POURCASTER EVENT BEVERAGE FORECASTING

PourCaster™

Predict. Pour. Perfect.

PourCaster demo
AI intensity · ZIP/state weather · inventory planning
← Back to PourCaster.com

Event inputs

City / ZIP code

Start date

End date

Start time

Sales hours per day

Baseline history

Baseline year

Use any of the last five event years as the baseline.

Known year-over-year trend

Optional annual trend % from older baseline to current event.

Baseline attendance

Alcohol tickets

Beer gallons

White wine 9L cases

Red wine 9L cases

Rosé wine 9L cases

Sparkling wine 9L cases

Spirits 9L cases

Other / RTD 9L cases

Commodity variety

Premium / craft beer share %

Split total beer into premium/craft vs core beer for supplier planning.

Non-alcoholic beer share %

Optional NA/low-alcohol beer allocation.

Spirits premium share %

RTD / seltzer variety count

Wine resolution

Beer resolution

Specific products

Editable product names flow into category cards and the supplier shopping list. Use commas or line breaks.

Core beer labels

Premium / craft beer labels

NA / low-alcohol beer labels

RTD / seltzer labels

White wine labels

Red wine labels

Rosé wine labels

Sparkling wine labels

Well / standard spirits labels

Premium spirits labels

Projection assumptions

Population growth vs last year

Percent. Later: fetched by city/ZIP.

Event momentum adjustment

Marketing, venue change, ticket trend, etc.

Weather outlook

Event type

Alcohol format

Food availability

Day/time profile

Intensity override

Drinking intensity will be predicted from event type, tickets per attendee, sales hours, day/time, food, format, and weather.

Back-stock insurance

Percent added on top of base forecast.

Safety round-up

Next options

Forecast confidence

Supplier return policy

Expected high temp °F

Rain probability %

Weather lookup not run yet. Uses Open-Meteo geocoding and forecast data when available.

Weather sources to check

National Weather Service / weather.gov Open-Meteo Commercial provider placeholder

Projected attendance

—

Waiting for inputs

Demand lift

—

growth + weather + intensity

Back-stock

—

insurance buffer

Runout posture

—

forecast stance

Projection notes

Run the projection to see assumptions and planning notes.

Supplier shopping list

Run the projection to generate a supplier-ready order list.

Next legitimate data tasks

Population growth

For v2, fetch city/ZIP year-to-date or latest annual population/visitor proxy and compare against last year's event period. Use it as one attendance-lift factor, not the only factor.

Weather confidence

For v2, blend 3 sources — NWS/weather.gov, Open-Meteo, and a commercial provider — then map temperature/rain/storm risk into commodity-specific demand changes.