Back to all work
Revenue Forecasting Engine
Per-location revenue forecasts plus a pricing optimizer that shows the upside.
The challenge
Marina and boat-rental operators price by gut and last year's numbers, which leaves money on the table and gives no real view of what each site should earn.
What we built
A Python pipeline ingests raw booking and boat-type CSVs, cleans them, and adds weather and census context per location. A two-stage model (a global XGBoost model plus per-location Prophet models) produces 12-month forecasts with confidence bands, and a pricing and fleet-mix optimizer recommends monthly price and mix changes on top.
The result
Each location gets a defensible baseline forecast plus an optimized one showing the revenue uplift from smarter pricing, delivered as per-site reports with a network-wide summary.