Automation triggers

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.

Trigger conditions

Every automation starts with a rating condition – this is your primary filter for targeting reviews:

Exact Targeting
Range Targeting
Exclusion Targeting

“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.

“more than” / “less than” – Cast wider nets for related review types

is more than 3 stars → Catch all positive sentiment (4-5 stars)
is less than 3 stars → Handle all negative feedback (1-2 stars)
is more than 1 star → Avoid the most frustrated users while catching improvable feedback

“More than 3 stars” includes both 4 and 5-star reviews, perfect for general positive response automations.

“is not” – Useful for excluding specific ratings

is not 5 stars → Target all reviews that aren’t perfect
is not 1 star → Avoid extreme negative reviews
is not 3 stars → Focus on clearly positive or negative feedback

Rating strategy examples

The Grateful Fan

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

The Improvement Opportunity

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

The Crisis Manager

Condition: is less than 3 starsUse case: All negative feedback requiring immediate, empathetic response.Risk level: ⭐⭐⭐ High – Frustrated users need careful, personalized handling

Text conditions

Target reviews based on their content with keyword matching:

Contains vs. Does not contain

Contains Keywords
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"

Great for excluding irrelevant reviews:

does not contain "free" → Avoid users only interested in free features
does not contain "fake" → Skip suspected fake reviews
does not contain "competitor" → Ignore comparative reviews
does not contain "trial" → Focus on committed users

Common exclusions:

Spam indicators: "fake", "bot", "paid"
Competitor mentions: Brand names, "better than", "switch to"
Price complaints: "expensive", "cost", "cheap"

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"

Language conditions

Serve your global user base by targeting specific languages:

Primary Market Focus
International Users
Global Catch-All

“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

“Language is [Specific Language]” – Serve key markets

Language is Spanish → Dedicated Spanish market support
Language is German → GDPR-compliant responses for EU users
Language is Japanese → Cultural context-aware responses

Language strategy examples

English-First Approach

Create detailed automations for English reviews first, then add simpler international versions:

5 stars + English + contains "love" → Detailed thank you with feature previews
5 stars + not English → Simple thank you with AI translation

Market-Specific Rules

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

Review length conditions

Fine-tune based on how much detail users provide:

Short Reviews
Detailed Reviews
Exact Length

“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

“longer than X characters” – Engaged users with specific feedback

longer than 200 characters → Detailed feedback worth personalized responses
longer than 100 characters → Moderate detail, specific concerns
These users are more invested and expect thoughtful replies

Best response strategy: Address specific points mentioned

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

Featured review condition

Target reviews that are highlighted or featured in app store listings.

Is Featured
Is Not Featured

“Featured review is” targets reviews currently shown as featured in the store listing.These reviews are the most visible to potential users browsing your app page. Create specific, well-crafted responses for them since they have an outsized impact on download decisions.Use case: Pair with AI-generated responses and detailed instructions to make sure your reply to a featured review is polished and addresses the reviewer’s points directly.

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.

Combining conditions (AND logic)

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

Example combinations

The Engaged Power User

Conditions:

5 stars
contains "feature"
English
longer than 80 characters

Result: Happy users providing detailed feature feedback – perfect candidates for beta programs or surveys.

The International Crisis

Conditions:

less than 3 stars
language is not English
contains "bug"

Result: Non-English users reporting bugs – needs immediate AI translation and escalation.

The Conversion Opportunity

Conditions:

exactly 3 stars
does not contain "price"
longer than 50 characters

Result: Neutral users with specific (non-price) concerns that can be addressed.

Strategy framework

Start with Rating

Choose your primary rating target based on the business goal.

Add Topic Filter

Use text conditions to target specific types of feedback.

Consider Language

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

Fine-tune with Length

Use length conditions to match response effort to user investment.

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.

Debug checklist

Too Few Matches
Too Many Matches
Wrong Matches

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

Your conditions might be too broad:

Add exclusion keywords (does not contain)
Narrow the rating range
Add language or length restrictions
Split into multiple, more specific automations

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

Getting Started

Essentials

Auto‑Replies

Review Management

Integrations

Organizations & Billing

Trigger conditions

Rating strategy examples

Text conditions

Contains vs. Does not contain

Advanced text targeting

Topic Clustering

Sentiment Detection

Language conditions

Language strategy examples

Review length conditions

Length-based strategy

Engagement Level Targeting

Quality Filtering

Featured review condition

Combining conditions (AND logic)

Example combinations

Strategy framework

Testing your conditions

Debug checklist

Actions

Templates

​Trigger conditions

​Rating strategy examples

​Text conditions

​Contains vs. Does not contain

​Advanced text targeting

Topic Clustering

Sentiment Detection

​Language conditions

​Language strategy examples

​Review length conditions

​Length-based strategy

Engagement Level Targeting

Quality Filtering

​Featured review condition

​Combining conditions (AND logic)

​Example combinations

​Strategy framework

​Testing your conditions

​Debug checklist

Actions

Templates

Trigger conditions

Rating strategy examples

Text conditions

Contains vs. Does not contain

Advanced text targeting

Language conditions

Language strategy examples

Review length conditions

Length-based strategy

Featured review condition

Combining conditions (AND logic)

Example combinations

Strategy framework

Testing your conditions

Debug checklist