The promise of mobile local advertising continues to invoke the “closed loop” idea. The device’s portability and location awareness means that it goes to the store with you – enabling all new ad performance tracking opportunities. Nothing terribly new there.
But it seems like the tech and media worlds are finally acknowledging that 93% U.S. retail spending happens offline. And an increasing share of that — to the tune of about $1.5 trillion — is influenced online and on mobile. So connecting those dots is the name of the game.
Local offline conversion tracking also isn’t new of course — having roots in various coupon formats over the years. And the last decade of digital media has brought us closer to conversion tracking and ROI assessment using proxies like clicks and phone calls.
Mobile payments is the next evolutionary step that’s materializing, and I just released a report on the state of the industry. The short answer is that it holds lots of promise but it’s gated by lots of fragmentation, adoption issues, and competing standards in its early days.
In the meantime, we’re seeing new players start to redefine a sub-sector that ties together loose ends in mobile local advertising: attribution. This comes along just in time for (or a result of) the age of big data. It’s an offshoot of the intersection of mobile-local and data.
It involves measuring ad performance by tracking users’ real world behavior after an ad exposure or engagement. I’m now in the middle of a related research paper in tandem with Verve Mobile and am finding that the science is developing into three main areas:
Offline Purchase Data
Including mobile payments already mentioned, this involves using offline transaction data to close the loop on measuring ad effectiveness. Moving parts include disparate ad networks, retailers and payment processors who all have to “talk” to one other. This makes it a fragmented and underdeveloped field, but one with much promise to draw direct correlations between ad spend and offline purchases. In the meantime, companies like Datalogix are extrapolating this correlation with Facebook and Twitter. And card-linked offers piggyback on an existing credit card infrastructure and entrenched consumer use case.
Location Data Analysis
This involves tracking users’ spatial behavior after ad exposures to see if they came within proximity of a store. Examples are Verve’s Foot Traffic Index, Place IQ’s Place Visit Rate, and JiWire’s Location Conversion Index. These are effective in that some are vertically integrated with an ad network or offering. But that’s also part of their downside: Is there a conflict of interest (or at least a perceived conflict) in that ad networks inherently have a vested interest in reporting higher performance?
Third Party/Panel Data
Swooping in to solve the credibility issue, third parties like Placed and Nielsen administer panels of mobile users. Their ad exposures and subsequent physical world behavior are tracked to derive pattern analysis and insights about ad effectiveness. This is similar to the online panels tracked and administered by comScore except out in the “real world”.
These are all at various stages of developments and clearly have unique benefits and drawbacks. Like many things, the answer could come down to of situational factors and individual campaign objectives. The right answer is usually a combination of methods. Looking ahead, a fourth unofficial category (or offshoot of the first category) is indoor mapping and engagement. This takes local search to the next horizon: inside stores. The idea is to influence users at the key engagement point where conversions happen.
Pioneered by companies like Shopkick and quickly filling in with startups and standards like Apple’s iBeacon, this covers the last mile (or inch) to the cash register. Besides customer service and loyalty, this has implications for the ad attribution topic at hand. It picks up where the steps (literally) in the “path to purchase” end – the front door. If you think about it, attribution can’t get much better than covering the un-tracked last few inches to the cash register. Offline ad attribution will be a term you’ll start to hear a lot more.
Mike Boland is senior analyst at BIA/Kelsey, where he heads up the firm’s mobile local coverage. Previously, he was a tech journalist for Forbes, Red Herring, Business 2.0, and other outlets.