Many of the recent advancements in marketing technology are predicated on the promise of an increasingly sophisticated ability to anticipate consumers’ actions and movements. But what kind of information can be depended upon to formulate the educated guesses that result in actual transactions? Of all the data that can be gathered and utilized, what works best to heighten the accuracy of these predictions? Some would argue it’s that most local of information that is all around us: the weather.
People have been checking forecasts via The Weather Company for more than three decades, and most of the company was acquired earlier this year by IBM, which saw the potential for its Watson Internet of Things division. Street Fight recently caught up with the firm’s EMEA Managing Director, Ross Webster (who will be a speaker at our upcoming LOCALCON conference in London next week), to talk about what makes weather data so valuable to businesses.
Obviously there’s no information that’s more local than the weather. How can it be leveraged to help businesses connect and engage with consumers? We call ourselves a location company that’s driven by weather. We map 2.2 billion locations globally for weather forecasts and provide information to allow people to plan their lives — to make decisions about what they’re going to do, where they’re going to go, what they’re going to wear. And we work with a lot of companies on a B2B basis: aviation companies, energy companies, retailers, anything where business performance would be affected by the weather.
Over the last four or five years, as data has become much easier to leverage and manipulate, we’ve started seeing ourselves as a product and technology company as well as a media company. From that, we’re starting to have conversations about how we can take data and predict consumer behavior based on weather conditions. We’re not just looking at the weather as absolute — “It’s sunny outside, so let’s have some ice cream.” It’s much more about the different layers of weather data, around relativity and seasonality.
For example, 60 degrees in Austin and 60 degrees in New York may be the same temperature, but people in Austin would react very differently [from people in New York]. We’ve started putting together algorithms that can basically predict consumers’ propensity to buy or behave in a certain way.
This weekend in London, we had the first sunny, warm-ish day. It wasn’t that warm, but it was sunny, and suddenly everyone was in shorts, buying ice cream. But we’re still in the beginning of April, so no one was leveraging that behavior change. Humans act like a swarm, and when the weather changes, we all change our behavior on the back of that. The clever advertisers would be the ones advertising ice cream and summer activities even though it’s April. We divide the seasons into six, and the most important ones are those transitional seasons between spring and summer and autumn and winter.
How does a long-established organization like the Weather Company build innovation into its DNA? I think a lot of it comes down to talent.;