Have you ever heard the case of Strava? Strava is an American service for tracking human exercise which incorporates social network features. It is mostly used for cycling and running using GPS data. Strava uses a freemium model with some features only available in the paid subscription plan. The service was founded in 2009 by Mark Gainey and Michael Horvath and is based in San Francisco, California. Well, now imagine the following situation. You and a colleague are at the Strava headquarters in the early 10's. Strava is a fast-growing startup and you're still pretty incredulous about the success and spread of the app you've been working on. On a normal afternoon at the office, you thought about mapping the data you've collected over the past few months onto a map of San Francisco. In short, you thought of a way to visualize what each user sees at the end of a workout - the route they took on the map - in a single map that would consider all the users in San Francisco and the time they took that route. In jargon, it's called a heat map, and it allows you to see which areas and times are most densely populated by cyclists in the city. This computer exercise generates a moment of pure fun with your colleague, moving a cursor you can see how the city's users are concentrated mainly in certain areas and - for example - how the trends are different between weekdays - in which we can imagine many people use the bike to go to work and then go downtown - and weekends, in which we see much longer average routes and a strong concentration in city parks. Imagine being in front of this screen with your colleague and being happy with the result, knowing how people move around the city using the bike and feeling that excitement you normally feel when you finish programming an application and see the result working. Once the tech euphoria has passed, imagine your colleague turning to you and saying, "Well, that's nice, but what do we do with it now? Who cares where people in San Francisco ride their bikes?". We don't know if that was the conversation...but that's definitely the right question for building a platform that can capture the value of a digital application's data. Who cares about the data we have? Who do they have value for? A brain storming session probably led to the right answer: the transportation departments of the various municipalities. There we go, Strava Metro was be born, a new service that offers municipalities or other entities packages of data on how people move around the city, allowing them to make data-driven decisions about, for example, where to build new bike lanes or where to make more or less investments. One of the first deals taken is with the Oregon Department of Transportation, which told Wired in 2013 that it bought an annual data package from Strava for $20,000, a number very far from the typical monthly fee for a freemium subscription. And from there, Strava Metro became another line of business for Strava, which in doing so became a true two-sided orthogonal platform. Strava is the platforms provider, the first side is represented by the end users, the cyclists, and the second side is represented by all the third parties that see value in this data, such as the various departments of transportation. As in the previous cases, this is a case of a client-as-a-source strategy, where the first side is the main source of the value that will then be offered to the orthogonal side, again generating unidirectional cross-side network externalities. This strategy is called “data trading”, data can be sold, but some cases even simply traded for example in exchange of other data, as Waze did back in the years with the municipality of Rome, exchanging data on the traffic in the city. This is the most complex strategy for capturing value through data collected with a digital application because it requires the platform's ability to understand who might be interested in that data and how to make it useful and actionable. Here we have various examples, Twitter for example selling Tweet streams for search purposes, but also two-sided transactional platforms like Uber or Skyscanner, which have become multi-sided by offering data packages to third-party actors, such as traffic research organizations in the case of Uber with Uber Movement or airports with Skyscanner Partners in the case of SkyScanner. Again, it is important to emphasize the privacy dimension. This mechanism makes sense and has value only if it confirms current regulations, such as the GDPR Europe, emphasizing that to implement this strategy, data can be anonymous, since its value emerges from the volume and the possibility of seeing in this large amount of data patterns of value for orthogonal actors.
