After gaining access to OpenAI Ads Manager Beta, the next step is to understand the platform’s key sections. Even if the advertising account has already been created, account information, user permissions, billing, campaign structure, conversion tracking, and reporting areas must be reviewed to ensure campaigns can operate effectively.
At this stage, the objective is not to launch a campaign immediately, but to understand the platform correctly and establish a solid foundation for advertising operations.
OpenAI Ads Manager Beta should not be viewed as an exact replica of Google Ads or Meta Ads. Although some principles are similar, the ChatGPT Ads experience is shaped around user intent and conversational context, so platform settings should be evaluated together with this strategy.
What is the purpose of the OpenAI Ads Manager Beta platform?
OpenAI Ads Manager Beta is the advertising management platform where ChatGPT Ads are created, managed, and monitored.
The platform is generally used to:
- Create advertising campaigns
- Manage campaigns, ad groups, and ads
- Monitor advertising performance
- Control spend and budgets
- Edit account information
- Manage billing and payment settings
- Grant access to team members
- Review and export reports
Since OpenAI Ads Manager Beta is still an evolving product, some areas of the platform may change over time. When creating campaigns, advertisers should therefore follow not only the current interface, but also official documentation and the latest product workflows.
Strategic recommendation: When opening the platform for the first time, do not immediately begin creating campaigns. First review account settings, billing, user access, and measurement preparation. Advertising performance often begins with these foundational settings before the campaign screen itself.
The core structure: Campaign, Ad Group, and Ad
The advertising structure in OpenAI Ads Manager Beta consists of three main levels:
- Campaign
- Ad Group
- Ad
This structure may feel familiar to performance marketing teams. However, the role of each level should be clearly separated.
Campaign level
The campaign is the highest level of the advertising strategy. Objectives, budget, date range, and the overall campaign structure are generally planned at this level.
For example, an e-commerce brand could divide campaigns into:
- New-season products
- Best-selling product groups
- High-margin products
- Specific category campaigns
- Brand awareness campaigns
If the campaign level is structured too broadly or inconsistently, reporting becomes more difficult. If it is too general, identifying which product or message is generating performance may also become challenging.
Ad Group level
The Ad Group is a more specific division within a campaign. Targeting, contextual signals, product groups, or messaging differences can be managed at this level.
For example, an “Outdoor Shoes” campaign could include the following ad groups:
- Trekking shoes
- Everyday outdoor shoes
- Waterproof models
- Discounted outdoor products
This structure makes both budget control and performance analysis easier.
Ad level
The Ad level represents the part of the advertisement that users see. Fields such as the headline, description, image, and destination URL are managed at this level.
The key consideration at the Ad level is that the advertising message should align with both the user’s needs and the destination page.
Instead of generic messages such as “The best products are here,” brands should use clearer statements that support the user’s decision-making process.
Why should account information be reviewed first?
After gaining platform access, account information should be one of the first areas reviewed.
This section generally includes:
- Account name
- Brand name
- Logo
- Website
- Country
- Currency
- Time zone
- Business information
The brand name and logo should be checked carefully because they may appear in advertising placements. When users see an advertisement, the brand identity should appear clear, trustworthy, and consistent.
Country, currency, and time zone settings are important for reporting and billing. An incorrect time zone can create problems when comparing campaign performance with GA4 or internal reports.
Strategic recommendation: Compare the time zone in your OpenAI Ads Manager account with the time zones used in GA4, CRM, and internal reporting systems. Different time zones may produce misleading results, especially in daily spend and conversion reports.
How should billing and payment settings be reviewed?
Even if the advertising account is active, campaigns may not run until billing and payment settings are complete. The billing section should therefore be reviewed before launching a campaign.
Key areas to check include:
- Has a billing profile been created?
- Is the billing information correct?
- Is the invoice delivery email correct?
- Has a payment method been added?
- Are the card details valid?
- Is the currency correct?
- Does the finance team require access?
These areas may appear technical, but they are critical to advertising operations. Payment-related interruptions after a campaign goes live can disrupt both the learning process and performance analysis.
How should user access and permissions be planned?
Team members can be invited to OpenAI Ads Manager Beta, but not every user needs the same permission level.
A role-based access structure is generally more appropriate for brand, agency, finance, and technical teams.
An example access structure could be:
- Brand manager: Account management and overall control
- Performance marketing team: Campaign creation and optimization
- Agency team: Campaign management and reporting
- Finance team: Billing and spend monitoring
- Technical team: Pixel, Conversions API, and measurement checks
This structure improves security and reduces operational complexity.
Strategic recommendation: If you work with agencies, define your access policy from the beginning. When changing agencies, removing access for former users is an important step that should not be overlooked.
What should be reviewed on the Campaign screen?
The Campaigns section lists campaigns and allows performance to be monitored at the highest level. Campaign name, status, spend, impressions, clicks, and other performance metrics can be reviewed on this screen.
It is not enough to check only whether a campaign is active or paused. The following questions should also be considered:
- Is the campaign actually delivering?
- Is spend progressing at the expected pace?
- Are impressions high but clicks low?
- Are there clicks but no conversions?
- Is the budget being spent too quickly?
- Is the campaign name descriptive enough for reporting?
A clear campaign naming convention can significantly simplify platform management.
Example naming structure:
TR | Product Feed | Women’s Shoes | Prospecting | July 2026
This structure is not mandatory. However, a naming standard that includes country, category, objective, period, and campaign type provides a major advantage in reporting.
How should the Ad Group screen be analyzed?
The Ad Group level is often one of the most critical layers in performance analysis. Even if overall campaign performance appears strong, some ad groups may be using the budget inefficiently.
The following checks can be made on the Ad Group screen:
- Which ad group receives the most impressions?
- Which ad group generates the highest CTR?
- Which ad group produces more expensive clicks?
- Which ad group is not generating conversions?
- Which context or product group performs better?
If the Ad Group structure is too broad, performance analysis becomes difficult. If it is too fragmented, data accumulation may take longer.
Strategic recommendation: Avoid dividing ad groups into overly granular segments in the first campaigns. Use a balanced structure that collects sufficient data for learning while still making performance differences understandable.
Which fields should be reviewed on the Ad screen?
The Ad level represents the actual advertising experience shown to the user. It is therefore not enough to check only whether an ad is active.
The following areas should be reviewed:
- Is the headline clear?
- Does the description avoid repeating the headline?
- Is the value proposition clear?
- Does the image support the advertising message?
- Does the landing page lead to the correct destination?
- Have UTM parameters been added?
- Does the ad contain any policy-violating language?
- Is the ad status “serving” or another eligible status?
OpenAI’s advertising copy recommendations emphasize clarity, honesty, relevant landing pages, and user experience. Brands should therefore avoid exaggerated claims, unclear promotional promises, and messages that do not align with the destination page.
How should reporting areas be used?
OpenAI Ads Manager Beta allows advertisers to monitor core performance metrics directly within the platform. These may include impressions, clicks, spend, CTR, average CPC, average CPM, and conversions when conversion measurement is configured.
These metrics should be interpreted together rather than separately.
For example:
- If impressions are high but CTR is low, the advertising message or targeting may not be strong enough.
- If CTR is strong but conversions are low, the landing page, product relevance, or price competitiveness should be reviewed.
- If CPC is high, targeting, bidding, or ad group structure may need to be reconsidered.
- If no conversions appear, the technical measurement setup should be checked.
- If spend increases quickly without conversions, data quality should be reviewed before pausing the campaign too early.
Reporting should not rely only on Ads Manager data. GA4, CRM, the e-commerce platform, and product performance data should also be evaluated together.
Early preparation for measurement is especially important for new channels such as OpenAI Ads. To better understand how product data and performance data can be evaluated together in AI-powered shopping experiences, read AI-Powered Smart Product Segmentation.
Why are CSV exports and offline analysis important?
The reporting screen in Ads Manager Beta may be sufficient for quick checks. However, CSV exports are necessary for more detailed analysis.
CSV exports can be used to:
- Compare campaign performance with GA4 data
- Review daily spend and click trends
- Identify inefficient areas at the Ad Group level
- Compare advertising variations
- Analyze the relationship between conversion data and spend
- Transfer data into internal reports
Developing a habit of exporting CSV data is particularly important during the first 30 days of learning on a new advertising channel. Trends that may not be immediately visible in the platform can become clearer through external analysis.
Strategic recommendation: During the first campaigns, review data daily rather than only weekly whenever possible. However, avoid making rushed decisions based on daily data. Early signals should be monitored, but frequent changes to budgets, creatives, or targeting before sufficient data has accumulated may disrupt learning.
Common issues that may occur in the platform
Advertisers may encounter several common issues while managing campaigns in OpenAI Ads Manager Beta.
The most common areas to review are:
The campaign is not delivering
Check the following:
- Has account verification been completed?
- Has a billing profile been created?
- Is the payment method valid?
- Is the campaign budget sufficient?
- Are the campaign start and end dates correct?
- Has the ad been approved, or is it still under review?
The ad was rejected
Check the following:
- Does the advertising copy comply with policies?
- Is the landing page consistent with the advertising message?
- Is the image appropriate?
- Does the ad contain a misleading claim?
- Is the destination page accessible?
There are impressions, but clicks are low
Check the following:
- Is the headline clear enough?
- Does the advertising message address the user’s needs?
- Does the image support the message?
- Is the Ad Group structure too broad?
- Are there enough ad variations?
There are clicks, but no conversions
Check the following:
- Does the landing page lead to the correct page?
- Are price and availability details current?
- Does the page provide enough product information?
- Does the page load quickly on mobile?
- Is measurement working correctly?
How should e-commerce brands use the platform?
E-commerce brands should not view OpenAI Ads Manager Beta only as a media management platform. Campaign data should be evaluated together with product data.
For example, if a product group receives many clicks but does not generate conversions, the problem may not be the advertising copy. The price may not be competitive, availability may be limited, variants may be incomplete, or the product description may not be persuasive enough.
E-commerce teams should therefore analyze platform data together with:
- Product feed quality
- Price and availability freshness
- Category structure
- Product images
- Variant information
- Campaign and promotional information
- GA4 product performance
- Add-to-cart and purchase rates
To explore the role of product feeds in advertising performance in more detail, read What Is Product Feed Optimization?.
Where does Optifeed fit into this process?
Optifeed is an AI-powered product feed optimization platform that helps e-commerce brands prepare their product data for advertising platforms and AI shopping experiences.
Monitoring campaign performance in OpenAI Ads Manager is important, but many factors that influence performance begin outside the platform. Product titles, descriptions, prices, availability, categories, images, variants, and promotional information are all fundamental parts of the process.
Optifeed can support brands by:
- Cleaning and organizing product feed data
- Improving incomplete or weak product fields
- Making product titles and descriptions easier to understand
- Managing price, availability, and variant data according to channel requirements
- Enriching product attributes with AI Enrich
- Creating product segments based on performance data
- Preparing multichannel feeds for Google, Meta, TikTok, and AI platforms
This approach supports campaign management in the OpenAI advertising platform with a stronger product data infrastructure.
Poor performance in the platform is not always a media buying problem. In some cases, the actual issue is that the product data, landing page, or measurement infrastructure is not aligned with the campaign objective.
OpenAI Ads Manager provides a central environment for campaign creation and performance monitoring. However, to get the most value from the platform, account settings, user permissions, billing, campaign structure, advertising messages, measurement, and product data should be considered together. For e-commerce brands in particular, combining platform management with product feed quality and AI shopping preparation can create a stronger advertising operation.
