This post, written, by Dr. Augustine Fou, Chief Marketing Science Officer for The Advertising Research Foundation is part of our CES-Inspired blog series. This topic is our first, Geo-location. My related post is here.
As more and more consumers spend more and more time on their mobile devices (even exceeding their time in front of computers) we are aggregating a massive new data set — geolocations based on the GPS locations in their mobile devices.
There are obvious benefits to having this data. Waze (Google) uses real-time speed information to crowdsource traffic stats that inform navigation systems. Ads for the closest barber shops or listings for restaurants in the vicinity can be brought up based on where the user actually is. Furthermore, geolocation can be used for additional context to understand the meaning of users’ searches. For example a search for “pizza” on a Friday night from home, usually means the user is looking for home delivery of pizza for dinner; while the same search for “pizza” at noon from an office location might mean the user is looking for a restaurant near the office to go to for lunch.
Along with these enormous benefits there are new risks that should not be overlooked. For example, knowing that someone is not home during certain hours every weekday could allow bad guys to easily burglarize the house. Knowing someone’s favorite restaurants, bars, or home address may present personal safety risks if that information falls into the wrong hands. So it really boils down to who has access to what information about individuals’ locations, at all times based on their mobile devices.
For the most part, the forerunners in the mobile data space like Foursquare, with location-based “check-ins,” have done a good job protecting users’ privacy by careful handling of their geolocation data; these were “walled gardens” with unique, custom data sets. But more recently, data management platforms, which sell user targeting data to programmatic ad exchanges, collect users’ place-based information via their mobile devices, often without their knowledge. They collect this information on users via many partners, from mobile apps, analytics packages, and even telecom providers (that pre-install tracking on locked phones). Then they sell the data to drive prices higher — i.e. higher premiums associated with greater targeting, because advertisers are willing to pay more for users whose locations are known.
But while these members of the ad tech supply chain are making higher profits from the buying and selling of user data, most users are not aware of the extent to which their data is being used, nor do they have any means to determine that and control their own information. That leads to bigger questions — who owns this geolocation data — the users or the companies that collected it? What rights do users have and what can they do if they wanted to “get their data back?” There is clearly enormous value in that data; but consumers are not getting any value from it at this point, while companies are profiting from it. Is this sustainable or does it have to change?
History has shown that any significant imbalance of value must ultimately be rebalanced in order for a healthy ecosystem to persist. We see this in physics – areas of high energy will balance with areas of low energy. We see this in nature – ecosystems with an explosion of invasive species will rebalance and settle into a new steady-state. In our digital advertising ecosystem, as consumers continue to gain power, they will also start to exercise their rights to see what data is being collected of them and demand the ability to control, edit, take it back, or delete it.
Other ecosystems have had to “rebalance” and acknowledge the rights of the consumer – think, Do Not Call List. There is already the digital equivalent called Do Not Track and Ad Choices, pioneered by digital advertising trade associations. Facebook and Google both now allow users to download their own data from the cloud — from emails to photos to videos, and every other type of asset — if they so choose to take their data with them.
Further, past analyses of how ecosystems evolve show some consistent patterns: 1) when a new market is being developed, pioneer companies create walled gardens in their attempt to set and become the standard and own the entire market, 2) then in order to continue to achieve growth, fast followers promote interoperability in order to gain access to previously established walled gardens — the interoperability increases the value of the network effect, and 3) once most players are interoperable, most of them no longer have unique, defendable competitive differentiation, which leads to waves of consolidation and eeking out more efficiency.
In the programmatic ad tech ecosystem, we may already be in phase 3 and some consolidation has already been witnessed. But the companies in the ecosystem that can most proactively make changes to empower consumers to know and control their own data will likely be the ones that succeed long term.