LostChurn Docs
Cancel Flows

Measuring Saves

Track cancel flow effectiveness with save rates, offer acceptance rates, churn impact, and revenue saved metrics.

Measuring how well your cancel flows perform is essential to optimizing them. LostChurn tracks every cancel flow session from start to finish, recording which steps subscribers see, which offers they accept or decline, and the revenue impact of each outcome.

Key Metrics

Save Rate

The most important metric for cancel flow effectiveness.

Save rate = Saved sessions / Total cancel flow sessions

A session is counted as "Saved" when the subscriber accepts an offer (pause, downgrade, discount, or extension) and does not proceed with cancellation. A session is "Churned" when the subscriber declines all offers and completes the cancellation.

Save RateAssessment
30%+Excellent — your flows are highly effective
15-30%Good — typical for well-configured flows
5-15%Fair — review your offers and survey-to-offer mapping
Below 5%Needs attention — offers may not match subscriber needs

Churn Rate Impact

Cancel flows reduce your voluntary churn rate. LostChurn calculates the impact by comparing:

  • Baseline voluntary churn rate — Churn rate before cancel flows were enabled (or from periods when flows were inactive)
  • Current voluntary churn rate — Churn rate with cancel flows active
  • Churn reduction — The percentage decrease attributed to cancel flow saves

View this in the dashboard under Cancel Flows > Impact. The comparison accounts for seasonal and growth-related variations to give an accurate picture.

Offer Acceptance Rate by Type

Not all offer types perform equally. Track acceptance rates for each to understand what resonates with your subscribers:

Offer TypeWhat to Measure
PauseAcceptance rate, return rate after pause ends
DowngradeAcceptance rate, re-upgrade rate over time
DiscountAcceptance rate, retention after discount expires
ExtensionAcceptance rate, trial-to-paid conversion rate

Compare these rates to determine which offer types deliver the best retention per dollar of revenue impact. A discount might have a higher acceptance rate than a pause, but the pause might deliver better long-term retention.

Revenue Saved

Revenue saved measures the MRR that would have been lost if the subscriber had cancelled, but was retained through a cancel flow offer.

Revenue saved = Sum of MRR from all Saved sessions

LostChurn captures the mrr_cents value from each cancel feedback record, giving you an accurate picture of how much revenue your cancel flows protect each month.

This metric accounts for the type of save:

Save TypeRevenue Calculation
PauseFull MRR preserved (billing resumes after pause)
DowngradeDifference between old MRR and $0 (the full lower-plan MRR is saved)
DiscountDiscounted MRR preserved (full MRR minus discount amount)
ExtensionProjected MRR if the subscriber converts after the extended trial

Dashboard Analytics Views

Cancel Flow Overview

The main Cancel Flows dashboard shows a summary of all flow activity:

  • Total sessions — Number of cancel flow sessions started in the selected period
  • Save rate — Percentage of sessions that ended with a save
  • Revenue saved — Total MRR preserved through saves
  • Top cancellation reasons — Most common reasons from survey responses

Session Detail

Click into any session to see the full journey:

  • Each step the subscriber saw
  • Their response at each step (survey answer, offer accepted/declined)
  • The offer presented and its configuration
  • Final outcome (Saved or Churned)
  • Timestamp for each interaction

Feedback Analysis

The Feedback view aggregates survey data across all sessions:

  • Reason distribution — Bar chart showing how often each cancellation reason is selected
  • Reason vs. outcome — For each reason, what percentage of subscribers were saved vs. churned
  • Reason vs. offer type — Which offer types were shown for each reason and their acceptance rates
  • Free text responses — Searchable list of open-ended feedback

Trend Analysis

Track metrics over time to identify patterns:

  • Save rate trend — Weekly or monthly save rate to spot improvements or regressions
  • Revenue saved trend — Cumulative revenue saved over time
  • Offer mix — How the distribution of accepted offer types changes over time
  • Cancellation reason trends — Shifts in why subscribers are leaving (e.g., a spike in "too expensive" after a price increase)

Using Data to Optimize

Improve Low-Performing Offers

If a specific offer type has a low acceptance rate:

  1. Check the offer against the cancellation reasons that trigger it — the mapping may be wrong
  2. Adjust the offer value (e.g., increase discount percentage, extend pause duration)
  3. Improve the copy — test different headlines and descriptions
  4. Consider replacing the offer type entirely (e.g., switch from downgrade to discount for price-sensitive segments)

Refine Survey Questions

If "Other" is a top cancellation reason:

  1. Review the free text responses for common themes
  2. Add new multiple choice options for recurring themes
  3. Remove options that are rarely selected

Test Flow Variations

Create multiple cancel flows and run them at different times to compare performance:

  1. Build a variant flow with different offers or different copy
  2. Activate it for a set period (e.g., 2 weeks)
  3. Compare save rates and revenue saved against the previous flow
  4. Keep the better performer and iterate

Exporting Data

Export cancel flow data for deeper analysis:

  1. Navigate to Cancel Flows > Sessions or Cancel Flows > Feedback
  2. Apply any filters (date range, outcome, cancellation reason)
  3. Click Export and choose CSV or JSON format

Exported data includes all session fields, survey responses, offer details, and outcomes.

Next Steps

  • Building Flows — Create or modify your cancel flows based on insights
  • Survey Steps — Refine your cancellation surveys using feedback data
  • Discount Offers — Adjust discount offers for better performance

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