Daily Revenue Reporting System
Replaced manual monthly revenue reporting with an automated daily system that classifies ARR movement across new business, upsell, cross-sell, downsize, and churn.
Problem
Revenue reporting at SalesRabbit was a manual, monthly process, leaving leaders with a stale, low-resolution view of revenue movement, customer activity, and business trends.
Full problem context, including the old process's cost and limitations, is pending and will be added here.
Approach
Built a daily revenue reporting system using subscription history data to classify ARR changes across new business, upsell, cross-sell, downsize, churn, and pending-churn activity.
Designed the supporting data infrastructure and logic to identify customer-level ARR changes by day, including the effects of quantity, discount, and list price changes.
Technical depth
- Daily classification logic for ARR movement: new business, upsell, cross-sell, downsize, churn, pending churn
- Customer-level, day-level granularity accounting for quantity, discount, and list price effects
- Built on subscription history data spanning billions of data points across thousands of datasets
- Pipeline architecture, data model, and specific tooling to be documented.
Outcome
Replaced manual monthly revenue reporting with automated daily reporting, giving leaders a more granular view of revenue movement, customer activity, and business trends.
Time saved versus the old manual process, and adoption across teams, is pending final numbers.