Automated Expert Price Estimation for B2B Platform
Snapshot
Client
Ringo - B2B music licensing platform serving advertising
Problem
Unreliable pricing damaged customer relationships and created constant manual correction work
Solution
Automated pricing system combining formalized expert knowledge with AI reasoning
Results
Production-ready system delivering validated pricing in 2.5 minutes, fixed-price with zero operational disruption and full client ownership
Situation
Ringo's B2B music licensing platform helps media professionals price and clear music for commercials. Their pricing model was producing unreliable estimates that required constant manual corrections, eroding trust with customers and creating ongoing work for the team. The founder had years of market expertise, but this knowledge was intuitive and not systematized, making it impossible to scale reliably.
Challenge
Pricing complexity came from limited historical data with high deal variability and tacit founder expertise that hadn't been formalized. Standard approaches wouldn't work: pure machine learning would overfit sparse data, while pure rules couldn't capture market nuance. The solution needed to integrate seamlessly with their third-party-managed platform without causing disruption.
Solution
We captured the founder's tacit pricing knowledge through structured sessions and encoded it into decision logic. The system combines these formalized rules with AI reasoning to handle the full range of deal variables, e.g. song, artist, usage scope, territory, and media context. This hybrid approach works with limited historical data while maintaining consistency across standard deals and flexibility for edge cases.
Results
