App GEO: how to get your app recommended by ChatGPT, Gemini and Perplexity.
"What is the best app for…" is now a question people ask an AI. The answer names a handful of apps. This is the playbook we use to get a client's app into that handful.
ASO gets you ranked inside the store. App GEO gets you named before the user ever opens one.
How assistants learn about apps
AppTweak defines GEO for apps as optimising every surface an AI assistant learns from, so the app is understood and recommended. In practice there are three surfaces:
| Surface | What it includes | What to fix first |
|---|---|---|
| Store presence | Title, category, description, reviews, release notes | A first paragraph that states what the app does, for whom, and the price model |
| Owned web presence | Website, FAQ, changelog, help docs | A crawlable page per app whose facts match the listing |
| External authority | Comparison articles, lists, reviews, forums, press | Accurate mentions in the articles that rank for "best X app" |
Store pages matter most. AppTweak found they accounted for 47% of citations for apps and 60% for games in ChatGPT app recommendations in May 2026. Since 3 November 2025 the App Store has been fully crawlable on the web, so iOS listings now count as well as Google Play.
Step 1: one description, everywhere
Pick one core intent ("expense tracking for small shop owners") and describe it the same way in the short description, the first line of the full description, the website's first paragraph and your social bios. Use the same feature names everywhere. A model that sees three descriptions of your app has to guess which is right; a model that sees one repeats it.
Step 2: make every source readable
- Let AI search crawlers in. OpenAI's
OAI-SearchBotdecides whether ChatGPT search can show you; see which OpenAI bot does what. - Make sure the site renders its content without JavaScript.
- Add MobileApplication structured data with links to both stores.
- Keep release notes descriptive. "Bug fixes" teaches a model nothing; "Added Hindi voice input" teaches it a feature.
Step 3: earn the outside mentions
When an assistant recommends apps it leans on listicles and comparisons that already rank. List the ten articles that rank for "best [your category] app" in your markets, check whether you are in them and whether the description is accurate, and pitch the ones where you are missing with something useful: a free account to test, a clear feature comparison, real numbers.
Step 4: Google's own assistants
Google Play now has Ask Play on listings, and the Gemini app can recommend and install apps directly. Both read the same three surfaces, so the work above pays twice.
Step 5: measure influence, not position
- Write 30 to 50 prompts real users would type, by intent and market.
- Run them monthly in ChatGPT, Gemini, Perplexity and Copilot.
- Record whether your app is named, in what position, alongside which competitors, and which sources are cited.
- Track the share of prompts where you are named. That is your GEO number.
This is exactly the overlap of ASO and GEO we work in. If you want the panel built and run for you, see GEO for apps.
Questions people ask
How does ChatGPT decide which apps to recommend?
OpenAI has not published a formula. Studies of citations show it leans on app store pages, the app's website and third-party comparisons, so consistent, accurate information across all three matters most.
Is GEO for apps different from ASO?
ASO ranks your app inside a store. GEO for apps gets your app named in AI answers outside the store. They share inputs, especially the store listing, so the same team should own both.
How do I measure if AI assistants recommend my app?
Run a fixed set of real-user prompts each month across ChatGPT, Gemini, Perplexity and Copilot, and track the share of prompts where your app is named.
Want this mapped onto your product?
See how our GEO work runs, or send your store link and a founder will reply personally.
