Forecast total store revenue over a future horizon using TimesFM 2.5.

Returns a markdown summary and table with point forecast and 80% confidence band (q10-q90).

Forecast demand by product, collection, or SKU using TimesFM 2.5.

Returns a ranked markdown table showing projected demand per group
with confidence bands. When group_value is 'all', forecasts the top N
groups by historical volume.

Analyze a past promotion's impact vs baseline: revenue lift, order lift, AOV change, post-promo hangover, and product cannibalization.

Compare two time periods across revenue, orders, units, AOV, discount rate, and units per order.

Identify seasonal patterns in store data by day of week, month, or quarter.

Detect anomalous days where actual values fell outside expected forecast bands.

Compare 2-4 promotional scenarios with what-if forecasting.

Each scenario specifies a promo period and discount depth. Returns a side-by-side markdown table with revenue projections, confidence bands, and a recommendation for the best-performing scenario.