How Companies Are Turning Data Exhaust Into Cash

Most organizations collect enormous amounts of data these days, and many of them are implementing complex AI/cognitive computing-powered analytic tools in order to make better business decisions. Even then, many types of companies—telecoms, retailers, financial services companies, and utilities, among others—have an enormous opportunity to take advantage of, and monetize, their data exhaust.

Data exhaust is any information collected that isn’t core to a business and the decisions it needs to make, according to a new ebook from TDWI. Typically, this secondary data comes from web browsing habits or GPS data. Google is notorious for collecting this kind of data on its users, even without knowing how, exactly, it will take advantage of the details. Sometimes, that exhaust might not be taken advantage of for months or years, if ever.

Because 50 different web interactions can result in a single transaction, data exhaust often occupies much more storage space than the primary data that companies are actively analyzing. Given the enormous cost of big data storage, companies might be able to mitigate some or all of the cost of storing data exhaust by monetizing it. Others could build entire new business departments around that otherwise-unused data.

Getting a bang for the data buck

Monetization of data exhaust can take on a number of different forms.

Say an online clothing retailer is collecting transactions as its primary—or core—data. At the same time, they might also be collecting cookies, usage analytics, and other browsing habits of their users. They might have tools in place to analyze some of that information to offer personalized results, but other organizations might want that data even more. A fashion brand, for example, might be able to use the data to understand patterns and create new products that more precisely satisfy what consumers want. Similarly, insurance companies are clamoring for telematics data from vehicles to build better policies based on more precise risk determinations.

The sheer variability of the potential applications for data monetization means that many companies should be able to find some angle for their secondary data. Cloud applications could sell usage information to marketing teams. Drug usage data might be useless to a hospital, but invaluable to drug research and development. According to TDWI ebook, any company that collects product usage data or customer transactions should be able to monetize them. Sometimes, it just takes some out-of-the-box thinking—your data exhaust might not include transaction data, but if you can see via GPS data that someone has spent 15 minutes inside a store, there’s a high likelihood they bought something. That small detail just might be valuable to someone else.

Challenges with data monetization

There are still big issues around the mining of data exhaust, first and foremost might be the importance of ensuring that data is anonymized. Any buyers of data exhaust shouldn’t be interested in what a particular individual is buying or how they’re behaving, and thus you should be doing the work to leave identifying details out of the equation to avoid privacy concerns among your customers. Better yet, aggregate the data in ways that leave users protected, according to TDWI.

Whereas simply leaving exhaust unattended requires very little other than paying for storage capacity, maintaining it requires a more sophisticated plan from IT and the rest of the organization—upper management included. Without significant buy-in and a developed methodology of how IT will approach managing their exhaust (or purging it, if need be), getting real value of it will be next to impossible.

Collaborating with a business intelligence provider might make the whole process easier—the authors behind the ebook, Birst, have a product targeted toward monetization of data exhaust—but there are a bevy of data brokers in nearly every industry that can help connect exhaust with those who might take advantage of it. Platform-as-a-service (PaaS) offerings can help manage and share data in a variety of ways.

Regardless of the approach, data exhaust is angling to become one of the next big questions in big data: how to manage it, and who, in the end, will be able to make the most money from its complexity.

Related:

Usage-based insurance and telematics

Real-time marketing with customer transaction data