Attrition and Return-Rate Early Warning System - Biotech Company
Attrition detection system allowed customer success to intervene within minutes instead of days which decreased attrition rates by -36% and decreased product returns by -14%, protecting an eight‑figure ARR slice.
[ CHALLENGE ]
Scaling a regulated medical device takes more than accurate algorithms. The hidden drain on revenue was silent churn and preventable returns driven by fragmented data and slow, reactive support. Three core challenges stood out:
Fragmented signals across systems such as AWS and Salesforce prevented a unified picture across more than 10,000 patients resulting in missing early warning signs of attrition and return risk.
Slow time to action resulted in support interventions routinely happening days after the first risk indicators, which meant issues had already compounded into low usage or a return.
Lack of predictive flags forced customer success teams to triage reactively rather than work a prioritized, evidence‑based queue of at‑risk patients.
[ SOLUTION ]
We built a cross‑system attrition risk pipeline to turn scattered events into timely action. Here are three keys to how it was delivered in 8 months:
Unified Telemetry and CRM Records for a Single Source of Truth
We joined AWS device telemetry with Salesforce account histories to create a modeling‑ready view of patient behavior and service touch points across the entire population.Supervised Attrition Modeling with Actionable Risk Flags
We trained an attrition model and converted scores into clear risk flags. These flags were piped directly into HubSpot so customer support could see who was trending risky and why, rather than guessing from raw logs.Closed‑Loop, Hour‑Scale Interventions
By embedding the risk flags into daily workflows, customer success moved from reactive cases to proactive outreach within hours instead of weeks, and every outreach fed outcomes back for continuous improvement.
[ RESULTS ]
-36%
Decrease in device usage attrition
-14%
Decrease in product returns
< 30min
Response time from customer support
