Predicting the reorder before it lapses.
Plan inventory a cycle ahead
At-risk routed to win-back
Forecast, risk, subscription health
The problem.
For a replenishment brand, the whole model rests on customers coming back on schedule. But planning was reactive: inventory got ordered by looking backward, and churn showed up as a cancellation, not a warning. Stockouts and dead stock both cost money, and win-back always arrived a step too late.
The approach.
I built a model that forecasts reorders a cycle ahead and scores every subscriber for churn risk each week. Three views tie it together: a forecast view comparing predicted against actual reorders, a churn-risk view that segments members from healthy to lapsing, and a subscription health view with the retention curve and net revenue retention.
The outcome.
Reordering became proactive and win-back got ahead of the cancel button. Inventory is planned against a forecast that tracks reality closely, and at-risk subscribers are flagged and routed into a win-back flow while there is still a subscription to save, so fewer stockouts, less dead stock, and lower avoidable churn.
Explore the dashboard.
INTERACTIVE SAMPLE · Illustrative data, not client figures. Switch tabs for reorder forecast, churn risk, and subscription health.
If your model depends on reorders but planning is reactive, I will forecast demand and flag at-risk customers before they lapse. One slot open for Q3 2026.