Tiered churn intervention
Scores churn risk daily and routes each band to email, SMS, push, or Slack: nurture content at low risk, personalized messages at medium, and CSM or founder outreach at high and critical.
Authored by Sid Chaudhary
Founder & CEO at Intempt
Agentic workflow
Coming soon7 steps Blu runs end to end. It drafts a plan and nothing runs until you approve it.
- 1
Score churn risk daily
Coming soonBlu builds a step
- 2
Take everyone above 30
Coming soonBlu builds a step
- 3
Write an email per band
Coming soonBlu builds a step
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Catch them when they log in
Coming soonBlu builds a step
- 5
Recommend what keeps people
Coming soonBlu builds a step
- 6
Treat each band differently
Coming soonBlu builds a step
- 7
See if the bands hold up
Coming soonBlu builds a step
About this recipe
When to use it
A one-size-fits-all churn save wastes a CSM's time on low-risk users and under-reacts to critical ones. This routes each risk tier to a different intervention, from nurture content up to an exec-sponsor task.
What it delivers
Uses a predictive churn-risk AI attribute to route users to one of four intervention tiers - low gets nurture content, medium gets personalized in-app plus email, high gets a CSM task plus recommendation surface, critical gets an agent handoff plus exec-sponsor task.
How you prompt this
Describe the outcome in your own words and Blu Agent maps it to this recipe, or run it by name. It drafts a plan first and nothing runs until you approve it.
Tell Blu Agent what you want
“Scores churn risk daily and routes each band to email, SMS, push, or Slack: nurture content at low risk, personalized messages at medium, and CSM or founder outreach at high and critical.”
recipe.md preview
Built from the published catalog. Blu Agent's full step prompts load in your workspace when you run it.
Inputs & outputs
What the recipe needs before it runs, and what it leaves in your workspace.
Inputs
- Nothing declared beyond an Intempt workspace. Blu asks for anything else it needs as it goes.
Outputs
How the recipe runs
Blu follows the steps in order and shows you each one before anything goes live.
- 01Score churn risk dailyCreate an AI-derived attribute 'churn_risk_score' on the User object, refreshed daily. Inputs: engagement velocity (sessions trend over 30/14/7 days), feature usage decay, support sentiment trajectory, billing-status signals, peer-cohort churn patterns, account-level usage (for B2B). Output: numeric 0-100 with tier label (low (0-29) / medium (30-59) / high (60-79) / critical (80-100). NOT binary at-risk-or-not) the nuance is the point: medium and high get different treatments. Refresh on every significant behavioral event so a sudden engagement drop is caught fast.
- 02Take everyone above 30Build a parent segment 'Churn risk - paying users' capturing all paying users with churn_risk_score >= 30. Implicitly partitioned by tier through the attribute. Excludes users in the first 14 days (early signals aren't reliable yet) and users already in active save flows (no double-intervention). Use the result of "Score churn risk daily".
- 03Write an email per bandGenerate per-tier email content. Medium tier: educational content matched to underutilized features that drive retention in their cohort + personalized 'pick up where you left off' deep-link. Tone: helpful, not alarmed. High tier: urgent value reinforcement, CSM availability signal, specific use-case help offer ('Want a 15-min walkthrough on [feature]?'). Critical tier: founder/CEO personal letter ('I noticed your account hasn't been used much: anything we can do?'), with direct calendar link and concrete asks. Send-from: success@ for medium, named CSM for high, founder/CEO for critical. Use the result of "Score churn risk daily", "Take everyone above 30".
- 04Catch them when they log inThis step builds a page. Generate in-app messages for high-tier users when they DO log in (rare and precious moments). Format: contextual banner referencing their most-likely-success-path ('Most users in your segment succeed by trying [feature] (want a 60-second walkthrough?'). For critical-tier users on rare logins: a personal-touch interrupt) full-screen modal from the CSM or founder offering a 1:1 call. Never blanket: only when AI signal is strong. Use the result of "Score churn risk daily", "Take everyone above 30", "Write an email per band".
- 05Recommend what keeps peopleConfigure a recommendation surface specifically for high+critical tier users: surfaces underutilized features that THIS user's cohort uses successfully but THIS user has not adopted (the 'features-that-stick-users' pattern). Renders in-app on dashboard, in email content blocks, and on personalization slots when the user does visit. The recommendation logic prioritizes features with high retention-correlation in this user's segment. Use the result of "Score churn risk daily", "Take everyone above 30".
- 06Treat each band differentlyBuild a tiered journey wired to the churn-risk segment. Branch on churn_risk tier at entry AND re-evaluate weekly: LOW tier (light-touch nurture email at Day 7 (no urgency, just value content). MEDIUM tier) Touch 1 email Day 0 (helpful tip), Touch 2 in-app at next login (deep-link to retention feature), Touch 3 email Day 7 with recommendation surface highlighting cohort-success features. HIGH tier: Touch 1 email Day 0 from CSM with offer of help, in-app urgent banner on next session, CSM task created same-day. CRITICAL tier: within 4 hours: founder/CEO personal email + agent handoff offering 1:1 call + urgent CSM task + executive-sponsor task. Tier RECOMPUTED weekly: users de-escalate (engagement returned) exit gracefully; users escalate get tier-appropriate next-touch. Exit on: churn_risk drops below 30 for 14+ days (recovered: log retention_win), Subscription canceled (handoff to post-cancel-winback), or unsubscribe. Use the result of "Score churn risk daily", "Take everyone above 30", "Write an email per band", "Catch them when they log in", "Recommend what keeps people".
- 07See if the bands hold upCompose a tiered churn intervention dashboard: distribution of users across tiers (low/medium/high/critical) per week (leading indicator of book-of-business health, tier-level save rate (% of users in each tier who exit risk vs. churn) proves tiered strategy works), critical-tier CSM response SLA (target: <4hr for human-touch start), ARR-weighted save value by tier, and tier-migration tracking (high to medium = success, medium to high = early warning). Compare model accuracy: predicted churn vs. actual churn at 30/60/90 days. Use the result of "Score churn risk daily", "Take everyone above 30", "Write an email per band", "Catch them when they log in", "Recommend what keeps people", "Treat each band differently".
Install Intempt and run it
- 1
Sign up
Create a free Intempt workspace.
- 2
Connect your data
Add the sources this recipe reads from.
- 3
Ask Blu
Type /predictive-churn-tiered-intervention in Blu once this recipe is live there.
- 4
Review and approve
Blu builds each step and waits for your OK before anything goes live.
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