From Data to Money

Source: O’Reilly

… the stages of evolution a data product goes through to actually deliver value to customers.

  1. Data: You need it, but selling it raw is the lowest level of business. Warden writes “The data itself, no matter how unique, is low value, since it will take somebody else a lot of effort to turn it into something they can use to make money”.
  2. Charts: Simple graphs, which at least help users understand what you have, but “still leaves them staring at a space shuttle control panel, though, and only the most dogged people will invest enough time to understand how to use it.”
  3. Reports: Bring a focus to what the customer wants. Many data-driven startups stop here and make good money doing that. But there’s further to go: “It can be very hard to defend this position. Unless you have exclusive access to a data source, the barriers to entry are low and you’ll be competing against a lot of other teams”.
  4. Recommendations: Your product now goes from raw data and produces actionable recommendations, a much more defensible business. “To get here you also have to have absorbed a tremendous amount of non-obvious detail about the customer’s requirements, which is a big barrier to anyone copying you,” Warden writes.

Warden offers this pithy advice: “More actionable means more valuable!”

SGEye goes beyond recommendations by enabling customers (actual and potential) to automatically generate more data, which is then used to refine the recommendations.

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