Price Intelligence & Revenue Leakage Detection

Revenue leakage is a strange kind of problem: nobody decides to lose margin. It accumulates quietly through unauthorized reseller discounting, MAP violations, and pricing drift that nobody's watching closely enough to catch in real time. By the time it shows up in a quarterly revenue review, it's been happening for months.

I built a monitoring system that surfaces pricing anomalies and unauthorized discounting across marketplaces as they happen, rather than as a retrospective finding, so a pricing or revenue team can act on leakage before it compounds, not just document it afterward. Reliable anomaly detection depends entirely on the data infrastructure underneath it — the same kind of collection and validation pipeline described in SARA.

A detection system that cries wolf trains its own users to ignore it.

That's the real constraint underneath anomaly detection: a threshold tight enough to catch real leakage early is also tight enough to flag every legitimate flash sale and seasonal discount. Distinguishing a genuine violation from ordinary pricing activity matters as much as catching the anomaly itself: an alert nobody trusts gets ignored within a week, and an ignored alert is worse than no alert.

The underlying principle holds anywhere alerting is involved: the goal was never more alerts. It was alerts a revenue team actually trusts enough to act on.