App store optimization

Two levers, and they are separate problems: being found, and being installed once found. Diagnose which is failing before changing anything.

Being found

The stores index different fields, so the same metadata does not work on both.

• App name / title — the single heaviest field. Brand plus the primary descriptive term. Do not spend it on brand alone.
• Subtitle and keyword field — no repetition across fields; duplicated terms are wasted characters, not reinforcement.
• Long description — indexed on one store, effectively not on the other. Write it for the store that indexes it and for humans on the store that does not.
• Category — pick where you can rank, not where you technically belong.

Target terms with real intent. Ranking first for a term nobody searches is a vanity result.

Being installed

Most visitors decide from the first screenshot and the rating, without scrolling or reading.

• Screenshots — the first two carry the decision. Lead with the outcome or the core screen, with a caption stating the benefit. Never lead with an onboarding or login screen.
• Icon — recognizable at actual size, distinct from category conventions. Test at real scale on a device.
• Rating — the strongest single conversion factor. Prompt for review after a success moment, never on launch or mid-task.
• Video — only if it demonstrates something a screenshot cannot. A weak one costs installs.

Reviews

Respond to negative reviews specifically and without defensiveness, naming the fix and its version where there is one. Prospects read the responses as much as the complaints, and a pattern of real answers converts.

Watch review text for recurring themes — it is the cheapest continuous product research available.

Testing

Change one element at a time and let it run a full weekly cycle; app traffic is strongly day-of-week seasonal. Attributing a lift to the wrong change is worse than not testing.

Tooling

The consoles are the source of truth: App Store Connect and Google Play Console, including their own experiment features — product page optimization and store listing experiments — which test on real store traffic rather than a simulation.

Keyword and competitor research: AppTweak, Sensor Tower, data.ai, AppFollow, and similar. Treat their volume estimates as directional; the stores do not publish the underlying numbers.

Review management and reply workflows live in the consoles or in the same tools, and replying is the part most teams skip.

Never

• Chase a keyword the app does not deliver on. Installs from a mismatched query become one-star reviews and a worse ranking than you started with.
• Change metadata, screenshots, and the icon in the same release. Nothing that moves afterward can be attributed.
• Solicit ratings from a user mid-task. The prompt lands where frustration is highest and the score reflects that.
• Ignore reviews on the version you just shipped. They are the fastest signal you will get that a release broke something.