Mining for Metadata Gold
Datafloq’s recent missive on metadata couldn’t be more on the money—literally.
According to author David Frankel, any enterprise whose software or technology generates non-identifying information (data that doesn’t convey a user’s identity) could transform that data into its own revenue stream. This application of the data, however, is not to be confused with using it to make internal product management decisions.
The same strategic focus that is going into how to build a foundation to use data for internal decision making should, simultaneously, be devoted to how to turn the data that is being created by the business into revenue opportunities. Businesses like yours are structuring data, storing data, and starting to use and analyze data themselves, but they are not embracing that they are, in fact, creating marketable customer data, operational data, industry data, and transactional data as a high margin bi-product [sic] of their normal existence.
Frankel goes on to cite FourSquare’s new product, Attribution, as an example of this process in application. FourSquare’s original app allows people to easily check into locations, and the company soon realized that the usage data the app was collecting could be of value to enterprises interested in measuring the conversion rates of their digital ads. That concept became Attribution, a completely new product and revenue stream catering to an entirely different audience.
The data monetization process requires both business acumen and technical resources. The first step is, of course, to generate non-identifying usage information. If you’re a SaaS company, the good news is this step is more-or-less taken care of. If you have users, you are generating usage metadata, but chances are you’re generating more than you’ll actually need. Before you set about storing that data, you’ll want to decide what’s worth tracking. One method is to start with low-hanging fruit—the data that’s easiest to collect—and proceed from there as needed.
Once you’ve targeted your data, the next step is to store it. Keep in mind that you’ll want to be able to query your database and visualize the information for discovery purposes, so make sure the data will be easy to access later.
It’s at the analysis stage that BI comes in. Having a tool that will help you rearrange, sort, filter, and visualize the metadata will go a long way towards making sense of it. If you’re a SaaS company you may already have an embedded BI solution as part of your software that you could retool for internal use. Manipulating the data will lead to a better understanding of its patterns and potential value.
Which leads me to the final step: strategy. The ultimate goal is to turn this metadata into a revenue engine, so finding a group of stakeholders interested in the data is crucial. For Foursquare, it was marketers, marketing agencies, and publishers looking for ad campaign validation. For a medical software application, it may be pharmaceutical companies; and for an HR application, it might be insurance providers. This part requires intimate knowledge of your data and industry vertical as well as how it overlaps with other verticals.
Come v2017.1, slated for release this May, Exago will begin making reporting metadata available to its clientele. It will be possible for applications hosting Exago to log usage metadata pertaining to folder management, charting, scheduling, mapping, and more. The power of this data to inform internal product decisions alone renders such monitoring tools invaluable, but their potential to generate new revenue is truly exciting. SaaS companies can begin taking advantage of this feature by packaging their BI metadata with the product, offering market insights to prospects as a value-add.
But there are dozens of ways to monetize data, and, as Howard Dresner intimates, “Embedded BI is just one [option], and it really depends on the targeted audience.” Regardless of the method you employ, data monetization requires a healthy dose of business savvy, and a BI solution that can help gather and analyze metadata certainly expedites the process.