rating-prompt-strategy
When the user wants to improve their app's star rating, increase ratings volume, optimize when and how they prompt users for a review, or recover from a bad rating period. Use when the user mentions "app rating", "star rating", "review prompt", "SKStoreReviewRequest", "In-App Review API", "ask for review", "low rating", "rating drop", "get more reviews", or "recover from 1-star". For responding to reviews, see review-management. For overall ASO health, see aso-audit.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/appeeky/aso-skills --skill rating-prompt-strategy- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads rating-prompt-strategy automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Rating Prompt Strategy
You optimize when, how, and to whom an app shows review prompts — maximizing high ratings while minimizing negative ones. Ratings are an App Store ranking signal and a conversion factor on the product page.
Why Ratings Matter for ASO
- Search ranking — Apps with higher ratings rank better for competitive keywords
- Conversion — Rating stars are visible in search results; a 4.8 beats 4.2 at a glance
- iOS: Rating resets per version (you can request a reset in App Store Connect)
- Android: Ratings are permanent and cumulative — one bad period is hard to recover
The Core Rule
Only prompt users who have experienced value. Prompting too early produces low ratings. Prompting at a success moment produces 4–5 star ratings.
iOS — SKStoreReviewRequest
Apple's native prompt. Rules:
- Shows at most 3 times per year regardless of how many times you call it
- Apple controls the display logic — calling it doesn't guarantee it shows
- Never prompt after an error, crash, or frustrating moment
- Cannot customize the prompt UI
import StoreKit
// Call at the right moment
if let scene = UIApplication.shared.connectedScenes.first as? UIWindowScene {
SKStoreReviewController.requestReview(in: scene)
}
Android — Play In-App Review API
Google's native prompt. Rules:
- No hard limits, but Google throttles it if called too often
- Show after a clear positive moment
- Cannot determine if the user actually rated (privacy)
val manager = ReviewManagerFactory.create(context)
val request = manager.requestReviewFlow()
request.addOnCompleteListener { task ->
if (task.isSuccessful) {
val reviewInfo = task.result
val flow = manager.launchReviewFlow(activity, reviewInfo)
flow.addOnCompleteListener { /* proceed */ }
}
}
Timing Framework
The Success Moment Trigger
Define 1–3 "success moments" in your app where users are most satisfied:
| App Type | Good Prompt Moments | Bad Prompt Moments |
|---|---|---|
| Fitness | After completing a workout | After skipping a session |
| Productivity | After completing a project/task | After a failed save or sync error |
| Games | After winning a level or beating a boss | After losing or failing |
| Finance | After first successful transaction | After a confusing error |
| Meditation | After completing a session | On cold open |
| Shopping | After a successful purchase/delivery | After a failed checkout |
Session-Based Rules
Only prompt users who meet all criteria:
Criteria to prompt:
✓ Sessions >= 3 (not a first-time user)
✓ Time since install >= 3 days
✓ Has completed [activation event] at least once
✓ No crash in last session
✓ No negative signal (error, cancellation) in current session
✓ Not already rated this version
Pre-Prompt Survey (Recommended)
Before triggering the native prompt, show a single in-app question:
"Are you enjoying [App Name]?"
[Yes, love it!] [Not really]
- "Yes" → trigger
SKStoreReviewRequest/ Play In-App Review - "Not really" → show a feedback form (email or in-app), do not trigger the native prompt
This filters out dissatisfied users before they can rate you 1–2 stars.
Expected improvement: 0.3–0.8 stars on average with a pre-prompt filter.
Version-Gating (iOS)
iOS allows you to reset ratings per version in App Store Connect. Use this strategically:
- Reset after a major improvement — If you fixed the top-complained issues
- Do not reset after a controversial change that users disliked
- After a reset, run an aggressive (but filtered) prompt campaign in the first 7 days
- Target your most engaged users first (longest session history)
Recovering from a Rating Drop
Diagnosis
- Check which version caused the drop — correlate with release dates
- Read the 1-star reviews for that period — find the common complaint
- Fix the issue in the next release
- Reply to every 1–3 star review (see
review-managementskill)
Recovery Campaign
After the fix is shipped:
- Reply to negative reviews: "Fixed in version X.X — please update and let us know"
- Some users will update their rating after a reply
- Run a prompt campaign targeted at your most loyal users (highest session count)
- Do not prompt users who left a negative review
Timeline
Day 0: Issue identified — hotfix or patch in progress
Day 1–3: Reply to every negative review acknowledging the issue
Day 7: Fix shipped — reply to previous negative reviews "Fixed in X.X"
Day 8+: Enable prompt for sessions >= 5, no crash last 7 days
Week 3: Monitor rating trend — should recover 0.2–0.5 stars in 2–4 weeks
Prompt Frequency
| Platform | Maximum | Recommended |
|---|---|---|
| iOS | 3× per 365 days (Apple-enforced) | 1–2× per version |
| Android | No hard limit (Google throttles) | 1× per 30 days per user |
Never show the prompt twice in the same session.
Output Format
Rating Strategy Plan
Current rating: [X.X] ★ ([N] ratings)
Platform: iOS / Android / Both
Success moments identified:
1. [Event name] — fires when [condition]
2. [Event name] — fires when [condition]
Pre-prompt survey: Yes / No
If yes: "Are you enjoying [App Name]?" → Yes / Not really
Prompt trigger logic:
Sessions >= [N]
Days since install >= [N]
No crash in last [N] sessions
[Activation event] completed: yes
Already rated this version: no
Expected outcome: +[X] stars over [N] weeks
Recovery plan (if rating < 4.0):
1. [Fix] — ship by [date]
2. [Reply strategy] — [N] reviews to address
3. [Prompt campaign] — start [date], target [segment]
Related Skills
review-management— Respond to reviews to recover ratingonboarding-optimization— Fix activation issues that drive 1-star reviewsandroid-aso— Play In-App Review API contextretention-optimization— Engaged users give better ratings
FAQ
What does the rating-prompt-strategy skill do?
When the user wants to improve their app's star rating, increase ratings volume, optimize when and how they prompt users for a review, or recover from a bad rating period. Use when the user mentions "app rating", "star rating", "review prompt", "SKStoreReviewRequest", "In-App Review API", "ask for review", "low rating", "rating drop", "get more reviews", or "recover from 1-star". For responding to reviews, see review-management. For overall ASO health, see aso-audit.
How do I install rating-prompt-strategy?
Run npx skills add https://github.com/appeeky/aso-skills --skill rating-prompt-strategy in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/rating-prompt-strategy/ (personal) or .claude/skills/rating-prompt-strategy/ (project).
Which AI agents can use rating-prompt-strategy?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is rating-prompt-strategy safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains rating-prompt-strategy?
It is published by appeeky in appeeky/aso-skills. It has 2,506 recorded installs.
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