{"id":15860,"date":"2022-10-03T22:47:32","date_gmt":"2022-10-04T02:47:32","guid":{"rendered":"https:\/\/d3.harvard.edu\/platform-digit\/?post_type=hck-submission&p=15860"},"modified":"2022-10-03T22:48:45","modified_gmt":"2022-10-04T02:48:45","slug":"big-data-at-the-weather-company","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/big-data-at-the-weather-company\/","title":{"rendered":"The Weather Company: Using Big Data to Drive Marketing Insights"},"content":{"rendered":"\n\n\n

In 2012, The Weather Company (TWC) was at a crossroads. Founded in 1982 as \u201cThe Weather Channel,\u201d the company\u2019s core business centered on<\/a> cable television programming, including weather forecasts and other weather-related content such as documentaries. But for years, viewership had been declining<\/a> in the face of \u201ccord-cutting\u201d by consumers, as well as the proliferation of digital weather tools made ubiquitous by the smartphone. Yet, TWC had no mobile weather app\u2014indeed, no real online presence to speak of<\/a>.<\/p>\n\n\n\n

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<\/a> by rebranding as \u201cThe Weather Company.\u201d The embrace of data analytics was a natural next step despite the company\u2019s decades-long roots in the cable television business. Said CTO Bryson Koelher<\/a>: \u201cWeather is the original big data application\u2026 when mainframes first came about, one of the first applications was a weather forecasting model.\u201d<\/p>\n\n\n\n

The company\u2019s digital transformation entailed three main steps:<\/strong><\/p>\n\n\n\n

First<\/strong>, TWC augmented its deep bench of talent in meteorology and atmospheric physics by hiring data scientists and machine learning experts<\/a> 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 \u201ccrowd-sourced microclimate data<\/a>\u201d to offer precise weather forecasts through its mobile app. <\/p>\n\n\n\n

Second<\/strong>, TWC overhauled its IT infrastructure by moving its 13 data centers into the cloud and integrating the \u201cloose-knit collection of aging applications<\/a>\u201d 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\u2014when a third-party application called on TWC servers to access weather data\u2014plummeted to 1\/70th<\/a> of the cost under the pre-cloud infrastructure, driving customer growth. Today, TWC is one of the world\u2019s largest API platforms, with over 25,000 partners and over 26 billion daily API calls<\/a>. <\/p>\n\n\n\n

Third<\/strong>, 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\u2019 behavior by analyzing \u201cwhen, where and how often people check the weather<\/a>,\u201d which would allow businesses to better target their advertisements.<\/p>\n\n\n

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Consumers in humid locales were targeted with anti-frizz hair products whereas consumers in dry locales were targeted with volumizing hair products<\/strong><\/em>. Source: Wall Street Journal.<\/a><\/em><\/figcaption><\/figure>\n<\/div>\n\n\n

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TWC\u2019s early experiments yielded surprising findings, according to a Wall Street Journal report<\/a>:<\/strong><\/p>\n\n\n\n