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“Everybody gets the notion of location-based targeting in the sense of, hey, you’re within a mile of a particular store, so we’re going to give you a push notification to try to get you to come in,” says David Bairstow, SVP of product management at Skyhook. “And while it can have its role, this is a pretty coarse approach, and has the risk of spamming.”

Then there’s geospatial insights, the grown-up version of location-based intel which translates location signals and location data into more contextual insights. And these insights can actually help brands and app developers understand their users and engage with them more effectively, he says.

It means essentially looking for when consumers’ devices intersect with things that have context around them — an airport, hotel, restaurant, sports stadium, retail location, and more. As you see people visit those places, you can start to build up a profile of that device, and by proxy, the person holding that device.

“The value of location data distills down to basic marketing principles — know your customer,” Bairstow says.

Using the sports stadium as an example: Traditionally, professional sports franchises actually don’t know that much about the people that are attending their games. A percentage of seats sold are from season ticket holders, and that varies widely franchise to franchise. They know a little more about these season ticket holders, but in a lot of cases, the season ticket holders aren’t the ones attending every game, since they share the tickets or use them as business assets.

And franchises know virtually nothing about the fans in the seats, particularly for the single-game attendees, relying on annual surveys and similar tactics to get a sense of the demographic profile of their fans.

But location data can identify the people who are actually attending these games and help a sports franchise understand the profile of people that attend one game a season, and how different they are from those who attend two to 10 games. What’s the difference between their high-income fanbase versus the low-income fanbase, and what can be learned about them?

In building that fundamental understanding of who the fans are, franchises can build better engagement plans. Some of that is around how to improve the fan experience. If the Chicago Bulls identify that their fans have a strong affinity with a particular local brand, they can coordinate with that brand and run promotions that are mutually beneficial.

The franchise can also use those insights for sponsorship. If you know there’s a strong affinity in Atlanta for Home Depot — which is headquartered in Atlanta — that’s a brand the Braves can approach to build partnerships.

“We’re providing understanding of the consumer base or the fanbase that allows the marketing to be smarter and more sophisticated about how fans are engaged,” he says.

Location data is also key for travel and hospitality. For instance, the airlines might know a lot about their travelers’ profiles through their frequent flyer and visitor programs — but that’s only when they’re traveling with their brand. In other words, JetBlue knows everything about the flights you take on JetBlue, but they have no idea how often you fly on Delta and United and other airlines. And that’s a huge piece of data to be missing, especially in an industry where competition for market share is fierce.

Being able to capture “micromoments” is another huge location intelligence advantage, Bairstow explains.

That means not just understanding flows and movements within the airport, pre-trip — what people are doing before they get to the airport, after they get to the airport, where they spend their time, where they’re eating — but understanding and monitoring in real time, for instance, when there are huge lines at TSA, he says. So if you have the Delta app, for example, Delta could push you a notification and say, hey, there are much shorter TSA lines at the other end of the terminal.

Yet another area is understanding the user journey. In the QSR space, for example, big companies are trying to understand and capture the types of journeys their customers make to fast food restaurants. Are they getting people on their commute? After they work? On their way to a game? Only when they’re traveling? If you can understand and classify those different journey types, understand the right time to intercept and engage, you can influence behavior and create even more visits and more trips.

That takes a lot more than just point-in-time observations, he adds. That’s looking at patterns using machine learning to understand and classify journey types, to dynamically understand when somebody is on a particular type of journey, so a marketer can engage and intercept.

“Location data is about filling in blind spots in your understanding of the customer,” Bairstow says. “It’s an incredibly complementary piece to any brand’s CRM.”

To learn more about how to develop a location strategy, how to integrate location intelligence into your understanding of customers, and use that data to drive decisions, don’t miss this VB Live event!

Don’t miss out!

Register here for free.

During this webinar you’ll learn how to:

  • Boost engagement with location-based consumer insights and competitive intelligence
  • Gain insight into the behavioral patterns of customers and prospects
  • Apply the best use of location data for your business


  • David Bairstow, SVP Product Management, Skyhook
  • Sheryl Jacobson, Principal Consulting Strategy and Analytics, Deloitte Consulting LLP
  • Stewart Rogers, Analyst at Large, VentureBeat (Moderator)

Sponsored by Skyhook