Study shows E-commerce sales can be significantly affected by the weather.

Chain Store Age reported on a study by Adobe Analytics that says, “weather events will add an additional $13.5 billion to U.S. e-commerce in 2023.” The article (“Study: Weather is a bigger e-commerce driver than Cyber Monday”) highlighted several high-level findings regarding online consumer purchases and certain weather conditions.

Regarding rain, Adobe reports that “the effects of rain are amplified on weekends, when the boost rain provides to e-commerce nearly doubles.” The analysis also revealed that “the impact of rain on e-commerce is strongest in the fall, when even a drizzle will boost e-commerce by around 5%.”

When it comes to wind, Adobe found that “online shopping increases 3.5%.” when winds are 15-20 MPH. However, windier conditions appear to distract consumers as attention may shift to potential negative impacts on people and property. Adobe pointed out that, “wind speeds in excess of 30 MPH generate a steeper 22.1% decline in online shopping.”

The findings are a good reminder to retailers and consumer-focused businesses about the omnipresent and often very large effects that changes in the weather have on shopper behavior and spending.

However, to combat lost sales due to out-of-stocks, reduce inventory costs such as markdowns or waste, or effectively target digital ads to optimize results, companies really need access to detailed weather-driven demand calculations. National or regional numbers will not suffice and lower level (category or product vs. total sales) are almost always needed. One size does not fit all when it comes to the weather’s impact on commerce.

Planalytics weather-driven demand metrics isolate and precisely calculate the sales impacts on a granular level so businesses can systematically address opportunities and risks. Consumers in every zip code respond uniquely to the same weather conditions as do different products and services. These demand responses also change throughout the year (a 68-degree day in February does not generate the same response as a 68-degree day in April), vary based on channel (online vs. in-store; mall-based locations vs. outlet centers, etc.), and can differ across various demographics (women vs. men, teenagers vs. seniors, etc.)

Check out the new Playbook “Profiting with PredictiveWeather-Driven Demand Analytics” to learn how Planalytics transforms the countless intersections of weather conditions, sales, channels, time, geographies, and more for specific products or services into analytics that are easily actioned to capture financial benefits. The analytics are easy to incorporate into existing business processes and technologies, from ERPs to SaaS solutions to Machine Learning forecasting platforms.