Your CS team spots churn after the customer has already decided to leave—because manual risk scoring is too slow to catch the early signals.
Churn doesn't happen overnight. It leaves breadcrumbs: a drop in feature adoption, a spike in support complaints, a quiet quarter with no expansion conversations. The problem is your CS team is drowning in accounts and can't watch all of them at once. This workflow automates the watching part. It ingests signals from your product (usage metrics, feature adoption), your support system (ticket volume, sentiment), and your CRM (last interaction date, expansion pipeline status), then scores each account on a simple risk scale: high, medium, low. When an account hits high-risk thresholds—say, 40% drop in DAU over 30 days, or three support tickets in two weeks with negative sentiment—the system doesn't just flag it. It triggers a playbook: a pre-built sequence of actions tailored to that risk type. A usage-drop playbook might route to the product specialist. A support-sentiment playbook might escalate to the account owner with a template for a check-in call. A contract-expiry playbook might surface the renewal date, expansion history, and a list of at-risk features. Each playbook includes context: why the account is flagged, what changed, who owns it, and what the CS team should do first. No hunting through dashboards. No guessing whether to call or email. The system has already decided the priority and the next move. The workflow runs on a schedule (daily or weekly, depending on your churn velocity) and updates scores as signals change. Accounts that improve drop back to medium or low. Accounts that worsen escalate. CS teams get a ranked list every morning: 'Here are your 12 high-risk accounts this week. Here's what to do about each one.' The human approval gates matter here. You don't want the system calling every customer who had one quiet week. You don't want it triggering playbooks for accounts that are already in an active renewal conversation. So the workflow includes checkpoints: CS can mark accounts as 'in-progress,' 'false alarm,' or 'monitor only,' and the system respects those flags. It also requires a human to confirm high-risk escalations before they hit the team's inbox, so you avoid alert fatigue. The result: churn becomes predictable and preventable. Your CS team moves from reactive firefighting to proactive intervention, with a clear playbook for every risk type.
Trigger: Daily or weekly schedule (configurable). Runs at off-peak hours. Recalculates risk scores for all active accounts based on the latest signals from product, support, and CRM. Flags new high-risk accounts and updates existing risk scores.
Pull account records from CRM, product analytics, and support systems. Normalize data into a unified schema (account ID, ARR, renewal date, last login, support ticket count, NPS). Handle missing fields with defaults or null flags.
Apply weighted scoring logic: usage decline (30%), support escalation (25%), engagement drop (20%), payment friction (15%), contract age/expansion opportunity (10%). Output risk score 0–100 and risk tier (green/yellow/red). Label model assumptions and confidence intervals.
Bucket accounts into playbook categories: high-risk (score 70+, red), medium-risk (50–69, yellow), low-risk (below 50, green). Assign playbook template based on risk driver (e.g., 'usage-decline' playbook vs. 'payment-friction' playbook). Flag expansion opportunities separately.
Retrieve account owner, executive sponsor, primary contact, recent interactions, known issues, and expansion potential. Identify internal stakeholders (sales, product, support) who should be looped in. Prepare one-pager summary for CS team.
CS manager or ops lead reviews flagged accounts, validates risk score, and approves playbook assignment. Option to override risk tier, reassign playbook, or mark account as false positive. Approval required before outreach triggers.
Launch playbook workflow based on approved risk tier and type. Playbook includes: templated outreach email, check-in call script, executive business review offer, product training session, and escalation path. Assign tasks to CS owner with due dates.
Send templated email or SMS to primary contact with personalized context (usage insights, specific pain points, renewal timeline). Include clear CTA (schedule call, join webinar, request demo). Log send event and track open/click metrics.
CS owner follows playbook steps: conduct discovery call, identify unmet needs, present solution roadmap or expansion offer, escalate to product/sales if needed. Document findings and next steps in CRM. Update account health score based on conversation.
Track task completion, email engagement, call completion, and customer response sentiment. Auto-escalate if no response after 7 days. Flag if risk score improves (usage increases, support issues resolve) to adjust playbook intensity.
At renewal decision point, log outcome (renewed, churned, paused, expanded). Record playbook actions taken, customer objections, and resolution. Use data to refine risk model and playbook templates for future cycles.
1. **Define your risk signals.** Decide which metrics matter most: DAU/MAU drop, feature adoption decline, support ticket volume, ticket sentiment, days since last login, contract renewal date, expansion pipeline status. Weight them by impact (e.g., 40% product usage, 30% support health, 20% engagement, 10% contract timing). 2. **Set thresholds.** Example: high-risk = 40% usage drop in 30 days OR 3+ support tickets in 14 days with negative sentiment OR 60+ days since last login. Medium-risk = 20% usage drop OR 1-2 support tickets OR 45+ days inactive. Adjust for your product and churn patterns. 3. **Connect your data sources.** Integrate your product analytics (Amplitude, Mixpanel, custom events), support system (Zendesk, Intercom, Freshdesk), and CRM (Salesforce, HubSpot). Ensure data freshness: product events within 24 hours, support tickets within 6 hours, CRM updates within 12 hours. 4. **Build playbooks.** Create 3-5 playbooks for your most common churn patterns: Usage Decline, Support Escalation, Expansion Stall, Contract Renewal, Competitor Activity. Each playbook includes: risk description, recommended action, template message, next steps, and escalation path. 5. **Set approval gates.** Require CS lead sign-off on high-risk escalations before they route to the team. Allow CS to mark accounts as 'in-progress' or 'false alarm' to prevent duplicate outreach. Exclude accounts in active renewal or expansion conversations. 6. **Configure notifications.** Daily digest email to CS leadership with ranked high-risk list. Slack alerts for critical escalations (e.g., accounts with >60% usage drop). Weekly summary of playbook execution and outcomes. 7. **Test and iterate.** Run in 'monitor mode' for two weeks. Compare system flags against your actual churn. Adjust thresholds and weights. Once accuracy hits 70%+ precision on high-risk flags, move to live playbook routing.