Live demo
14 series in. 4 alerts out.
One unit-economics book, four customer segments, 60 days, 14 series. On day 42 one segment stopped paying for itself. Revenue grew through the entire window, orders and average order value never moved, and blended gross margin stayed inside its normal band. Find the segment.
Every number on this page is computed in your browser right now, by the same CUSUM and Bayesian changepoint code that runs in production. Nothing here is a screenshot.
The comparison that matters
Against the rule most teams actually ship
The standard configuration is a percentage or sigma threshold against a trailing mean, evaluated per metric. Run it over the exact same 14 series and count what lands in the channel.
The false-alarm count is not a judgement call. The incident was injected at a known index, so every naive alert before that index is wrong by construction.
What the engine found
Detection run
| Metric | Trend | Baseline | Now | Change | Confidence | Method |
|---|---|---|---|---|---|---|
Contribution margin per order segment=resellers | $18 | $12 | −34.6% | 99.9% | CUSUM | |
Shipping cost per order segment=resellers | $7.36 | $11 | +49.4% | 99.9% | CUSUM | |
Support cost per customer segment=resellers | $2.22 | $4.03 | +81.3% | 99.9% | CUSUM | |
Refund rate segment=resellers | 3.14% | 7.82% | +150% | 99.9% | CUSUM |
Show your work
Contribution margin per order · segment=resellers
Baseline mean μ = 0.0012 and σ = 0.0386, both computed from the first two thirds of the day-over-day percentage changes. The slack k = 0.0193 is half a sigma, and the decision boundary h = 0.1544 is four. The accumulator runs on percentage changes rather than raw levels so a healthy growing series cannot drift across the boundary on its own.
alert if |Δ| > 2.5σ vs 7-day mean fired 7 times across this one metric, including 2 before anything was actually wrong. The statistical pipeline sent one message, on the day the regime actually changed.
What lands in Slack
One message, with the work already done
- 1.Pull reseller orders since Aug 10 and check discount code usage against the partner allow list.
- 2.Break shipping cost per order by destination zone to confirm the mix shift.
- 3.Recompute reseller CAC payback with the new contribution margin before renewing the partner terms.
The written cause is generated only after the statistics confirm the change. The model never decides whether something is an anomaly — it explains one that has already been established. Getting that order backwards is how these products hallucinate.