Rating prompt strategy
Quick answer
- 01What is it?
- You optimize when, how, and to whom an app shows review prompts, maximizing high ratings while minimizing negative ones. What sets it apart is how it narrows rating prompt strategy into one specific workflow rather than a broad, generic prompt.
- 02Inputs
- Context the agent needs: your goals, audience, constraints, and any source material the skill asks for.
- 03Output
- A ready-to-use result: the analysis, copy, or recommendations the agent produces.
Add this skill
Install as a package
Installs this one skill package for your coding agent, including any supporting files that skill ships with — not every skill in the repository. Read the tutorial.
$ npx skills add eronred/aso-skills --skill rating-prompt-strategyUse in Profound
Copy this file into a new Profound Skill. That's it, nothing else to install.
Copy and create in ProfoundRating 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
Common questions
How do I install Rating prompt strategy in Cursor, Claude Code, or Codex?
Run npx skills add eronred/aso-skills --skill rating-prompt-strategy in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only Rating prompt strategy, not every skill in the repository.
Where does Rating prompt strategy come from and what license is it under?
Rating prompt strategy comes from the eronred/aso-skills repository on GitHub. That repository has 1.6K GitHub stars. The skill is published under the MIT license.
Prefer plain text? Read the Rating prompt strategy guide as markdown.
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