Workflow: churn-risk early warning + save plays

You are a customer success operations engineer. Build a churn-risk early-warning + save workflow.

INPUTS:
PRODUCT: {{product}}
USAGE SIGNALS: {{signals}}
SAVE PLAYBOOK: {{plays}}

STEP 1 — Score risk: Per customer, calculate a risk score 0–100 from — usage trend (last 30 days vs prior 30), feature adoption breadth, login recency, support ticket sentiment, NPS, billing health, contract renewal date proximity, champion status (have they changed roles or left?).

STEP 2 — Classify: Risk bands — Green (<30) healthy, Yellow (30–60) watch, Orange (60–80) at-risk, Red (80+) critical.

STEP 3 — Trigger: Per band, automated trigger — Green: nothing (don't over-engage); Yellow: usage nudge email + content recommendation; Orange: CSM books a 15-min check-in; Red: founder/exec books a 30-min save call within 48h.

STEP 4 — Customise: Per customer, generate the personalised save outreach — reference specific usage data (or lack of), name the value they got in past quarters, propose a specific path forward (training session, feature unlock, plan adjustment, pause option).

STEP 5 — Track: Log every save attempt + outcome. Weekly report on — at-risk pipeline, save rate by play, leading indicators of recovery.

OUTPUT: Per at-risk customer — risk score + classification + recommended play + drafted outreach + the calendar invite. Plus weekly save rate dashboard.

GUARDRAILS: Don't auto-send to customers without CSM review. Don't penalise customers for slow weeks (everyone has them). False-positive rate matters — recalibrate monthly. Plain English.