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Triggers are the brain of your automation rules – they determine which reviews get automatic responses and which ones don’t. Think of them as smart filters that evaluate every incoming review against your criteria.
The secret to great automations: Start specific, then expand. It’s easier to broaden a narrow rule than to fix an overly broad one that’s responding to the wrong reviews.

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Trigger conditions

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Every automation starts with a rating condition – this is your primary filter for targeting reviews:
“is exactly” – Perfect for specific scenarios
  • is exactly 5 stars → Thank your biggest fans
  • is exactly 1 star → Handle crisis situations with care
  • is exactly 3 stars → Target neutral reviews for improvement opportunities
Be careful with “exactly 1 star” rules – these users are often extremely frustrated and may benefit from manual, personalized responses.

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Rating strategy examples

Condition: is exactly 5 starsUse case: Thank users who love your app, potentially ask for referrals or feature requests.Risk level: ⭐ Low – Happy users appreciate acknowledgment
Condition: is exactly 3 starsUse case: Users who like your app but have specific concerns worth addressing.Risk level: ⭐⭐ Medium – These users can often be converted to higher ratings
Condition: is less than 3 starsUse case: All negative feedback requiring immediate, empathetic response.Risk level: ⭐⭐⭐ High – Frustrated users need careful, personalized handling

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Text conditions

Target reviews based on their content with keyword matching:

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Contains vs. Does not contain

Perfect for identifying specific topics:
contains "bug" → Technical issues requiring dev team attention
contains "love" → Positive sentiment worth celebrating  
contains "subscription" → Billing-related questions
contains "crash" → Critical stability issues
contains "update" → Feature requests or update feedback
Pro tips:
  • Use multiple automations for different keywords rather than one complex rule
  • Include common misspellings: "recieve" and "receive"
  • Consider synonyms: "bug", "glitch", "broken", "error"

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Advanced text targeting

Topic Clustering

Group related keywords:
  • Bug reports: "crash", "freeze", "error", "broken"
  • Feature requests: "add", "wish", "would like", "feature"
  • Positive sentiment: "love", "amazing", "perfect", "excellent"
  • Billing issues: "charge", "subscription", "cancel", "refund"

Sentiment Detection

Emotion-based targeting:
  • Frustrated: "frustrated", "annoying", "terrible"
  • Excited: "awesome", "incredible", "blown away"
  • Confused: "confusing", "don't understand", "how do"
  • Grateful: "thank you", "appreciate", "helpful"

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Language conditions

Serve your global user base by targeting specific languages:
“Language is English” – Target your primary market
  • Use your best templates and most detailed responses
  • Perfect for testing new automations before global rollout
  • Ideal when you have specific English-only offers or content

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Language strategy examples

Create detailed automations for English reviews first, then add simpler international versions:
  1. 5 stars + English + contains "love" → Detailed thank you with feature previews
  2. 5 stars + not English → Simple thank you with AI translation
Customize responses for key markets:
  • German users: Include GDPR compliance mentions in data-related responses
  • Japanese users: Use more formal, respectful language structures
  • Spanish users: Include cultural context and community references

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Review length conditions

Fine-tune based on how much detail users provide:
“shorter than X characters” – Quick ratings with minimal text
  • shorter than 50 characters → Brief ratings like “Good app” or ”⭐⭐⭐⭐⭐”
  • Perfect for simple thank you messages
  • Often just emoji or very brief sentiment
Best response strategy: Short, sweet acknowledgments

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Length-based strategy

Engagement Level Targeting

Match response effort to user investment:
  • Short reviews (< 50 chars) → Brief, friendly acknowledgment
  • Medium reviews (50-200 chars) → Standard template responses
  • Long reviews (200+ chars) → Detailed, personalized replies

Quality Filtering

Use length to identify valuable feedback:
  • Combine longer than 100 characters + contains "feature"
  • Target users who provide actionable feedback
  • Prioritize responses to detailed suggestions
Target reviews that are highlighted or featured in app store listings.
Featured reviews change over time as the app store rotates them. If a review loses its featured status after your automation already responded, the response remains in place.

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Combining conditions (AND logic)

The real power comes from combining multiple conditions with AND logic:

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Example combinations

Conditions:
  • 5 stars
  • contains "feature"
  • English
  • longer than 80 characters
Result: Happy users providing detailed feature feedback – perfect candidates for beta programs or surveys.
Conditions:
  • less than 3 stars
  • language is not English
  • contains "bug"
Result: Non-English users reporting bugs – needs immediate AI translation and escalation.
Conditions:
  • exactly 3 stars
  • does not contain "price"
  • longer than 50 characters
Result: Neutral users with specific (non-price) concerns that can be addressed.

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Strategy framework

1

Start with Rating

Choose your primary rating target based on the business goal.
2

Add Topic Filter

Use text conditions to target specific types of feedback.
3

Consider Language

Decide if you want language-specific responses or global coverage.
4

Fine-tune with Length

Use length conditions to match response effort to user investment.

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Testing your conditions

Always test before going live! Create automations in disabled mode first, then check the Reviews Feed to see which reviews would have matched your conditions.

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Debug checklist

Your conditions might be too specific:
  • Remove one condition at a time to see which is limiting matches
  • Check for typos in keywords
  • Consider synonyms and alternative phrasings
  • Verify your apps are properly connected
Master these trigger conditions, and you’ll create automations that respond to exactly the right reviews at exactly the right time. Next, learn how to craft the perfect responses in the Actions guide.

Actions

Master template-based and AI-generated responses

Templates

Create response templates that power your automations