based experiments quickly is a key competitive advantage. Brands that adapt well will thrive in this new ecosystem.
Safety concerns remain a priority as the ad volume grows rapidly.
The company uses partners like DoubleVerify to evaluate the ad environment.
This prevents ads from appearing in unsuitable conversations without user consent.
Managers must ensure their safety policies align with these pilot programs.
Compliance teams need to review how negative keywords are enforced automatically.
The revenue target of $100 billion by 2030 sets a long-term horizon.
It requires consistent growth and innovation in ad formats over the next decade.
Engineers should look at how carousels perform compared to text banners.
Testing different layouts will reveal which format drives more clicks.
Data from these tests will inform future product decisions for years.
Users who see ads during image generation may feel annoyed or confused.
This friction could lead to lower engagement with the core chat feature.
Product managers must balance revenue goals with user satisfaction metrics.
Retention rates are a critical KPI that cannot be ignored easily.
A bad ad experience might drive users away from the platform entirely.
The integration of third-party tools like Hightouch and Tealium adds complexity.
Engineers need to understand how these external systems connect to OpenAI's backend.
API documentation and integration guides will be essential resources for teams.
Misconfigured data flows could lead to inaccurate attribution reports.
Regular audits of the measurement stack are necessary for accuracy.
What to do
Advertisers can participate in the test by setting up accounts with OpenAI Ads.
They should start by defining their target audience and conversion goals clearly.
Contacting sales teams at OpenAI will provide access to the initial advertiser list.
Participating early gives brands a chance to shape the testing parameters.
Providing feedback on the carousel format helps refine the user experience.
Engineers running models can monitor how ads load and render during generation.
Check if the carousels appear consistently across different devices and browsers.
Report any bugs where ads overlap with the generated image content.
OpenAI will likely release a changelog or status page for these updates.
Staying informed about the rollout schedule helps teams prepare their infrastructure.
Managers should review the brand safety features available to their organizations.
Ask how negative keywords are implemented and managed within the platform.
Ensure that your internal guidelines match the external pilot programs offered.
Consider running a small budget test to validate the ROI of this format.
Compare the cost per acquisition against other advertising channels you use today.
Teams working on measurement should explore the new attribution providers joining the mix.
AppsFlyer and Adjust are already established players in mobile tracking.
Integrating them with your existing analytics stack will require some technical work.
Consult documentation from Hightouch or Tealium for specific connection instructions.
Verify that conversion events are being sent correctly to OpenAI's servers.
The $1 billion revenue run rate suggests a stable and growing business model.
Investors and partners expect continued investment in ad infrastructure and tools.
Keep an eye on the roadmap for more advanced features like video ads.
Prepare your team for potential shifts in how AI content is monetized globally.
This change marks a significant evolution in the relationship between creators and advertisers.
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