Takeaways from Streetfight’s Local Data Summit 2015 in Denver
Mary Bowling

Streetfight Denver 2015 logo

Last week, Streetfight held its second Local Data Summit in Denver, Colorado. Many of the Streetfight folks are based in the Mile High City area and quite a few of the sponsors were based in Denver or Boulder, as well.

There were also representatives of some national companies involved in data, like Yext and YP.com, and some big players that I wouldn’t have expected, such as MasterCard, which makes its vast amount of unpersonalized data on global purchases available to others. The almost three dozen presenters and panelists were squarely focused on their visions of how data is shaping the future of marketing.

Streetfight Denver 2015 crowd

Here are summaries of what I found most fascinating at Streetfight’s Local Data Summit. I’ll start with David Mihm, since his thoughts are probably of the most interest to LocalU readers.

David Mihm

David’s topic, Probing the Depths of Google’s Local Data Iceberg, was an argument for understanding just how much data Google has from its Search, Mapmaker, Adwords, Plus and Mobile platforms, as well as from programs like GOOG 411 that served their purposes and were then phased out.

Google’s data set is both extremely deep and wide with “an amazing cache of data around entities.”  Google has behavioral data around locations and local businesses that it’s continually analyzing and sometimes acting on. Mobile phones give Google amazing location awareness to meld with that data. Some examples he gave:

  • Google Now is associated with all things Google, as well as with apps that help to put things together — like hotel reservations, calendars to remind us of those reservations and driving directions to our destinations.
  • Driving directions show strong user intent to visit a business and location awareness lets Google know if you actually went there.
  • Android Pay will help Google close the loop between online search behavior and offline purchases.

My takeaways were that Google has the most data and the most useful data and that all the other players have a lot of catching up to do and business owners should concentrate on creating attractive, information-rich knowledge graphs around their enterprises.

Stefan Weitz

The opening keynote from Stefan Weitz, who until recently was the Director of Search at Bing, set the stage for the day by talking about how the future of search will look nothing like it does today. The presentation title, Your Coming Superpowers, was very apt.

More and more people are becoming continually connected via the internet of things and through those things are constantly sending out data signals that are being captured.  So there’s a lot of data out there — currently four zettabytes (1 zettabyte = 1 billion terrabytes) a day is gathered and stored in the crawlable cloud. That’s doubling every year. These signals are not just stored as raw data, but characteristics and relationships are being mapped by the search engines, allowing their machines to not only understand things much more easily, but to train themselves to recognize patterns and try to predict what comes next.

In addition, machines are now capable of interacting with us in somewhat human ways. We all know they can hear and speak to us these days, but perhaps don’t realize all the other ways they have of sensing what’s going on and reacting to it.

One example Stefan gave was the X-Box Connect’s ability to sense what we’re doing. It can understand things like changing heart rates, the amount of weight being put on each foot, how quickly arms move and in which directions, and so on.  He then talked about how Netflix could use a similar technology enabling it to sense our reactions to what we are watching — essentially allowing us to truthfully rate shows without having to do anything other than watch them.

Chris Dancy

In the second keynote of the day, Chris Dancy — billed as the world’s most connected human — took us through his journey of what that means and how it helped him to learn about himself and his environment and ultimately change his life for the better. Much of it was a cautionary tale about how we freely give up our data everyday and it then becomes lost to us and often we can’t get it back without paying for it.

Robert Reich

The founder of Denver/Boulder New Tech contended that cheap sensors + algorithms = retail profits.  His thought-provoking argument is based on finding ways to use increasingly inexpensive sensing devices, such a beacons, cameras, motion sensors, smoke detectors, etc., to help retailers engage and appeal to visitors in their stores and to create mashups of sensors to achieve new forms of useful automation.

Amber Case

Amber told us she is leaving Esri to write a book about Calm Technology. Even though the concept has been around since 1995, it’s a new one to me. It refers to making technology unobtrusive rather than disruptive. Instead of demanding our attention, technology should do its job quietly in the background by sensing changes and adapting to our needs.

Local Data Summit Amber Case Interview

In other words, it gets technology out of the way by designing things with the least amount of technology with which they can operate. She said this is best done by testing out in the real world because testing environments don’t produce real world insights.

Amber stated that a slow creep in privacy loss is usually ignored and won’t prompt any big policy changes. She said that people will give up a lot of privacy if what they get in return is useful and that they are clearly informed about what will be done with their data.

Case referred to our industry as a tower of babel and encouraged developers to cooperate and allow others to build upon their systems for everyone’s benefit.

Cristobel von Walstrom

Mastercard Advisors’ VP of Location Intelligence gave us some examples of how its purchasing data can be sliced and diced to provide insight into buying patterns. In one example, she showed us how forecasts of extreme winter storms can help stores stock and staff appropriately for those types of predicted weather events. In others, she demonstrated how knowing where travelers come from and what they tend to buy when they arrive in certain places can help us to target them before they even leave home.

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