Why this exists
Most App Store listings don't lose installs to one big mistake. They lose them to a dozen small ones: a repeated word that wastes ten characters, a first screenshot that shows a login screen, a review prompt that fires before the user has done anything.
This is the checklist I run on every app I ship (KalFit, PlantFit, BudgetFox and the rest). Work through it section by section and tick each box. If you'd rather not grade it by hand, paste the AI prompt at the end of each section into Claude, Gemini or ChatGPT along with your listing.
How to use it in 15 minutes
- Open your App Store product page and App Store Connect side by side.
- Copy your title, subtitle, keyword field, promotional text and description into a note. You'll paste them into the prompts.
- Spend about 3 minutes per section. Anything you can't tick goes on your fix list.
- Fix the metadata items first. Title, subtitle and keyword field only change when you submit a new version, so batch those changes into your next release.
A note on accuracy: Apple documents the character limits and guidelines below. Some things, like exactly how words combine across fields or which locales a storefront indexes, come from ASO practitioners' testing, not from Apple. Where that's the case, I say so. Treat those as strong defaults, and test them on your own app.
1. Metadata (12 checks)
AI prompt: grade my metadata
You are an App Store Optimization auditor. Grade my iOS listing metadata against these rules and return a table: Check | Pass/Fail | Evidence | Fix.
Rules:
1. Title ≤30 chars and contains the primary keyword.
2. Subtitle ≤30 chars, contains a second keyword cluster, reads as a benefit.
3. No word repeated across title, subtitle and keyword field (case-insensitive; treat singular/plural as the same word).
4. Keyword field ≥95 of 100 characters used.
5. Keyword field is comma-separated with no spaces.
6. Keyword field uses single words, not multi-word phrases.
7. No filler words: app, iphone, free, or the category name: [CATEGORY].
8. No competitor brands or trademarks.
9. Every keyword is relevant to what the app does: [ONE-SENTENCE DESCRIPTION OF THE APP].
10. First 2 lines of the description state the core benefit.
Count characters exactly and show the counts. Then suggest one improved title, subtitle and keyword field that fix every failure, with character counts. Do not invent search volume numbers.
Title: [PASTE]
Subtitle: [PASTE]
Keyword field: [PASTE]
Promotional text: [PASTE]
Description (first 3 lines): [PASTE]
2. Visuals (10 checks)
AI prompt: grade my screenshots
I'm attaching my App Store screenshots in order (1 to N) and the top 3 competitor apps' first screenshots for the keyword "[KEYWORD]".
For each of my screenshots, tell me:
- The headline text, and whether it states a user benefit or just a feature
- Whether it's readable at search-result thumbnail size (about 1/3 of screen width)
- What a first-time user would understand in 2 seconds
Then:
1. Judge whether screenshots 1–3 alone explain what the app does and why it's better.
2. Compare my first 3 with the competitors': what do they communicate that I don't?
3. Rewrite all headlines (max 7 words each) so they lead with outcomes, and naturally include these keywords where it fits: [KEYWORDS].
4. Suggest the order of screens I should use.
Be blunt. No praise unless it's earned.
3. Ratings and reviews (7 checks)
AI prompt: grade my reviews
Here are my last [N] App Store reviews (rating, date, title, text) and my replies, if any.
1. Group the 1–3★ reviews into themes. For each theme: number of reviews, one representative quote, and whether it's a bug, missing feature, pricing complaint, or expectation mismatch (the listing promised something the app doesn't do).
2. List any reviews with no reply.
3. Score my existing replies 1–5 for specificity and tone, and rewrite the weakest 3.
4. Expectation mismatches: tell me which line in my listing likely caused each one.
5. Based on review content, suggest the best moment in the app to show the rating prompt.
Reviews:
[PASTE]
4. Conversion (8 checks)
AI prompt: grade my conversion setup
Act as a conversion-rate auditor for an iOS app listing. Here is my current setup:
- In-app events (live/planned): [LIST OR "none"]
- Custom product pages: [LIST AUDIENCE/SOURCE + KEYWORDS ASSIGNED, OR "none"]
- Product Page Optimization tests (past/current): [LIST OR "none"]
- Pricing model and trial: [DESCRIBE]
- Last 3 "What's New" texts: [PASTE]
- App Store Connect funnel for the last 30 days: impressions [X], product page views [Y], first-time downloads [Z]
Tasks:
1. Calculate my page-view rate (Y/X) and conversion rate (Z/Y). Don't compare them to "industry averages" unless you can name the source.
2. Propose 3 in-app event ideas for the next 60 days that fit my app ([ONE-LINE DESCRIPTION]), each with a name ≤30 chars, short description ≤50 chars, long description ≤120 chars. Show character counts.
3. Propose 2 custom product pages (audience, headline for screenshot 1, keywords to assign).
4. Propose 1 Product Page Optimization test with a clear hypothesis.
5. Rewrite my last "What's New" to be benefit-led, ≤3 short lines.
5. Localization (6 checks)
AI prompt: grade my localization
My app: [ONE-LINE DESCRIPTION]. Primary storefront: [e.g. US].
Here is my English (US) metadata: Title [PASTE] / Subtitle [PASTE] / Keyword field [PASTE].
Here is my metadata for these other locales: [LOCALE: TITLE / SUBTITLE / KEYWORDS ...].
1. For each locale, check that the title and subtitle are ≤30 characters and the keyword field ≤100, and show the counts.
2. Flag words duplicated across locales that may be indexed in the same storefront (assume US indexes English (US) + Spanish (Mexico); tell me this is a practitioner assumption, not Apple documentation).
3. For each non-English locale, flag any keyword that looks like a literal translation where locals would likely search a different term, and suggest alternatives. Mark your confidence (high/medium/low) and tell me which ones a native speaker must verify.
4. Suggest how to use the Spanish (Mexico) keyword field to add English-speaking US keywords I couldn't fit, without duplicates.
6. Technical and hygiene (4 checks)
AI prompt: the master audit (all sections at once)
You are a senior App Store Optimization consultant auditing an indie iOS app. Use only the data I give you. Never invent search volumes, rankings or benchmarks. If something needs data I haven't provided, say "needs data".
App: [NAME] | Category: [CATEGORY] | What it does: [ONE SENTENCE] | Main storefront: [COUNTRY]
Title: [ ] | Subtitle: [ ] | Keyword field: [ ] | Promotional text: [ ] | Description first 3 lines: [ ]
Screenshot headlines in order: [ ]
Preview video: [yes/no + first 3 seconds description]
Rating and count: [ ] | Replies to 1–3★ in last 90 days: [ % ]
Review prompt trigger: [WHEN]
In-app events / custom product pages / PPO tests: [ ]
Localized locales: [ ]
Output:
1. A score out of 47 (one point per check below) with a Pass / Fail / Needs data table.
2. The 5 fixes with the biggest expected impact, ranked, each with the exact new text where relevant (show character counts).
3. What to put in my next app update vs what I can change today without one.
Checks: [PASTE THE 47 CHECK TITLES FROM THIS CHECKLIST]
Your 15-minute fix list
| Priority | What to fix | Needs a new version? |
|---|---|---|
| 1 | Duplicate words, spaces, filler in title/subtitle/keyword field (checks 3–8) | Yes, batch into the next release |
| 2 | Screenshot 1–3 headlines (checks 13–15) | Yes for screenshots (new version), or test with PPO |
| 3 | Unreplied 1–3★ reviews (check 26) | No, do it today |
| 4 | Promotional text (check 11) | No, do it today |
| 5 | Review prompt timing (check 24) | Yes, it's an app code change |
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