Data Overview
Churnkey gives you two main data entities in Coupler.io: raw session records and pre-aggregated session summaries. Together they cover the full spectrum from granular interaction logs to rolled-up retention metrics.
Entities
Sessions
One row per churn prevention session — customer ID, session outcome, timing, offers shown, engagement signals
Cohort analysis, individual customer review, funnel debugging
Session aggregations
Rolled-up counts and rates across sessions — saves, cancellations, deflection rates by time period or segment
Dashboards, KPI tracking, trend reporting
Sessions data
Session fields
Session ID
String
Unique identifier for the session
Customer ID
String
Identifier linking back to your customer record
Created at
Timestamp
When the session was initiated
Outcome
String
Result of the session (e.g., saved, cancelled, paused)
Offer shown
String
Which retention offer was presented
Offer accepted
Boolean
Whether the customer accepted the offer
Session duration
Number
Time spent in the cancel flow (seconds)
Cancel reason
String
Reason selected or submitted by the customer
Revenue at risk
Number
MRR associated with the customer at session time
Session metadata
Plan name
String
Subscription plan the customer was on
Billing interval
String
Monthly, annual, etc.
Country
String
Customer's billing country
Source
String
How the session was triggered
Session aggregations data
Aggregation metrics
Total sessions
Number
Count of all sessions in the period
Saves
Number
Sessions that resulted in a retained customer
Cancellations
Number
Sessions that ended in cancellation
Save rate
Number
Percentage of sessions resulting in a save
Revenue saved
Number
MRR recovered through successful saves
Deflection rate
Number
Rate at which customers were deflected from cancelling
Aggregation dimensions
Period
Date
Time bucket for the aggregation
Plan name
String
Grouped by subscription plan
Cancel reason
String
Grouped by stated cancellation reason
Offer type
String
Grouped by the offer presented
Common metric combinations
Save rate by cancel reason — identify which objections are hardest to overcome
Revenue saved by plan — prioritize retention efforts on high-value segments
Session volume vs. save rate over time — spot whether your cancel flow performance is improving
Offer acceptance rate by offer type — determine which offers actually work
Use cases by role
Track weekly save rates and revenue recovered without manually exporting from Churnkey
Compare offer performance to refine which discounts or pauses to show first
Build a Looker Studio dashboard that updates automatically each day
Pull revenue-at-risk and revenue-saved data into spreadsheets for MRR reconciliation
Join Churnkey session data with billing records in BigQuery for a complete churn impact report
Use Aggregate transformation in Coupler.io to roll up saves by billing period
Analyze cancel reasons by plan to inform roadmap prioritization
Send session outcome data to ChatGPT or Claude for automated pattern detection and recommendations
Append data from multiple Churnkey environments (test and production) to compare behavior
Platform-specific notes
Session aggregations are pre-computed by Churnkey — they are not the same as applying Coupler.io's Aggregate transformation to the Sessions entity, though you can use both approaches
The Sessions entity can grow large for high-traffic cancel flows; consider using Coupler.io's Aggregate transformation to summarize before loading into spreadsheet destinations
Revenue fields reflect MRR at the time of the session and are not updated retroactively if a customer's plan changes later
Cancel reasons depend on what options you've configured in your Churnkey cancel flow — custom reasons will appear as-is
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