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RD Station Radar GEO is a free analysis of how ChatGPT and Gemini interpret a brand, with presence, sentiment and competitors. The check takes seconds, but RD Station doesn’t publish how it works. So this review explains what the analysis measures, what it leaves out and when it’s enough.
In short
- Radar GEO, from Brazilian software company RD Station, is free and rates brand presence, sentiment and competitors, only in ChatGPT and Gemini.
- RD Station doesn’t publish its method. The page doesn’t say how many questions the analysis asks or which model answers. It also doesn’t promise the AI’s answers or the cited sites.
- Because the AI’s answer changes with every run, a one-off analysis shows a snapshot. So a small change between two months doesn’t signal a trend.
- For agencies, the score mainly helps to open the conversation with a client. However, trends, competitors and monthly reports call for ongoing monitoring, with fixed, repeated questions.
What is RD Station Radar GEO?
RD Station Radar GEO is a free check of how ChatGPT and Gemini interpret a brand. RD Station is a Brazilian marketing software company. First, you fill in a form with the company name, website, segment and location, plus your name and a business email. Then the tool returns its analysis of the brand.
The official Radar GEO page, in Portuguese, promises the diagnosis in a few seconds. When you submit the form, however, you agree to receive communications from RD Station, which sells marketing and sales software. In other words, the free tool also generates leads for the company.
GEO is the work of getting a brand into AI answers, as our guide to what GEO is explains. So Radar GEO shows a snapshot of that result at a given moment.
Which engines and metrics does the analysis cover?
The analysis covers only ChatGPT and Gemini, and it promises three outputs: brand presence, sentiment and a competitor comparison. According to RD Station, presence measures how much AI mentions the brand, in the context of its segment and location. For sentiment, the higher the score, the more positively AI talks about the brand.
| What the page promises | How RD Station describes it |
|---|---|
| Engines | ChatGPT and Gemini |
| Brand presence | Mentions within the segment and location |
| Sentiment | A higher score when AI speaks well of the brand |
| Competitors | A comparison with the main competitors |
| Insights | Contexts, topics to optimize and the most visible competitors |
In addition, the page’s FAQ says the insights show the contexts where the brand appears and “which prompts or topics need to be optimized” (translated). They also point to the competitors that are most visible in AI answers.
Since the form asks for the company’s location, presence takes that place into account. On the other hand, the page doesn’t list Perplexity, Copilot or Claude among the engines it analyzes. AI in Google Search, such as AI Overviews and AI Mode, is also left out.
How does RD Station Radar GEO arrive at its score?
RD Station doesn’t explain how Radar GEO calculates its scores. The page doesn’t say how many questions the analysis asks, which ones, or which version of each model answers. It also doesn’t say whether the engines search the web or which country the query comes from. In addition, we found no article about the tool in RD Station’s help center. Therefore, nobody can redo the math.
Some signals, however, help you read the result. The form asks for segment and location “for a more precise answer” (translated). In other words, the data you type in is part of the analysis. The page also describes the result as a “current view” (translated) of your content in the AI landscape. So RD Station itself presents the check as a snapshot of the moment, not as a time series.
What does RD Station Radar GEO leave out?
Based on what RD Station publishes, Radar GEO leaves out what you need to verify the score. The page doesn’t list the questions used, and it doesn’t promise the AI’s full answers or the cited sites. It also doesn’t mention history or disclose the sample size. Without that data, the score works as a snapshot, but not as a target.
| What the page doesn’t disclose | Why it matters |
|---|---|
| Questions used | They show if the sample fits your client |
| Full answers | They let you recount mentions and spot errors |
| Cited sites | They point to the sources AI uses for the industry |
| Other engines | Perplexity, Copilot, Claude and AI in Google Search |
| History | Without it, you can’t see change over time |
| Sample size | Without it, there’s no margin of error |
The questions matter more than they seem. RD Station’s own GEO guide explains why. According to the guide, a brand can “show up in institutional searches, but disappear when the question involves comparison, recommendation or choosing a supplier” (translated). Since the page doesn’t show the questions, you don’t know which of these cases the score is based on.
This limit applies to any tracking, too. Rand Fishkin, cofounder of SparkToro, considers visibility percentage across many prompts a reasonable metric. Still, he adds a warning:
“there’s still a giant hole in AI tracking: the prompts.”
Rand Fishkin, SparkToro (2026)
Does a one-off analysis measure a trend?
No. A single analysis shows a snapshot of the day, because the AI’s answer changes with every run. In addition, without the sample size, you can’t calculate the margin of error. So nobody can tell a real change from noise, even between two RD Station Radar GEO checks run with the same data.
Variation is part of how AI tools work. In fact, in a SparkToro study, 600 volunteers ran 12 prompts 2,961 times in ChatGPT, Claude and Google’s AI. The chance of ChatGPT repeating the same list of brands was below 1 in 100. However, the study was done with Gumshoe.ai, a startup that sells AI tracking.
To measure a trend, then, the sample must be known and large. With 30 answers, for example, the margin of error for the presence rate ranges from 18 to 31 points. The math is in our guide to measuring brand mentions and citations, which uses 50 questions, 5 runs and 4 engines per month. Likewise, sources rotate fast. In a SISTRIX study in six countries, not including Brazil, Google’s AI Mode replaced 56% of cited sources every week.
How do you use the Radar GEO result in a client meeting?
Use the result to open the conversation, not as a contract target. RD Station’s Radar GEO for agencies page, in Portuguese, suggests running the analysis on the client’s domain and bringing the diagnosis to the meeting. Then show what the score doesn’t cover and propose a measurement with fixed questions.
- Write down the data you entered: name, website, segment and city. After all, segment and location feed the analysis, and only the same data lets you compare one run with the next.
- List the errors about the brand: AI may get the product, the price or the city wrong. So record each error, because it becomes a correction task.
- Run buying questions: 15 to 20, without naming the brand, in ChatGPT and Gemini, as in the free GEO audit checklist.
- Compare competitors: Radar GEO promises to show the most visible competitors. Next, check whether the same names appear in the answers to the buying questions.
- Propose the baseline: the fixed list of questions, repeated every month, becomes the first deliverable.
RD Station’s GEO guide, in fact, recommends the same exercise. The idea is to research market questions in AI tools and see if the company appears, in what context and next to which competitors. Because this work takes time, charge for the full diagnosis as a fixed-scope project. To compare Radar GEO with a manual test and other free checkers, see our AI visibility checker guide.
When should you move to ongoing monitoring?
Move to ongoing monitoring when the question changes from “does AI know the brand?” to “is the brand growing in the answers?”. Usually, that happens when the client asks for trends, competitors, more engines or a monthly report. In those cases, therefore, RD Station Radar GEO becomes just the starting point.
| Need | Radar GEO | Ongoing monitoring |
|---|---|---|
| Questions | Not disclosed | Your own fixed list |
| Frequency | One-off | Daily or weekly |
| Engines | ChatGPT and Gemini | More options, by plan |
| Answers and sources | Not promised | Some tools export them |
| Price | Free | $29 to $99 per month at entry level |
The prices in the table come from our GEO tools comparison. In the same comparison, four of the seven tools document exporting the text of the answers. So before you subscribe, run the same list in Portuguese during the free trial and compare it with a manual check.
To pay in Brazilian reais, on the other hand, see our guide to the best AEO and GEO tools in Brazil. Of the eight Brazilian tools analyzed there, four publish prices in reais, with entry plans from R$97 to R$1,490 per month.
For a first check on a new client, however, Radar GEO is still useful, because it’s free and takes seconds. NotHuman, which publishes this blog, also works in this market.
Want to know how your brand shows up in AI answers today?
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Main sources
- RD Station, Radar GEO, official page of the free analysis, in Portuguese (2026).
- RD Station, Radar GEO para Agências (Radar GEO for Agencies), in Portuguese (2026).
- RD Station, GEO: o guia da otimização de conteúdo para buscas em IA (GEO: the guide to optimizing content for AI search), in Portuguese (2026).
- SparkToro, study on how inconsistent AI brand recommendations are (2026).
- SISTRIX, stability of the sources cited in AI search (2026).
