Weather has a huge influence on human behavior – and it shouldn’t come as a surprise that it also influences consumers’ buying decision.
Weather is the single most important external factor in how businesses perform, and affects about $500 billion of annual commercial activity among Fortune Global 500 companies.
According to a paper on “The effect of weather on consumer spending”, exposure to sunlight increases our willingness to spend money by up to 56%:
And when temperature changes, just one degree is enough to make a difference on sales:
Weather and advertising
Advertising is the art of influencing consumers’ buying decisions and as such its impact is maximized when it is aligned to weather trends. While the technology to run weather-based campaigns is not mainstream yet, retailers are experimenting with it and the results are extremely encouraging.
Case study: Subway
Subway – a sandwich chain – boosted store traffic 31% by changing its ads to correspond with weather shifts. By using artificial intelligence (AI) software with a real-time signal-based targeting tool, they created dynamic ads for a foot-long sandwich promotion based on weather patterns.
The effort generated a 53% reduction in campaign waste by making 7.9 million impressions more relevant to the current weather. That meant, for example, avoiding ad placements for hot sandwiches during heat waves that blanketed much of the country last summer.
The results are stunning and show how companies are starting to leverage AI and weather to automate their ad spend and make real-time intelligent adjustment that have a real impact on a company bottom line.
The Subway case study shows that weather has an influence at the business macro level. However, during our data analysis work for the EW-Shopp project, we learnt that it also interacts with the specificity of a location at a micro level.
Measurence’s business case uncovered an interesting insight: based on the physical location, people react differently to the same variation in weather conditions.
In Northern and central Italy, and specifically in Milan, Rome and Ravenna, the behavior of people that are looking for a new car at a dealer location is different than in Southern (Palermo and Naples).
Measurence found out that in the south, people prefer to visit the dealer locations during the rainiest days of the year rather than during extremely sunny days. However, in Northern locations, we did not find any dependencies related to the number of visitors and precipitations.
We plan to investigate these dependencies in more details expanding our study to more location across Italy and adapt our prediction models based on those new learnings.
Measurence is a location intelligence company. Our mission is to transform offline human behavior into actionable insights and automate decision-making.