The Problem

Our churn rate hit 15% in Q4 2024. At that rate, we'd lose our entire customer base in 7 months. We needed to act fast.

Week 1: Identify Churn Signals

Step 1: Track User Behavior

We identified 5 signals that predicted churn within 30 days:

• No login for 7+ days
• Zero API calls in 14 days
• Support ticket unresolved >48 hours
• Failed payment attempt
• Downgrade from paid to free

Step 2: Segment At-Risk Users

We created 3 risk tiers:

High Risk (3+ signals)

Immediate intervention needed

Medium Risk (2 signals)

Automated email sequence

Low Risk (1 signal)

Monitor closely

Week 2: Build Retention Flows

Flow 1: The "We Miss You" Email

Triggered after 7 days of inactivity:

Subject:

"We noticed you haven't logged in..."

Body:

• Personalized with their last action

• 1-click login link

• Offer: 30-min onboarding call

Result:

23% reactivation rate

Flow 2: Failed Payment Recovery

3-email sequence over 7 days:

Day 1: "Payment failed - Update card"
Day 3: "Don't lose access - 4 days left"
Day 7: "Final notice + 50% discount"

Result:

67% payment recovery

Flow 3: Proactive Support

For users with unresolved tickets:

• Slack notification to founder
• Personal video walkthrough
• Offer to hop on a call

Result:

89% issue resolution

Week 3-4: Optimize & Scale

What We Learned

Timing matters: Reaching out at day 7 is 3x more effective than day 14
Personalization wins: Generic emails had 4% open rate, personalized had 31%
Founder touch: Personal outreach from founder had 78% response rate

The Tools We Used

SaaS Radar

Churn prediction & survival scoring

Customer.io

Automated email sequences

Stripe

Payment recovery webhooks

Slack

Real-time alerts for high-risk users

Want to Reduce Your Churn?

Get AI-powered churn prediction + automated retention playbook

Start Free Trial