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Weather Sensitivity: Analytics For Outerwear

By: David Frieberg

In previous articles I have used a measurement called Weather-Driven Demand (WDD) to illustrate just how much outerwear category sales shift each year due to changes in the weather. Calculated from detailed analyses of historical sales and weather data, WDDs isolate the impact that the weather alone has on consumer demand, compared to the prior year, by market, and by time period. For example, the WDD for November 2014 was positive in southern markets like Miami (+22% WDD), Charlotte (+16%), Atlanta (+15%) and Tampa (+9%) where temperatures were much colder than the year before.

These weather-driven demand numbers are used by both retailers and suppliers to understand past performance, track sales impacts during the selling season and to plan for the following year. Diving a little deeper into the analytics, one can look at weather sensitivity numbers which provide additional insights into how Mother Nature’s effects on consumer purchasing varies through the season and across locations.

WDD numbers incorporate a year-on-year perspective, quantifying the delta in demand for a category based on the variance between last year’s weather conditions and the current year’s weather conditions. Weather sensitivity calculations don’t provide a comparison to the previous year; but they do form the foundation for WDDs by identifying the percentage of a category’s total sales volume that is affected by the weather on average in a given market for a given time period. With weather sensitivity analytics, businesses can understand in which weeks and months consumers in various markets are most (or least) responsive to changes in weather.

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