Churn prevention emails

Users don't just churn, they show signals first: decreased usage, failed logins, support tickets. Email reaches out before cancel.

Triggers

• Haven't logged in 14 days
• Feature usage dropped 50%+
• Downgrade or cancel attempt

Tactics

• 'We noticed you haven't been back' outreach
• Offer help / demo
• Case study of success
• Specific save offer for downgraders

Measurement

% of at-risk users retained.

What to do with this

• Build the 4 critical at-risk email flows before broader churn optimization, they catch the biggest recoveries
• Trigger at-risk emails automatically from usage signals, manual detection misses most churns
• Include a human option in the save flow ("reply to get on a call"), high-value accounts warrant human intervention
• Track recovery rate per signal, different at-risk signals have different save potential and deserve different effort
• Run win-back 60-90 days after churn, some churners return after the circumstances that caused them to leave pass