Mobile Location Data and the Advertising Targeting Opportunity

June 22, 2010 · Posted in Commentary, Companies 

So I’ve been getting a re-education recently on the latest and greatest in digital ad networks and targeting.  Things like behavioral targeting and re-targeting have been around with us for ages, even before the Doubleclick & Abacus Direct controversies of the dot com boom years over a decade ago.  But for whatever reason, the whole hyper targeting and re targeting seems to have been placed back on the front burner of the industry, thanks in large part to the availability of inventory via advertising exchanges and the success that ad networks have seen in recent years… both of which have attracted a new category of entrants, including advertisers and agencies alike, back to the space.

So to those not in that industry here is the best I can do in summarizing what’s going on here.

The amount of display ad inventory available online is absolutely massive… far more than the supply of advertising dollars chasing it… so the price someone is willing to pay to serve any old advertisement to a random Internet user is pretty negligible. Meanwhile, the internet advertising industry long ago went down the path of selling itself as a data intensive, highly measurable and result oriented medium… and for better or worse is generally stuck with that description.

So… the name of the game nowadays is to not just serve anyone on the Internet any old ad and call it a day, but to serve a very specific group of people, sometimes a very specific ad, and measure what happened afterwards to see if it ‘worked’ in terms of driving clicks or purchases… rinsing and repeating until one gets the desired result or gives up and tries for a new result instead.  The more highly correlated a given piece of information is with some desired activity like a click or purchase, the more valuable it is.

So some folks are making tens of millions of dollars doing very little more than going to an open advertising exchange and buying low cost impressions generated by people they know, and then adding in the information they have on those folks in order to more effectively target ads in a game of information arbitrage.

The vast majority of folks are focusing on the part of the equation around WHO will be shown what ad… which can be things like people who shopped online for flat screen tvs in the past 30 days, or people who checked an online stock portfolio in the past 24 hours, or someone who just read reviews of new cars on an auto oriented site.

A great recent example of this is a company called Magnetic (http://www.magnetic.is) which just raised $5 million in funding some top VCs, and a company that PaidContent thinks could be part of the next big wave in online advertising.  What Magnetic  does is provides advertising re targeting data off of searches conducted at one’s site. So not only can site owners continue to run a Google AdSense for search program directly on their own site, but let’s say you’re running a car blog and someone searches for “Ford Mustang” on your site and later heads over to  somewhere like cnn.com to read about the disaster in the Gulf.  Ordinarily there is no way to know that a reader on cnn.com reading about the disaster in the Gulf may be interested in a Ford Mustang, but using a system like Magnetic allows CNN to directly get this information and try to use it to charge more for their ads, or alternatively ad buyers for someone like Ford may not even concern themselves with specific sites and instead simply buy people who have searched for their brand or products wherever they may go across the web, through purchases of ‘individual cookies’ via blind advertising inventory exchanges. 

Another similar example is aCerno which was recently acquired by Akamai for $95 million. aCerno uses consumer shopping data gathered from a co-operative of approximately 550 major e-commerce sites, to re target advertisements across the web based on their online shopping behavior. 

The key words to keep in mind about where the industry stands today is terms like “shopped online”, “checked an online portfolio”, “read an auto site”… notice one thing in common here… all these behaviors are taking place in front of a computer screen. But what about the vast majority (95%) of the times when all those folks walked into a Best Buy store, Fidelity retail brokerage or stepped foot onto a Ford auto lot to do their commerce the old fashioned way offline?

There is no reason why this game of information arbitrage needs to be limited to purely online behaviors, or to the traditional browser of the PC based Internet.

Is a guy who spent three and a half hours sitting in Yankee Stadium four separate times last month probably a better prospect to buy Yankee hats, mugs, and jerseys gear than the general public? You betcha. 

Is a user who spent 45 minutes at a local Ford dealer lot last Saturday, potentially someone in the market for a car with higher than average intent to purchase a Ford vehicle? Probably.

So you have to think that it won’t be long before all of that algorithmic, arbitraging media trading that we’re seeing online these days begins to bleed over into the world of offline meets online, using location data at the center, in fact it’s nearly here.

Now this could very easily turn into another rah-rah post about why mobile social applications like Foursquare, Gowalla, Loopt and MyTown are going to take over the world… they get you to fork over information about your whereabouts and that information can be digital adverting gold.

But I am not sure I am ready to concede that this is something for mobile social networks to own…  do you really need a user to push a button to tell you where they are in order to get that location information? Per a recent L.A. Times article, the latest Apple iPhone terms and conditions changed to include a section related to LBS where they declare that “Apple and our partners and licensees may collect, use, and share precise location data, including the real-time geographic location of your Apple computer or device” and the article also makes note of Google’s similar geo data collection policies for Android Phones. 

For at least a few years now companies like Sense Networks and Placecast  have been working with large volumes of aggregated location data, collected from a variety of places, in an attempt to unlock the value contained within a long history of geospatial locates.  So there are obviously other ways to get at this raw data and make it valuable beyond the self reported (and self serving?) check in, which after all is just a small snapshot of activity of a few million users at best. But how valuable is a string of user locates as stand alone data?

In the current online world, tracking a search query or information from a web page to turn it around for re targeting purposes is relatively straightforward since everything already exists digitally. But when someone goes SOMEPLACE in the real world now, the digital documentation about that place is currently pretty weak…  so going to a position in space at some point needs to get digitally mapped back to the vast reservoir of digitized knowledge that we have about that space.

Folks like Localeze have started us down this path by making business listings more rich versus the dry name, address and phone numbers of the days of the yellowpages, but they’re coming at it from a perspective of web and local search.

Meanwhile an interesting new company called PlaceIQ is coming at it from the perspective of painting a better contextual picture of the places people visit. In the same way that ContextWeb tries to understand the context of the content on a webpage to serve a better ad, PlaceIQ is looking to better understand the context of a place to serve a more relevant mobile ad to folks at that location, not based on the content within a mobile site or app, but on the geographic space surrounding the customer at that time.  Taking it a step further PlaceIQ, similar to companies like Magnetic and aCerno,  will look to extend that knowledge of place to using information about historical presence at places to better target advertising via re targeting… like a mobile ad for a Derek Jeter jersey targeted to someone who attended a game in Yankee stadium a few days earlier.

Just knowing that a person is at a given latitude and longitude alone may turn out to be about as useful as knowing someone is on the web… and from an advertisers point of view, pretty low value. But if that latitude and longitude can be resolved to a place, and a ton of other information assigned to that place, then a new rich dataset for targeting and re targeting across the mobile and geoweb will evolve with location and presence at its center.

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