It goes without saying that smartphones have radically changed the marketing landscape. One of those changes is the capacity to determine whether and how digital ads are affecting foot traffic into stores. Location data collected from mobile devices also offer a range of other benefits: audience and operational insights, competitive benchmarking and more.
Yet, despite these capabilities, location data and offline attribution are still not widely utilized. I recently talked with Neil Sweeney, founder and CEO at Freckle IOT about the current state of location intelligence, offline attribution and where things are headed in the near future.
Greg Sterling: How widely adopted is offline attribution today?
Neil Sweeney: I think it is maybe 5 percent [of brands, retailers] at most. Those that are adopting offline attribution, if they are, are doing so using a standalone channel (i.e., Google) and not holistically across the board.
GS: What are some of the other current use cases you’re seeing for location data, beyond offline attribution?
NS: Audits are probably the second largest. If you are a retailer and want to know who is in your location — irrespective of media — on Monday afternoon, in a specific store, how do you measure this?
In short, you don’t. Retailers are in hand-to-hand combat right now and are in desperate need of this real-time data so they can make more intelligent decisions.
Another thing I am seeing is location data being used as a baseline in the creation of segments, which is a completely intellectually bankrupt model. Segments are the equivalent of branding, a feel-good tactic with no science behind it. They won’t succeed due to their inability to determine their overall effectiveness in driving a sale (that is what attribution does).
GS: Which marketing channels are currently most aligned with offline attribution?
NS: Digital by far the most: desktop and mobile. This makes sense, as those in this vertical are the most data- and measurement-savvy and have experience working with DMPs and third-party measurement firms, such as viewability vendors, etc.
As you get down the tunnel of traditional media, your implementation tends to fall off. Outdoor is interesting. The industry has been buying a non-real-time, self-reported number for way too long, and this is ripe for disruption.
Search is also starting to take form due to the overall spend levels going into search, but its challenge is the dominance of one firm.
Terrestrial radio and TV are the hardest, but both of these mediums are moving to an OS model where that AM signal in your car will be replaced by an app that will allow for attribution to take form. The same goes for TV.
In short: All channels are moving toward offline attribution but at different speeds. They will all end up in the same spot. When they all embrace attribution down each channel, is when it gets sexy; that is when the data science really needs to kick in. This is the part that I am excited about.