We are also embedded with all the major airlines. We provide data feeds to GM and Toyota, and to energy farms that might be interested in knowing how much wind they’re going to get this year, and to derivatives traders. WeatherFX uses the information that we have, and correlates that with marketer data.
AM: At its simplest, how does selling weather data actually work?
VS: Retail is an easy example. We have a retailer who may have a couple hundred or even a couple thousand stores across the U.S. We take data from each of those locations for each of their products, then we look at the information over time. We are looking to see what products start jumping off shelves when the dew point is X, the temperature is Y, and the rainfall is Z. What we give them is essentially: “Here are the 15 products you should be selling right now.”
We also overlay certain basic parameters on the weather. If it’s Friday, mothers are looking for what they’re going to be doing on the weekend. If they are looking to stock groceries for the weekend, and we know that the weekend is going to be gorgeous, how do we make it clear to them that they should be buying items for a barbecue?
AM: How much does weather really matter to companies?
VS: One of the fascinating things about weather is that it is so fundamentally local, and relevant to people in a very localized context. It’s hard to find another data set that does that—usually we run into some kind of data scarcity, where you only know whether one in every 10,000 people is interested in this product or that service. We have to make sure that we have the data-gathering apparatus, and not just today’s data—ideally we have historical data too, and then we have to build in the fact that the climate is changing as a whole.
As a company, we are beginning to take a much stronger approach to climate change, which you’ll see—we are the only ones who covered President Obama’s climate speech in its entirety. More-extreme weather is interesting to businesses, to insurance companies.
AM: Can you walk me through an example of how weather influences consumer behavior?
VS: There is a correlation for bug spray that’s kind of bizarre. We found that a very small difference in dew point made a huge difference in bug-spray orders. When the dew point changed, insects popped up, and everybody ran for the bug spray. Now that we’re working with bigger and bigger data sets—say, across a couple hundred thousand products, or a couple thousand retail locations—we are beginning to find a lot of situations like this.
Retailers have a fundamental knowledge of weather because of their supply chains. They know that it is impacting trucks, and how you get stuff from production locations to retail locations. But they hadn’t really taken that to marketing. For someone who came from a background where I sold more-esoteric data products, it has been a very humanizing experience to sell weather, because it’s something that everybody has a story around—it makes for a very personal tale.