The 'Uber' Of Data

Companies of the sharing economy like Uber and Airbnb have disrupted massive industries by changing the math on what the theorists call asset utilization.

In fact, they changed the math so much that assets not previously considered a viable part of their respective markets -- my fancy fast car while I’m in my office, or your Manhattan apartment while you’re off visiting Mom for a weekend -- suddenly became very viable, indeed. They did this by exposing information about those assets in easily accessed online marketplaces, so that anyone could find out about the asset’s characteristics, its availability, its pricing… but you already know that story.

I’m reminding you of it now, though, because it’s a potent way to think about the potential of, a tiny, not-exactly-stealth start-up whose founder and CEO I spoke with recently. This small company could play a possibly large role in the future of AI by arranging access to the data that is all-important to making AI effective.

Nick Jordan says he witnessed a thirst for data in his prior jobs, which included SVP of cross-device marketing firm Tapad (acquired a year ago by Norway’s Telenor Group), and a stint at Adobe before that, when it acquired Demdex, the DMP start-up where he was VP, partner solutions.

“There are a lot of data scientists out there hypothesizing about what they could do with data sets they don’t have, but know exist,” says Jordan. “The problem is, when they try to go and get access to datasets -- to acquire datasets outside their own walls -- that process is hopelessly broken.”

Figuring out what organizations might have the data you’re looking for is hard enough, but it turns out to be the easiest part of that “hopelessly broken” process. Jordan explains that it’s harder still to find the right person in an organization with knowledge of and authority over the data you want, and then to convince her to sell the data — which only leads to myriad challenges over negotiating the price. And if you achieve all that, there’s the painful data integration problem: moving the data from point A to point B and translating it into a format you can use.

But even that’s not all. “Most times, a single source of data is not enough. You have to repeat the whole painful process for many different data sources,” notes Jordan.

Enter Jordan’s company is in the process of closing a second round of investment that will bring the invested total thus far to $2 million. The platform is up and running with a handful of early customers.

To dramatically oversimplify, the mechanics of’s platform are actually very similar to Uber's or Airbnb’s: organizations that have data assets they’re willing to share post them to the platform, and establish standard pricing. Potential data buyers search the platform to find the data assets they need to make their models hum. “We offer a couple of different approaches to ‘try before you buy,’” Jordan says.

Each dataset, alone, isn’t necessarily the answer to anyone’s prayers; but aims to make it dead simple to assemble multiple disparate datasets that together can empower AI-based models. “When you combine these little signals across billions and billions of data points, it can become very valuable to customers building predictive models,” Jordan notes.

Naturally, since Jordan comes out of digital advertising and marketing, those are the first kinds of organizations he has recruited to populate data into, and to make use of it as customers. “Right now, everyone from brands to marketing technology platforms to publishers are very data-focused,” Jordan points out. Data, after all, is the oxygen of modern marketing.

For publishers, Jordan’s plan could add data monetization as a potentially sizable third revenue model to their existing subscription and advertising models. For marketing technology platforms, could simplify access to many datasets. “Data acquisition can be so painful for them,” says Jordan. “They generally stop after one or two deals, but that may not be enough to drive the best outcomes,”

As for the “not exactly stealth” aspect of the start-up, I learned about because I know someone who knows someone, if you know what I mean. But Jordan says stealth isn’t a strategy, just a matter of prioritization. The company is still building its data pool and getting early customer experiences, so it’s not yet up to PR and marketing.

Data, as I said, is the oxygen of modern marketing. But Jordan is right about how challenging it can be to get efficient access to just the data you need, at a fair price. It’ll be interesting to watch as this still-small start-up attempts to gain first-mover advantage over the oxygen of the coming data society.

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