app-store-optimization
Improves visibility and conversion in the App Store and Google Play — metadata, keywords, screenshots, ratings, and the listing experience that turns an impression into an install. Use this to audit or optimize an app listing, plan a launch listing, diagnose poor install conversi
Install
npx skills add https://github.com/cbrock84/headcount/tree/main/plugins/demand-generation/skills/app-store-optimization
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install cbrock84-headcount@llmmart
git clone https://github.com/cbrock84/headcount.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole cbrock84/headcount collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
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.
Sources
references/sources.md in this skill lists the outside authorities that settle the questions
here — what each one is authoritative for, and what you may do with it. Check them before
answering on anything they cover, and cite what you used. Most are free to read and not free
to reproduce; the use note on each is binding.
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.
Files (headcount)
-
references
-
sources.md 1.8 KB
# Sources — `demand-generation:app-store-optimization` <!-- Generated by scripts/build-sources.py from sources/*.toml. Do not edit. --> Check these before answering on anything they cover, and cite what you used. The use note on each one is binding: most of what a professional cites is free to read and not free to reproduce. ## App Store Review Guidelines Apple · global · **read and cite only — copyrighted, do not reproduce** <https://developer.apple.com/app-store/review/guidelines/> Machine-readable: <https://developer.apple.com/app-store/search/> **Authoritative for:** Whether a listing, screenshot set, price presentation or subscription flow will be rejected. Binding for anything shipping through the App Store, and copyrighted — cite the rule number, do not mirror the text. ## Children's Online Privacy Protection Rule, 16 CFR 312 US Federal Trade Commission · US · public domain (US government) — quote freely <https://www.ecfr.gov/current/title-16/chapter-I/subchapter-C/part-312> Machine-readable: <https://www.ftc.gov/business-guidance/resources/complying-coppa-frequently-asked-questions> **Authoritative for:** Whether a property counts as directed to children, and therefore whether behavioral advertising, retargeting pixels or lead capture may run on it at all. ## Google Play Developer Program Policy Google · global · **read and cite only — copyrighted, do not reproduce** <https://play.google.com/about/developer-content-policy/> **Authoritative for:** Store listing, metadata, ads, data-safety and monetization rules for Android distribution, including the explicit prohibitions on keyword stuffing and incentivized ratings. --- Sources are maintained in `sources/` upstream, not here. If one is wrong, out of date, or missing, fix it there — this file is regenerated and an edit to it is lost.
-
-
SKILL.md 3.7 KB
--- name: app-store-optimization description: Improves visibility and conversion in the App Store and Google Play — metadata, keywords, screenshots, ratings, and the listing experience that turns an impression into an install. Use this to audit or optimize an app listing, plan a launch listing, diagnose poor install conversion, or improve store search visibility. --- # 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. ## Sources `references/sources.md` in this skill lists the outside authorities that settle the questions here — what each one is authoritative for, and what you may do with it. Check them before answering on anything they cover, and cite what you used. Most are free to read and not free to reproduce; the use note on each is binding. ## 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.
Comments (0)
Sign in to join the conversation.
Reviews (0)
No reviews yet.
No comments yet.