Implicit Signals

by Scott - 1 Comment

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I’m extremely fascinated by the opportunity to leverage data to find implicit signals. If you’re unfamiliar with the term implicit signals, I’m referencing instances when user actions/data imply meaning, yet don’t state it outright. Fred Wilson provides some additional quality content on the implicit web here.  An example of an implicit signal can be if I check into the same coffee shop on foursquare every morning. By doing this I’m implicitly recommending their coffee. I don’t state it outright, but the act of me broadcasting my location when I purchase it every morning implies that I like their coffee.

API’s have driven a lot of the innovation around this concept because they enable the sharing of data. Still, I believe we have only scratched the surface of what is possible with gleaning implicit signals. I think the true breakthrough around this concept will occur when platforms begin to share greater amounts of proprietary data. Because businesses have different goals, their focus can be extremely different, even when interpreting the same data. They can easily gloss over subtleties such as implicit signals if the insight does not directly reside in their value chain. This is just one reason why I believe there are a ton of untapped opportunities here.

I think the biggest opportunities exist with data that has a perceived privacy risk such financial information. These opportunities have been harder to access because fewer people have had the chance to innovate using the data. My favorite example to think about is What if Mint shared select users financial information with a few strategic partners. I like to think about the the marriage of Mint and Linkedin. My bank account and purchase history juxtaposed with my professional profile has the ability to tap into some pretty interesting applications. One large opportunity is the passive job search.

From you can get a pretty good understanding of my yearly income. You can also get a pretty granular view of my spending habits. Do I eat at fancy places? How much do I spend on rent? What percentage of my income do I save and what percentage do I spend?

Let’s say for fun I dine out at all the best places, spend a lot on rent, and save on a smaller percentage each month than most. From my extravagant lifestyle, one may implicitly assume that money is important to me. If an HR person at another company was seeking someone with my skillset for a higher paying position this insight has the potential to vastly improve the signal to noise ratio as they recruit candidates. On my end, I may receive a better job opportunity when I wasn’t even looking for one. There is a ton of value for both parties.

Would ever focus on analyzing spending habits to source hyper-focused professional opportunities? Maybe, but probably not. I acknowledge this situation is hypothetical and in many cases unrealistic, yet I still think there is so much potential around sharing to data to derive implicit signals. I’ll expand more on these thoughts soon including the biggest hurdles which are preventing the full potential of implicit signals being unlocked.

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