Where Big Data Comes From And Where It Goes

As journalist Hugo Rifkind’s train passed through Newcastle on its way north from London, his phone pinged. He had received an email. The message was from TripAdvisor, and it was offering him information about hotels in the city he had just passed.

Rifkind’s confused tweets asking his followers how the website knew where he was reveal much about both the fine content targeting that Big Data can bring and the invisible way in which that data collection works.

The source of Big Data can be divided into at least nine different areas, including documents  and media, business apps and machine logs, archives and sensor data, as well as the public Web, social media and data storage centers themselves.

When a customer completes a survey, he volunteers information about himself. When he buys a product, he reveals his purchase preferences and adds to a list of other purchases that helps to build a near-complete picture of his tastes. When he browses the Web, he notifies advertising firms like Google of the sites he has visited, allowing them to displays ads promoting pages in which he has already shown an interest. And when he creates an account on TripAdvisor and leaves his telephone’s GPS on, he tells a travel company when he’s far from his usual haunts and may be in need of a place to stay.

Different businesses will have access to different kinds of data but content marketers are usually able to depend at least on social media data, on information collected by the Web, and on the company’s own customer records.

Together, that data can be used to track customers through their journey, to create different messages that can be checked in A/B tests to see which are the most effective, and to predict customer behavior in the future.

Taking A Siesta In Beijing

One of the most common uses of Big Data by content marketers is to transform it into infographics. Those attractive visuals so frequently shared on social media draw on data from a range of different sources but the most original will make use of the company’s own information. Jawbone, for example, drew on the data collected by its fitness trackers to share sleeping habits in cities around the world. We learn that Tokyo sleeps the least with just five hours and 44 minutes a night while residents of Melbourne, Australia enjoy a mighty six hours and 58 minutes. Five percent of Beijingers nap in the afternoon, double the percentage of Madrid residents who take a siesta.

Other companies have trawled through their data to produce reports on dating preferences, the sharing economy and the kinds of projects most likely to be funded through crowdsourcing.

Software collects the data. Analysts break it down. Content marketers turn the trends the analysis produces into stories that people want to share and into advertising that’s targeted, valued and achieves results.

Hugo Rifkind might have been confused about how TripAdvisor knew where he was but companies now have access to a constant stream of real-time information and can automatically turn it into content, delivering it to leads wherever they are.

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