Selling Your Data? Here’s What You Need To Know
If you’ve been collecting data for a while for your own analytical use, you’re hopefully getting some good value out of it. And it may not surprise you to find out that other companies may get value out of it, too. But if you’re looking to sell your data, there are some things you should know.
About one-third of companies are selling their data, according to a recent Forrester Research report. And it’s not just the mammoth outfits like Netflix or Boeing that are monetizing their digital assets — Forrester says that small companies are getting in on the action, too.
Forrester identified some interesting correlations among the companies that are selling the most data. For starters, data sellers tend to have higher growth. In fact, companies growing 10% or more per year were three times as likely to be selling its data as companies with low or no growth, according to Forrester’s report.
Companies that have figured out how to sell their data also tend to have a chief data officer (CDO) on staff. According to the research, 48% of companies that have a CDO also report that they’re selling their data, while only 24% of those lacking a CDO are also data sellers.
Not surprisingly, data sellers also tend to have more sophisticated governance initiatives. Forester says firms that sell data are twice as likely to create a business-led data stewardship or governance program as those that do not.
Data selling cuts across industries, according to Forrester, and businesses that sell to other businesses are just as apt to be data sellers than businesses that sell to consumers.
Forrester had some great examples of data-selling in the real world:
- LexisNexis sells all kinds of data, but one of the most recent examples involves its CounselLink Insights offering, which helps companies determine if they’re spending too much on outside counsel or worker compensation claims.
- Siemens provides data about the availability of trains through its Siemens Mobility Data Services offering.
- Micheline Tire Care sells data aggregated from its customers’ tire pressure monitoring (TPM) systems that helps customers know about the overall health of the vehicle.
The actual form that the digital deliverable takes also varies in the new data ecosystem. Forrester says that 37% of firms provide raw data, either through a download over the Web or through FTP. A tad more firms (47%) report offering their data via an API. Examples of API-based data selling include the TomTom Traffic Stats API, Dun & Bradstreet’s Business Verification and Company Contacts APIs, and the US Bureau of Labor Statistics.
We’re increasingly finding data bazaars pop up that cater to more sophisticated data monetization. You can find an array of data-serving APIs at the Microsoft Azure DataMarket, while newer players like Dawex provide a central source for data downloads or API feeds with provisioning and billing functions. “Selling data, however, requires a data- and development-savvy target market,” Forrester says.
It’s not surprising to learn that companies will often sell or share data first with their partners (including suppliers and resellers) before they start selling it to any Tom, Dick, or Harry. The Air Miles program in Canada and American Express’s Plenti program in the United States are good examples of these partner-focused data sharing programs.
Consumers are also getting in on the data buying (and data selling) action. On the sell side is just about any major website today that offers a service in tacit exchange for some of one’s personal data. Forrester reports that a majority of consumers support this form of data sharing.
But consumers can also be on the receiving end of the big data deluge. Forrester reports that customers of Pacific Gas and Electric (PG&E) can compare their energy consumption against the aggregated energy usage of other PG&E customers; Opower provides the data here. Similarly, athletes that use certain Suunto watches can compare their performance stats (collected via the watch) against other athletes.
The potential benefits of using other people’s data are huge. It’s all about data blending. If one particular data set is good, and another makes it better, then there’s no reason not to add even more data. This, of course, is one of the main premises of the big data analytics movement. Without mixing data sets, one cannot find interesting correlations.
Forrester reports that nearly three-quarters of companies are looking to create a “data innovation” capability. These desires cut across departments; product development, operations, marketing, sales, finance, and human resources are involved.
So, what steps should prospective data sellers take to get started? Forrester analyst Jennifer Belissent offers some tips.
“The first step might seem obvious but to some it’s not,” Belissent tells Datanami. “What data do you have? The first place to look is at what data you use internally. Sometimes companies would want to keep that for themselves, but other times the data can benefit others without revealing any trade secrets.”
There are some limitations to what you can sell, however, particularly with GDPR going into effect next year and other regulatory constraints. “Privacy is a concern, and you might think twice about selling it if you’ve promised not to,” she says. “WhatsApp’s flipflop on customer data left users feeling betrayed.”
There are multiple ways to sell the data. “If you’re selling data you might sell through a data broker, a curated marketplace or a self-service marketplace,” Belissent says. “Companies like Exapik brings brokers data deals, and Quandl helps prepare the data and provide a marketplace. But selling data requires a data- and development-savvy target market and that means slower time to value.”
How particular companies use data varies greatly, and prospective data sellers would do well to think about adjacent use cases. The public data miner Enigma, for example, collects information about liquor licenses as a proxy for new restaurant openings that could be receptive to hearing about hospitality services, Forrester says.
Similarly, when AT&T collected data to help it place retail outlets, it realized that other retailers might benefit from that data too.
This brings up another thorny issue: competition. You obviously don’t want to help your competitors by selling them your most valuable data. However, Forrester finds that most companies are willing to part with some data provided they are compensated for it.