Data signals
The signals behind every forecast
By analysing various data points such as weather patterns, local events, traffic flows, seasonality trends, holidays and schedules, we help grocery stores optimise their inventory.
01
Weather patterns
Temperature, precipitation and sunshine shift both what and how much people buy.
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02
Local events
Concerts, sports, markets and festivals change footfall around a store.
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03
Traffic flows
Movement of people and vehicles past a store shapes its demand curve.
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04
Seasonality trends
Weekly, monthly and annual cycles in sales history.
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05
Holidays
Public and religious holidays and the days around them.
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06
Schedules
Recurring calendars such as school terms, paydays and opening hours.
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No single signal explains demand. Together they explain a lot.
Each signal on its own is a partial story. A warm day matters more on a weekend; a concert matters more for the store next to the venue; a holiday matters more when it creates a long weekend. Time series models can learn these interactions from history, which is why Chopp combines the signals rather than looking at each one in isolation.
Ready to cut away the waste?
Tell us about your store or chain, and we will show you how AI sales forecasting can help you order the right products in the right quantities.