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Feature Drop-Off Detection

Reinforcing value when users disengage from previously adopted features

Julie Zehntner avatar
Written by Julie Zehntner
Updated over 2 weeks ago

Summary

This play detects when users disengage from previously adopted features. By tracking event-level drop-offs, you can intervene early and reinforce product value.

Why this works

  • Surfaces disengagement tied to specific workflows.

  • Turns drop-off into an outreach trigger.

  • Prevents silent churn by restoring product relevance.

Goal

For the reader: Spot and respond to event-level drop-offs before they escalate.
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For the company: Retain at-risk users by reviving usage of sticky features.
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Accoil Signal

(1) Primary signal

  • Event (feature) with negative Adoption Change %

  • Feature was previously used

  • Account = Active or recently active

(2) Additional insights

  • Power user or admin role

  • Previously adopted multiple features



Action steps

1. Identify Event Drop-Off Trends + Impacted Accounts

  • Go to Engagement Profile β†’ Events

  • Sort by Adoption Change %

  • Filter & segment accounts with sharp declines on core events

2. Trigger Reactivation Content

  • Use connections to send insights to the tools your team uses

  • Send targeted messaging with help docs, walkthroughs, or examples

  • Use CRM or Connections to personalize delivery by role or feature

3. Offer Enablement Touchpoints

  • Invite to short refresh sessions or async demos

4. Monitor Recovery

  • Use account activity views to track whether usage resumes

  • Tag successes for follow-up

  • Escalate flat accounts to CS for deeper retention support



Supporting metrics

Metrics

How to measure in Accoil

Renewal Rate

% of eligible accounts that renew

Contract Expansion Rate

% that increase value at renewal

Post-Renewal Health

Usage and retention trends post-renewal



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