> 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.

fetch
$curl "https://skillshub.wtf/Eronred/aso-skills/rating-prompt-strategy?format=md"
SKILL.mdrating-prompt-strategy

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 TypeGood Prompt MomentsBad Prompt Moments
FitnessAfter completing a workoutAfter skipping a session
ProductivityAfter completing a project/taskAfter a failed save or sync error
GamesAfter winning a level or beating a bossAfter losing or failing
FinanceAfter first successful transactionAfter a confusing error
MeditationAfter completing a sessionOn cold open
ShoppingAfter a successful purchase/deliveryAfter 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

  1. Check which version caused the drop — correlate with release dates
  2. Read the 1-star reviews for that period — find the common complaint
  3. Fix the issue in the next release
  4. Reply to every 1–3 star review (see review-management skill)

Recovery Campaign

After the fix is shipped:

  1. Reply to negative reviews: "Fixed in version X.X — please update and let us know"
  2. Some users will update their rating after a reply
  3. Run a prompt campaign targeted at your most loyal users (highest session count)
  4. 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

PlatformMaximumRecommended
iOS3× per 365 days (Apple-enforced)1–2× per version
AndroidNo 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 rating
  • onboarding-optimization — Fix activation issues that drive 1-star reviews
  • android-aso — Play In-App Review API context
  • retention-optimization — Engaged users give better ratings

> related_skills --same-repo

> subscription-lifecycle

When the user wants to optimize their subscription business end-to-end — from trial start through renewal, cancellation, and win-back. Use when the user mentions "subscription lifecycle", "trial conversion", "churn", "cancellation", "win-back", "lapsed subscribers", "dunning", "billing retry", "grace period", "renewal rate", "subscriber LTV", or "resubscribe". For paywall design and pricing strategy, see monetization-strategy. For subscription analytics dashboards, see app-analytics.

> seasonal-aso

When the user wants to optimize their App Store listing for seasonal events, holidays, or trending moments — including keyword opportunities, metadata updates, screenshot theming, and timing strategy. Use when the user mentions "seasonal", "holiday", "Christmas", "New Year", "Valentine's Day", "summer", "back to school", "seasonal keywords", "trending now", "limited time", or wants to capitalize on a calendar event. For general keyword research, see keyword-research. For full metadata rewrites,

> press-and-pr

When the user wants to get press coverage, media mentions, or editorial features for their app — including writing press releases, pitching journalists, getting on "best apps" lists, or building an app press kit. Use when the user mentions "press", "PR", "media coverage", "TechCrunch", "journalist", "press release", "app press kit", "get featured in media", "editorial coverage", "review from a blogger", or "app launch announcement". For Apple editorial featuring, see app-store-featured. For laun

> onboarding-optimization

When the user wants to improve their app's onboarding experience, increase activation rate, reduce Day 1 drop-off, or optimize the first-run flow. Use when the user mentions "onboarding", "first-run", "activation", "tutorial", "day 1 retention", "new user flow", "permission prompts", "sign-up conversion", "onboarding funnel", or "users dropping off early". For overall retention strategy, see retention-optimization. For paywall placement, see monetization-strategy.

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