From forecasting the future to simulating it
Shadow starts by telling you what your users will do if you change nothing. The endgame is a living, owned model of your users' behavior you can query and stress-test — before you ship.
Shadow Preview: the do-nothing forecast
Read-only, segment-level behavioral trajectories from your own product data: the 7/14/30-day decline, the confidence band, the worst case, and the cost of inaction — backtested and calibrated. No PII, no writes.
- Segment-level forecasts
- Calibrated confidence
- Cost of inaction
What-If: counterfactual simulation
Move from "what happens if we do nothing" to "what happens if we ship this." Simulate a change — a gating tweak, a new flow, a pricing move — against your cohorts and see the projected impact, who's affected, and the second-order effects, before a single user is touched.
Owned models of your users' behavior
A persistent, continuously-updated behavioral model of your user base — grounded in real behavior, not synthetic personas — that compounds in value over time. Query it, stress-test decisions against it, and catch the risks that live in the counterfactuals no analytics tool can see.
We build in this order on purpose: forecasting earns the data relationship and proves calibration first — then simulation stands on a foundation you already trust.