Five LLMs in parallel.
A prompt battery runs against ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews on every audit so single-model variance does not drive the result.
APP DISCOVERY
AI Discoverability
Measures whether AI assistants — ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews — actually recommend your app, with share-of-voice and intent-coverage against peers.
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Discoverability
What's distinctive.
Cross-channel consistency.
LLMs cross-reference your store listing and your website. Mixed signals between the two depress recommendations — the engine surfaces those inconsistencies explicitly.
Where the AI cites.
For citation-emitting providers, the engine tracks where the AI pulls from — community, editorial, owned, or store — so the source of your AI presence is legible, not opaque.
The methodology.
"LLMs don't match keywords — they match problems to solutions."
- 1
Score across six dimensions
Every audit evaluates your app across six scoring dimensions, run in parallel against all five LLM providers:
- Presence — does your app get mentioned at all for category-relevant prompts?
- Position — when mentioned, where does your app rank in the LLM's response?
- Sentiment — what framing does the AI use when citing your app?
- Intent coverage — across functional, emotional, and social dimensions, which user intents do LLMs associate with you?
- Competitive standing — share of voice vs. competitors across the prompt battery.
- Community health — adjacent signal layer from category-relevant communities.
- 2
Citation analysis
For Perplexity and Google AI Overviews, the engine tracks where the AI cites: community, editorial, owned, or store. Citation source is part of the score.
- 3
Cross-channel consistency
The engine compares store listing positioning to website positioning. LLMs cross-reference both, and inconsistency between them depresses recommendations.
- 4
Ranked, explainable actions
Findings convert to recommendation rows with the signal that triggered each one, the data sources it pulled from, and the projected score impact.
Data sources
Apptonomy prompt battery (versioned with the engine); direct API queries to ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews; published website (when URL available); citation URLs returned by citation-emitting providers; community-signal modules.
AI's role
LLMs are both the runtime (the analysis target) and the parser (extracting structured mentions, positions, sentiment, and intent matches from response text). The six-dimensional model, the citation-source taxonomy, and the cross-channel consistency rubric are human-authored and kept current weekly.
A real recommendation, end to end.
This is the shape of a recommendation row in the Weekly Revision Plan. The reasoning, the sources, and the projected impact are part of the row — not buried in a tooltip.
AI Discoverability
+12 AI Discoverability score.Add 'for beginners' framing across your subtitle, description opener, and screenshot 2 caption.
- Why
- Your app surfaces in only 8% of LLM queries vs. category-leader 52%; the 'beginner-friendly running app' intent has zero presence across all five LLMs, and your website already leads with beginner framing while your store listing emphasizes advanced metrics — a cross-channel inconsistency.
- Sources
- Five-LLM prompt battery, website scrape, listing text, intent map.
- Expected impact
- +12 AI Discoverability score.
What you get.
- Five-LLM share-of-voice — what % of category queries cite your app.
- Intent-coverage matrix — which intents you win, which you lose, and to whom.
- Citation source breakdown — Reddit, editorial, owned, or store-listing.
- Cross-channel consistency report — listing vs. website alignment.
- Recommendation rows — concrete listing edits with expected impact.
How you act on it.
- Approve, edit, or decline each recommendation in the Weekly Revision Plan.
- Recommendations often pair with Store Text edits or Screenshot caption changes — the engine flags the dependency.
- Bulk-approve a batch when you trust the engine on a class of changes.
- Schedule a re-audit to confirm the change moved the AI Discovery score.
AI Discoverability is included on every plan, including Free.
See plans →See whether AI assistants recommend your app.
Paste any App Store or Google Play URL. The first audit is free.
Get a free quick audit for your app.