Understand the category
See which advertisers account for the largest share of sponsored placements in the available category snapshot, then inspect the ads behind that position.
Know who is visible before you plan.Personalized Ads Intelligence
Choose your category, company, and competitors. The dashboard organizes available ChatGPT ad observations into the market, rival, opportunity, context, and campaign evidence your team needs to make a decision.
Start free with a personalized view of the available intelligence evidence.
A "ChatGPT ads dashboard" can mean one of two things. A performance dashboard reports on your own campaigns, through OpenAI's Ads Manager or a tool that reads its Ads API. A market dashboard shows which other advertisers appear in ChatGPT, with their ads and the questions they appeared for. This page is the second kind.
| OpenAI Ads Manager reporting | ChatGPT Ad Library dashboard | |
|---|---|---|
| Whose ads | Your own ad account | Advertisers observed in our library |
| Data source | OpenAI's delivery data | Ad placements our collector recorded in ChatGPT |
| Metrics | Impressions, clicks, spend, CTR, CPC, CPM, conversions, CPA, attributed sales and ROAS | Observed placements, ads, advertisers and the questions they appeared for |
| Competitors' ads | No | Yes |
| Spend and cost data | Yes | No |
OpenAI's reporting covers impressions, clicks, spend, CTR, CPC and CPM, plus conversions, cost per action, post-click conversion rate, attributed sales and return on ad spend. Reports can be broken down by country, device, platform and product. Impressions and clicks can appear within minutes, spend updates later, and conversions need at least a day. Hourly and product reporting go back about 30 days, and other delivery reporting 365 days. Conversions use a 30-day click and 1-day view window by default. It covers only your own ad account.
Source: OpenAI's reporting documentation, checked on 29 Oct 2026. More: ChatGPT ads measurement and ChatGPT Ads API.
It turns a large public ad library into a focused research workspace for one company and category. Instead of browsing thousands of ads without a plan, you begin with the category leaders, compare selected rivals, investigate lower-pressure prompt territories, inspect inferred context and observed campaign-tag evidence, and open the creatives that support each finding. The result is not an automatically generated market story. It is a structured, evidence-linked view that helps a marketer decide where to investigate and what to test next.
It shows no spend, CPC, impressions or conversions for any advertiser; those exist only in each advertiser's own Ads Manager. Our counts describe the questions we ask, not all of ChatGPT.
The dashboard is organized around the questions marketers, founders, product teams, and agencies ask before they spend time or budget.
See which advertisers account for the largest share of sponsored placements in the available category snapshot, then inspect the ads behind that position.
Know who is visible before you plan.Select up to three competitors and compare their observed share, creatives, prompt territories, landing-page campaign tags, and inferred targeting context.
Replace generic competitor research with evidence.Rank semantic prompt groups by verified openness, low advertiser pressure, evidence coverage, and relevance to your product description.
Build a test backlog from observed gaps.Personalization changes the order and relevance of the evidence. It does not change the observed facts or start a private monitoring process.
Select the category you want to understand and the competitors you want kept in view.
Provide your company, website, and product description so the workspace can resolve entities and rank product-relevant opportunities.
Start with leaders and composition, then move into competitor, opportunity, context, campaign, or ad evidence.
Open the advertiser profiles, prompts, creatives, and observed landing-page evidence behind each conclusion.
Begin with category intelligence, then carry the same evidence into deeper monitoring, planning, and controlled campaign work.
Category composition and advertiser ranking
Selected competitor comparison and prompt territories
Semantic opportunity groups and supporting evidence
Inferred context and observed campaign-tag research
Searchable advertiser and creative evidence
Dedicated advertiser and prompt monitoring
Visibility history and supported change detection
Evidence-backed campaign planning, activation, alerts, and briefings
What the evidence supports, where it stops, and how the dashboard should be used.
It is a research workspace that organizes observed ChatGPT sponsored placements, advertisers, creatives, prompt territories, inferred context, and campaign-tag evidence around a selected category, company, and competitor set.
No. The initial dashboard personalizes evidence already available in the shared library. Dedicated recurring monitoring begins only after its scope and coverage are confirmed.
No. The dashboard is category-first, so companies that have not been observed can still study market leaders, selected competitors, lower-pressure prompt territories, and campaign evidence.
Dashboard loading is deterministic. It composes stored observations and calculated evidence. Product relevance can help order opportunities, but observed facts remain separate from personalization.
Yes. Ads Manager reporting, also available through the Ads API, shows impressions, clicks, spend, CTR, CPC, CPM and conversions for your own ad account. It doesn't show other advertisers' ads.
Not in Ads Manager. Our library has recorded 19,050 advertisers since Apr 2026, and the dashboard shows their ads and the questions they appeared for, but not their spend.
Choose a category and the rivals you care about. The evidence stays linked to the ads and advertisers behind it.
Questions about the data, a brand you expected to see, partnerships, or access to the intelligence layer. We read every message.