The Weather Company: Using Big Data to Drive Marketing Insights
A legacy media company arrests its decline through an ambitious digital transformation strategy built on big data and predictive analytics.
In 2012, The Weather Company (TWC) was at a crossroads. Founded in 1982 as “The Weather Channel,” the company’s core business centered on cable television programming, including weather forecasts and other weather-related content such as documentaries. But for years, viewership had been declining in the face of “cord-cutting” by consumers, as well as the proliferation of digital weather tools made ubiquitous by the smartphone. Yet, TWC had no mobile weather app—indeed, no real online presence to speak of.
Confronting these headwinds, the company embarked on an ambitious plan to leverage big data to propel the company into new, digital-first business verticals. The company announced its pivot by rebranding as “The Weather Company.” The embrace of data analytics was a natural next step despite the company’s decades-long roots in the cable television business. Said CTO Bryson Koelher: “Weather is the original big data application… when mainframes first came about, one of the first applications was a weather forecasting model.”
The company’s digital transformation entailed three main steps:
First, TWC augmented its deep bench of talent in meteorology and atmospheric physics by hiring data scientists and machine learning experts to work on cross-disciplinary teams building more complex forecasting models integrating a wider array of data. Relatedly, it expanded its pool of weather data by acquiring Weather Underground, which offered a weather app that used “crowd-sourced microclimate data” to offer precise weather forecasts through its mobile app.
Second, TWC overhauled its IT infrastructure by moving its 13 data centers into the cloud and integrating the “loose-knit collection of aging applications” constituting its legacy platform into a single integrated data platform. This integration not only enabled more efficient data analytics processing, but it also made it easier for third-party partners to plug into the platform. Costs for each API call—when a third-party application called on TWC servers to access weather data—plummeted to 1/70th of the cost under the pre-cloud infrastructure, driving customer growth. Today, TWC is one of the world’s largest API platforms, with over 25,000 partners and over 26 billion daily API calls.
Third, TWC began a period of experimentation to understand new verticals where its big data strategy would generate value for its business customers. A key vertical that emerged was marketing and advertising. TWC hoped to generate hyper-localized insights about consumers’ behavior by analyzing “when, where and how often people check the weather,” which would allow businesses to better target their advertisements.
TWC’s early experiments yielded surprising findings, according to a Wall Street Journal report:
- Consumers in different locales respond to the same weather differently:
- Bug spray sales increased during spring in Dallas when the dew point was below average, whereas bug spray sold better in Boston when the dew point was above average.
- In Chicago, heatwaves caused a surge in air conditioner purchases within a day, whereas consumers in Atlanta—ostensibly more acclimated to heat—tended to wait more than 2 days during heatwaves before purchasing relief.
- When a consumer checked the weather affected their consumption habits:
- Michaels’ craft stores had hypothesized that sales would surge on rainy days—when many people would take up craft projects. Instead, TWC insights showed that Michaels’ store sales surged when weather forecasts predicted rain 3 days in advance.
- Individuals who checked the weather earlier in the day were more likely to make decisions about how to plan the rest of their day—including potential shopping trips.
Future Applications
In November 2015, TWC was acquired by IBM. In November 2019, IBM launched Global High-Resolution Atmospheric Forecasting (GRAF), which brought IBM’s supercomputing power together with TWC’s weather prediction know-how. GRAF promised forecasts that refreshed hourly on areas as small as 2 miles wide (as compared to every 6-12 hours, on areas as small as 6-9 miles wide, under the most advanced weather forecasting alternatives then on the market). The supercomputer underlying GRAF claimed to process 12 trillion pieces of weather data integrated from an array of sources including smartphones and airplanes. GRAF promised to continue extending TWC’s pioneering approach to weather-related predictive analytics into new applications across a range of industries.
Joseph, thank you for the interesting blog post. I use The Weather Channel all the time, but never questioned its business model or strategy. As you mentioned, I think it took a bold but very suitable step for cord-cutting and using big data for customized forecasts. I believe Starbuck also researched on behavioral science to investigate the relationship between the weather and consumer habits. IBM’s acquisition seems like a smooth transition as forecasting is such a complex procedure requiring enormous data.
Joseph, really interesting post. I appreciated your specific examples of how their data created new and valuable insights for advertisers to better target users. I imagine getting top data science talent is a challenge for TWC given their less than innovative image. The acquisition will likely help with this but given that even tech companies are competing aggressively for talent, I imagine it will continue to be an issue into the future.
Before reading your post, I would have said that TWC was like a newspaper– they provide information, paid for by advertising. You’ve given some really powerful examples of how TWC is actually a data company whose real revenue-generating power comes from B2B data-sharing partnerships. I’d love to see more of their portfolio of partnerships. For example, have they partnered with restaurants to identify how demand for certain menu items shifts based on weather? So interesting!
Thank you for the interesting blog post about TWC! I had no idea that they were acquired by IBM and am excited to leverage their highly specific GRAF forecasts in the future. I also didn’t appreciate that TWC was able to consolidate its 13 data centers in to the cloud and reduced the cost to 1/70th of the pre-cloud infrastructure cost. I’d be interested to know how long this migration effort took (and how expensive the implementation process was). I also wonder if the weather channel would consider expanding to B2B offerings in addition to its existing advertising programs (i.e. deliver businesses’ location-specific weather data and predictive sales insights for businesses that do not currently advertise with TWC).
Joseph, super interesting blog post! I love The Weather Channel app and look at it every morning before heading out. It’s very interesting to see how they pivoted from a TV channel to a platform fully leveraging AI / ML and able to commercialize it. I didn’t know they had been acquired by IBM but it speaks to the level of data analytics capabilities they developed that their expertise became attractive for a big established player to continue advancing their own data analytics strategy. I’d be interested to know more how the post-acquisition integration went and how IBM has leveraged TWC’s data assets since then and how they’ve applied their capabilities to IBM’s other products!