Domo Analytics · Technology · Austin, TX · 10 weeks
Customer churn prediction model deployed to production in 10 weeks
A Series B analytics startup struggled to deploy their churn prediction model because their data pipelines kept breaking. We overhauled their data infrastructure, fixed the pipeline issues, and got the model running in production within 10 weeks. In three months, the model flagged $2.6M in at-risk ARR, helping the customer success team retain 340 accounts they would have otherwise lost.
Challenge
The data science team created a churn model that predicted correctly 78% of the time in tests, but it never went live. The data pipeline broke multiple times a week because CRM and product usage data kept changing formats. Without reliable data, the customer success team couldn’t identify which accounts were at risk.
Outcome
The model went live in week 10. Within three months, it flagged $2.6M in at-risk ARR. The customer success team used these alerts to save 340 accounts that data showed were likely to churn. The pipeline has operated continuously for 18 weeks without issues.
Results
- $2.6M At-risk ARR identified in Q1
- 340 Accounts retained in first quarter
- 78 to 84 correct per 100 Model accuracy improvement
- 10 wks From rebuild to production
Our data science team built a good model, but the pipeline kept failing, so we couldn’t put it to use. Thinklytics fixed the pipeline, improved the model, and got it running in production within 10 weeks. We retained 340 accounts in the first quarter alone.