The World Of Data: Hoarders Vs. Sharers

Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Auren Hoffman, CEO at SafeGraph.

In my last AdExchanger column in September, I discussed truth and religion data companies. Truth data companies are backward-looking, focusing on data that can reveal information about people or when something happened. Religion data companies attempt to predict the future based on data.

Another axis of data companies that is often overlooked but equally as important is the hoarders versus the sharers.

Both hoarders and sharers spend a great deal of time collecting proprietary data and pride themselves as having a core competency in great underlining data. But once these companies have great data, they follow very different strategies.

Data hoarders build tools on top of their data, and they never sell the underlying data.  These companies can build amazing applications and they use their data as a core advantage that makes their application better.

One example of a super data hoarder company is Flatiron Health, which was started by the founders of Invite Media. Flatiron Health has great proprietary data on oncology and it uses this data to make amazing products that help fight cancer.

Data hoarders need to go super deep in one vertical to provide a very exciting solution for that vertical. The upside of that strategy is that they can grow really fast because they often become the de facto experts in their field. The downside is that their growth is dependent on the growth of the vertical they choose. For instance, if you are servicing ad tech, you are betting the ad tech vertical will grow.

Data sharers also have amazing data, but for them, data is the product. They spend their time building great data sets and then they invest in APIs and other tools so they can broadly deliver their data. One example of a data sharer is Windfall Data, which is working on building the most accurate estimate of every consumer’s net worth. It appends this data to marketers, nonprofits, financial services and more.

Data sharers often pivot to becoming data hoarders, but rarely do data hoarders become data sharers. For instance, when it launched its first product, a stack database to help companies choose technology, Siftery was a classic data sharer. But its latest offering, Siftery Track, more closely resembles a data hoarder because it helps companies use this data to track their software spend.

Data sharers have the luxury of being a horizontal solution across many verticals. The positive is that they have a lot of places to sell to. The negative is they need to sell to other applications that can make their data sing, which means they often do not control their own destiny and may have slower growth.

As startups develop their data company, it is important to squarely put themselves in either the data hoarder or the data sharer bucket.

Follow Auren Hoffman (@auren) and AdExchanger (@adexchanger) on Twitter.

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