One of the most critical steps when getting started with OpenAI Ads is building the campaign structure correctly. Campaign structure does more than determine where ads are placed; it directly affects budget management, reporting, testing plans, and optimization.
In OpenAI Ads Manager Beta, the advertising structure consists of three main levels:
- Campaign
- Ad Group
- Ad
This structure may be familiar to performance marketers who already use Google Ads and Meta Ads. However, because user intent in ChatGPT Ads is more conversational, thinking only in terms of keywords or traditional audience targeting may not be sufficient.
How does campaign structure work in OpenAI Ads Manager?
In OpenAI Ads Manager Beta, the Campaign, Ad Group, and Ad layers form a complementary structure.
The Campaign is the top level where you define the overall objective, budget, schedule, and country targeting.
The Ad Group represents a theme, product group, intent area, or use case within the campaign. Context hints become particularly important at this level.
The Ad is the advertising unit users see within ChatGPT. Fields such as the headline, description, image, and landing page are managed at this level.
In this structure, the Campaign carries the overall objective and budget, while the Ad Group represents a more specific user need. The Ad presents the creative message that responds to that need.
Strategic recommendation: When building your campaign structure, think about user intent before thinking about the advertising platform. What need might a user describe to ChatGPT? Designing the Campaign and Ad Group structure around the answer to this question can produce a more effective setup.
Campaign level: Objective, budget, and schedule
Campaign is the highest level of the OpenAI Ads structure. This is where the campaign’s overall purpose and operational boundaries are defined.
At the Campaign level, the following areas should be planned:
- Campaign name
- Campaign type
- Campaign objective
- Budget
- Start and end dates
The first decision when creating a campaign is which business objective the campaign will support.
For example:
- Will the campaign support a new product launch?
- Will it drive traffic to a specific category?
- Will it increase brand visibility?
- Will it promote discounted products?
- Will it test high-margin product groups?
Launching a campaign before clarifying this objective makes later reporting more difficult.
How should the campaign objective be selected?
In OpenAI Ads Manager Beta, the campaign objective may affect how ads are optimized and which pricing model is used.
In general, there are two main approaches:
Visibility-focused campaigns: More suitable for objectives such as brand awareness, product promotion, or introducing a new category.
Click-focused campaigns: More relevant when the objective is to direct users to a landing page, drive traffic to a product page, or begin the purchase journey.
E-commerce brands may initially be more aligned with click-focused or conversion-focused campaigns. However, visibility-focused campaigns can also be tested for new category launches, seasonal collections, or product groups with low awareness.
Strategic recommendation: Do not try to solve every objective within the first campaign. Instead of combining awareness, traffic, and conversion expectations in a single campaign, connect each campaign to one primary business objective.
How should the budget structure be planned?
Campaign budget is one of the most critical settings in OpenAI Ads Manager. When defining the budget, consider not only daily spending capacity but also the learning process.
The following questions can help when setting the first campaign budget:
- Is this a testing campaign or a scaling campaign?
- Which product or service group has the highest priority?
- What could the expected cost per click be?
- What is the estimated landing page conversion rate?
- How many days should the campaign collect data?
- Is the daily spend manageable from a reporting perspective?
A budget that is too low may prevent the campaign from collecting meaningful data. A budget that is too high may create unnecessary spending risk in a structure that has not yet been tested.
Beginning with a more controlled budget and increasing it based on early signals is generally a healthier approach.
Why is campaign naming important?
Campaign naming may appear to be a simple detail, but it becomes the foundation of reporting as the account scales.
A good campaign name may include:
- Country
- Language
- Category
- Campaign type
- Campaign objective
- Period
- Product group
Example:
TR | Product Feed | Women’s Dresses | Conversions | Summer 2026
This naming structure makes it much easier to monitor campaign performance in external reports or compare it with GA4 data.
Strategic recommendation: Establish a naming convention from the first campaign. Names such as “Test 1,” “New Campaign,” or “OpenAI Trial” may appear convenient in the short term, but they make long-term reporting more difficult.
Ad Group level: Theme, intent, and context hints
The Ad Group is where more specific campaign segments are created. In the ChatGPT Ads structure, Ad Groups should be viewed not only as groups of ads, but also as a way to organize user intent and context.
Different Ad Groups within a campaign can be divided according to:
- Product category
- Use case
- Target user need
- Price segment
- Season
- Promotion type
- Brand or collection
- Problem and solution area
For example, a sports equipment brand could create the following Ad Group structure:
- Home workout equipment
- Running accessories
- Yoga and Pilates products
- Sports products for beginners
This structure makes the advertising message clearer and performance easier to interpret.
What are context hints?
Context hints are an important field used at the Ad Group level in OpenAI Ads Manager Beta. They help describe the conversation themes, user needs, or contexts in which an Ad Group may be relevant.
Context hints should not be treated as traditional keyword targeting. The objective is not to match individual words, but to explain which conversation areas are relevant to the Ad Group.
For example, using only the following phrase for a brand selling running shoes may be too limited:
“running shoes”
Better context hint examples could include:
- “Users looking for lightweight running shoes for long-distance running”
- “Users seeking comfortable and supportive shoe recommendations for daily training”
- “Users looking for suitable sports shoe recommendations for beginner runners”
These statements explain more clearly when the product becomes relevant.
Strategic recommendation: When writing context hints, think about the problem users are trying to solve rather than only how they search for your product. In the ChatGPT experience, the language of need may be more powerful than traditional search terms.
Should the Ad Group structure be highly fragmented?
One of the most common mistakes in initial campaigns is dividing the Ad Group structure into too many segments. Creating a separate Ad Group for every product, category, or user intent may appear organized in theory. In practice, however, data may become overly fragmented and performance more difficult to interpret.
The opposite approach—placing all products in one Ad Group—can also cause problems. In this case, identifying which theme, product group, or message generates performance becomes difficult.
A healthier starting approach is to build Ad Groups according to the following principles:
- Each Ad Group should have one primary theme.
- Each Ad Group should contain similar user needs.
- Very different products should not be placed in the same Ad Group.
- Each Ad Group should be broad enough to collect sufficient data.
- Context hints should be consistent with the Ad Group theme.
In e-commerce, category data alone may not be sufficient for dividing products by performance. Grouping products according to sales, revenue, availability, and conversion data can create stronger campaign structures. To explore this approach in more detail, read AI-Powered Smart Product Segmentation.
Ad level: Advertising message and landing page
The Ad is the advertising unit users see within ChatGPT. At this level, the headline, description, image, and destination page become important.
The following fields should be prepared carefully:
- Ad headline
- Ad description
- Image
- Landing page URL
- UTM parameters
- Brand name and logo
- Advertising policy compliance
When writing advertising copy for ChatGPT Ads, benefit-focused, clear, and contextually relevant messages should be preferred over short, generic slogans.
Weak example:
“The best products are here.”
Better example:
“Discover lightweight and durable backpacks for everyday use.”
The second example explains more clearly what the product is, who it is suitable for, and which need it addresses.
How should ad variations be created?
Instead of relying on a single advertising message in OpenAI Ads, different messaging angles should be tested for the same product or service.
Different angles for a product could include:
- Price advantage
- Use case
- Material quality
- Fast delivery
- Customer reviews
- Seasonal need
- Gift alternative
- Technical feature
- Problem and solution
For example, a luggage brand could test the following advertising angles:
- “Discover lightweight cabin-size luggage.”
- “Durable large suitcases for long trips.”
- “Lightweight wheeled luggage with spacious interiors.”
These variations may help the advertisement appear more relevant in different conversation contexts.
Strategic recommendation: Do not create ad variations by changing only a few words. Each variation should address a different user need or decision criterion.
Why does landing page selection affect performance?
In OpenAI Ads, landing page selection is as important as the advertising message. When users click an advertisement, the promise in the ad should match the page they reach.
If an advertisement presents a specific product group, directing users to the homepage is usually not the best approach. A product page, category page, or dedicated collection page should be used instead.
A strong landing page should clearly present:
- Product or service description
- Price information
- Availability information
- Variant options
- Images
- Delivery and return information
- Reviews or trust signals
- A clear call-to-action button
Missing information on product pages can directly affect advertising performance, especially for e-commerce brands. After describing a need inside ChatGPT, users should find the same level of clarity on the landing page.
To explore the role of trust signals in AI shopping experiences in more detail, read Trust Signals in AI Shopping.
Guided campaign creation or bulk upload?
Two main approaches can be considered when creating campaigns in OpenAI Ads Manager Beta:
Guided campaign creation is the step-by-step campaign creation process within the platform. It may be a more controlled and understandable method for initial campaigns.
Bulk upload allows campaign structures to be uploaded at scale using a CSV template. It is a more scalable method when creating many campaigns, Ad Groups, or ad variations.
Guided campaign creation may be more suitable for brands at the beginning stage. It makes it easier to learn how the platform works, understand the fields, and build the first campaign structure in a controlled way.
Brands with large catalogs, agencies, or teams creating many ad variations may evaluate bulk upload at a later stage.
Strategic recommendation: Create your first campaign manually in the platform and validate the structure. Then scale the same logic using bulk upload. Starting with bulk upload from day one can amplify naming errors or missing field problems.
Example structure for the first campaign
An e-commerce brand could structure its first OpenAI Ads campaign as follows:
Campaign:
TR | Product Feed | Outdoor Products | Conversion | Summer 2026
Ad Group 1:
Lightweight Travel Backpacks
Context hints:
- Users looking for lightweight backpacks for travel
- Users seeking durable backpacks with spacious capacity
- Users comparing backpacks suitable for cabin luggage
Ad examples:
- “Lightweight Travel Backpacks”
- “Discover Durable Backpacks”
- “Cabin-Friendly Backpack Models”
Landing page:
Travel backpack category page or the relevant product collection
Although this structure appears simple, it provides a strong starting point. The campaign objective is clear, the Ad Group theme is well defined, the context hints are close to user needs, and the advertising message is consistent with the product group.
How should early post-launch signals be interpreted?
Aggressive optimization immediately after launch may not be the right approach. The campaign should first be allowed to generate basic signals.
The following questions can be reviewed during the first few days:
- Has the campaign started receiving impressions?
- Are clicks being generated?
- Is CTR at the expected level?
- Is spend increasing too quickly?
- Are clicks reaching the correct landing page?
- Can the traffic be identified separately in GA4?
- Is conversion tracking working?
- Are certain Ad Groups clearly outperforming others?
- Are differences emerging between ad variations?
Reading early signals is important in a new channel. However, changing campaigns too frequently with limited data can make it difficult to understand which factor is actually influencing performance.
How can Optifeed support 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.
Product data quality becomes directly important when building an OpenAI Ads campaign structure. The more accurate the product title, description, category, price, availability, variant, image, and promotional information is, the more effectively the campaign structure can be designed.
Optifeed can support brands by:
- Organizing product data according to the campaign structure
- Segmenting products based on performance, availability, category, or margin signals
- Making product titles and descriptions easier to understand with AI Enrich
- Keeping price, availability, and variant information up to date
- Creating multichannel feed structures for Google, Meta, TikTok, and AI platforms
- Analyzing which product groups are strongest before campaigns launch
Optifeed’s role is not limited to generating a technical feed output. It helps brands build stronger campaign structures using more accurate and better-organized product data.
A successful OpenAI Ads campaign structure is created when the right objective, appropriate Ad Group segmentation, strong context hints, clear advertising messages, relevant landing pages, and clean product data work together. Campaign settings are important, but the real difference comes from the marketing strategy and data quality behind those settings.
