A curious thing about the OMMA Data and Behavioral conference we hosted on Wednesday in New York: There was a lot of talk about the limits and caveats surrounding data. One of the objects of this iteration of the show series (which began on the very day in 2007 that AOL bought Tacoda) was to widen the lens from strictly behavioral targeting to that larger field of digital data of which behavioral targeting is a part. “Big data” was the dominant trope throughout. But it was fascinating to hear our speakers discuss, again and again, how data needs to be used judiciously, in concert with creative intelligence and consumers.
Tom Morton, Chief Strategy Officer of Euro RSCG, made the case for “poets” in an age of quants. “Big data still needs big interpreters,” he said. Quantification is inevitable, but targeting needs a brand voice -- and creatives need to understand how to use all this data.
The first panel of the day on media planning in an age of data underscored the need for understanding data’s limits. Jason Leigh of Razorfish argued that sometimes a data layer just isn’t worth the cost and added effort -- we need testing to determine when it really matters. The panelists cited Netflix as an example of a vendor that probably does well simply by making massive, low-cost buys everywhere. Even with the waste of missing targets, the price differential may not be worth it. Sometimes spray and pray works, Stewart Pratt of SapientNitro said. Morpheus Media's Toby Evers reminded us that finding the “right audience” is not enough if the person you are targeting is not in the right spot in the purchase funnel for your message.
The idea that data has the capacity to build new products, allowing companies to work more transparently with consumers to get them involved, came through during the “Predictive Analytics” panel. Duncan McCall, CEO of PlaceIQ, said that he felt once consumers themselves become more aware of and in control of their own data trail then the industry can really become productive: “Once we bring the consumers in on this, the world is going to change.”
Interestingly, C-K's Killian Schaffer picked up on McCall's point and called it “data liberation... Once consumers start realizing that their data is valuable, I am really interested to see what the ecosystem will look like [where] we figure out some exchanges where people will raise their hands and say,'You can use my information – feel free to market to me.'”
The role of the consumer in cooperating with data exchange was an interesting offshoot of this panel. Rachel Pasqua, who leads mobile at Organic, made the wise observation that the iPhone is doing a great job of accustoming people to opt-in. Any time an app needs to access the phone’s geo-location capabilities it must ask permission of the user. This is a little thing but significant, since it signals to the user that a specific benefit (usually more precise information about nearby resources or mapping) is the result of this exchange of data. As Pasqua pointed out, this gets people in the habit of opting in -- and seeing a demonstrable benefit from doing so.
Of course this sort of conscious data exchange requires that brands answer in kind. The pressure is on the publisher or the brand to deliver something of value directly tied to the data points being shared. PlaceIQ, for instance, uses the attributes of a location to infer a user's likely intentions in order to serve the right ads. Someone coming out of a bar is likely to be looking for fast food, as opposed to someone doing a search from a gym two blocks away.
Byron Reese, who leads innovation at DemandMedia, followed up on this theme of data as a creative agent in society in his fascinating presentation. He asked us to imagine a world of data created by limitless sensors attached to everything -- where virtually everything we do, from eating to walking, consuming media to sleeping, can somehow be captured. In this world, we will see wild affinities and correlations that beg for explanation.
He suggested, much as Tom Morton did, that the mountains of data are a challenge to the creative intelligence to craft new ways of thinking about the world around us. The data requires interpreters and creative types who can turn the inferences about cause and effect into new products and services.
One of my takeaways from this week’s show is that as we start moving from discussing “behavioral tracking and targeting” and towards “data” writ larger, the discussion becomes energized with more possibilities.
The predictive analytics panel is available in the stream here.
Byron Reese’s talk is here.
Tom Morton’s keynote is here.