Generative engine optimization tool built around prompt gaps
A generative engine optimization tool measures how AI engines describe and recommend your brand so you can improve it. MentionRadar runs your prompts weekly in ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews and lists the gaps where a competitor is named and you are not.
- Prompt gaps by engine and competitor
- Cited pages behind each gap (Growth+)
- Weekly re-measurement on fixed prompts
- AI visibility score and position history
| Prompt | Engine | Named instead | Cited page |
|---|---|---|---|
| best e-bike for a hilly commute | Perplexity | Alto Bikes #1 | urbanrider-reviews.com |
| folding e-bike for train commuters | ChatGPT | Ridgeline #2 | reddit.com |
| e-bike with the longest range under 3000 | AI Overviews | Alto Bikes #1 | commutergear-blog.com |
| alternatives to Ridgeline e-bikes | Gemini | Alto Bikes #3 | youtube.com |
| cargo e-bike for school runs | Claude | Ridgeline #1 | familyride-guide.com |
Why gaps beat averages in GEO
An average score tells you how you are doing. It does not tell you what to do on Monday. Generative engine optimization gets concrete when you look at single answers where you lost, and the clearest loss is a prompt where the engine names a competitor and leaves you out.
MentionRadar stores every competitor named in every tracked answer, so the gap rows come straight from your weekly runs. Each row has the question, the engine, who took the place and in which position. From Growth upward it also shows the pages the engine cited for that answer, which is usually where the explanation sits.
Gaps also group well. Five gaps that all cite the same review site are one outreach task, not five. Three gaps on comparison prompts where only your competitors have comparison pages are one content task. That grouping is the core of a working LLM SEO tool workflow.
The GEO measurement loop
Four steps, repeated on the weekly run. The loop only works if the prompt set stays the same between measurements.
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1
Baseline
Run the full prompt set for two or three weeks before changing anything. Answers vary between runs, so one week is a sample, not a baseline.
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2
Change one thing
Pick a group of gaps with a shared cause and act on it: a comparison page, an updated guide, a pitch to the site the engine cites.
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3
Re-measure weekly
Leave the prompts alone and watch the same rows. Note which engine moves first and whether the cited pages change.
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4
Keep or drop
If the gaps close and stay closed for several runs, keep the change and move to the next group. If nothing moves, try another cause.
In this chart, Kestrel sits outside the answer for three baseline weeks (drawn at the bottom of the chart). In week 35 the team publishes a hill climbing comparison and gets added to a review site the engine cited. Perplexity names Kestrel from week 36 and moves it to second by week 39.
The overall effect shows in the AI visibility tracker score, but the loop is judged on the rows you targeted.
Typical causes of a gap and the usual response
| What the cited pages show | Likely cause | Usual response |
|---|---|---|
| A review or guide that lists competitors only | You are missing from a source the engine trusts | Pitch the editor, offer a product to test |
| A competitor's own comparison page | They answered the question and you did not | Publish a fair comparison on your site |
| A forum or Reddit thread | Buyers recommend others in public discussion | Join relevant threads openly as the brand |
| Your page, but with old facts | The engine reads outdated information | Update the page, keep facts consistent |
| No citations at all | The answer comes from what the model learned earlier | Build mentions over time, measure over months |
Gaps are competitor intelligence too. If one rival keeps taking your place across engines, the competitor monitoring tool view shows what is being said about them on the web, and the AEO tool checklist covers the groundwork that closes most gaps.
Questions about generative engine optimization tools
What is generative engine optimization?
Generative engine optimization, or GEO, is the work of improving how generative AI engines such as ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews talk about your brand. It overlaps heavily with answer engine optimization. The practical goal is the same: be named, and ideally recommended, in the answers your buyers read.
What is a prompt gap?
A prompt gap is a tracked prompt where an engine names at least one of your competitors and does not name you. It is the most actionable row in GEO data, because it shows the exact question, the engine, who took the spot and, on Growth and higher, which pages the engine cited.
How do I measure whether GEO work is paying off?
Keep the prompt set fixed, record a baseline, make one change, and compare the next weekly runs on the same prompts. MentionRadar keeps the history, so you can see when a gap closes, which engine moved first and how the AI visibility score responds.
How quickly do AI answers change after I publish something?
It varies by engine. Engines that search the web at answer time can pick up a new or updated page within days or weeks, while answers drawn mainly from what a model learned earlier move more slowly. That is why a few weeks of weekly runs say more than a single check.
Which plan do I need for GEO work?
Starter tracks 15 prompts in ChatGPT, Perplexity and Google AI Overviews and shows which competitors are named where you are not. Growth tracks 40 prompts in all five engines and adds the cited pages behind each answer, which most teams need to decide what to change.
Does MentionRadar write or publish GEO content for me?
No. It measures and shows the evidence. It needs no access to your website and does not publish anything on your behalf, so your team stays in control of what goes live.
Find your first prompt gaps
Scan your brand from the homepage. You see real web mentions and an AI engine answer in about a minute, before you create an account.