Rating Prompt Strategy

appeeky/aso-skills/skills/rating-prompt-strategy

by appeeky3919d7c27402No license2.1K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 2 days ago

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.

Instructions onlyMarketing & Sales
AI-generated overview

Plans when and how mobile apps should prompt users for star ratings to raise ratings and recover from drops.

What it does
This skill produces a rating prompt strategy plan covering success-moment triggers, session-based eligibility criteria, prompt frequency limits, and a pre-prompt survey that filters dissatisfied users before the native review prompt. It includes platform-specific guidance for iOS SKStoreReviewRequest and Android Play In-App Review API, plus version-gating advice and a recovery campaign timeline for apps with low ratings. The deliverable is a structured plan with trigger logic and expected outcomes.
When to use it
Use it when an app's star rating needs improvement, review volume should grow, or prompt timing and targeting need optimization. It also fits recovery after a bad rating period or a rating drop tied to a release.
Requirements
No scripts or tools are required; it is instructions only. It references iOS StoreKit and Android Play In-App Review APIs as context but does not run code.

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
swift
import StoreKit
// Call at the right momentif 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)
kotlin
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 progressDay 1–3: Reply to every negative review acknowledging the issueDay 7:   Fix shipped — reply to previous negative reviews "Fixed in X.X"Day 8+:  Enable prompt for sessions >= 5, no crash last 7 daysWeek 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

Source and attribution

Source:appeeky/aso-skillsinskills/rating-prompt-strategyat commit3919d7c

License: No license

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