NATALIE BOKENHAM: It’s the year [the] personal data consumers are sharing about themselves will ultimately create a rewarding experience for consumers. I think communication will become a lot more personalized. Google Now is a great example. It’s a feature on the Android operating system that sends you personalized messages related to where you are and what you need to be doing in the next few hours based on things like current traffic conditions and weather conditions or mashing up a ton of public and personal data to serve you the most relevant possible messages. You can’t advertise yet on Google Now, but consumers are getting used to receiving messages in this way and we think brands will need to think about delivering messages in a timely, relevant way that’s data-driven.
You rely on data for client advisement. Can you expand on that?
Catalina Marketing Solutions developed a prototype for an app [Scan It! Mobile] and we’re working closely with them and showcasing their prototype in our lab. It’s live in [the supermarket chain] Stop & Shop. They provide data that helps inform our thought leadership and we help feed back to them thoughts on what clients are saying [and they share with us] what they learned through their mobile app. It’s a partnership, really, and potentially if we have a client that their solution might make sense for, we’ll talk to them about how we can create a custom opportunity or some kind of business development opportunity for them or they can proactively come to us about how we can activate that for our brands.
How does that app work in the physical environment?
The idea is that Catalina knows everything about people’s point of sale purchase data and they see the future of grocery purchases in mobile. They can’t determine how long it will take to get to that point, so they’re testing this out now to see what triggers make people want to use it, what kind of threshold for offers and content do you need to actually drive people to use it? Ultimately, the app allows you to purchase as you browse.
You scan a barcode on your product, you add it to your shopping basket and you essentially pay as you go. Catalina is trying to create a more seamless purchase [process] with the consumer, [and] to personalize the purchase experience in real-time for that consumer, like real-time offers based on their likes and purchase history as well as their location and what they just bought. It’s taking the data trove they already have on shoppers and adding in a real-time layer in order to serve them up based on where they are and what they’re doing in a store at the time.
What else has been developed through the lab recently?
We tend to showcase examples of technology we think are indicative of trends to come, but we’ll also showcase things we think are likely to grow. In terms of things we helped to develop, a great example is a project we did with the New York Times, which is a product called Spark.
The New York Times is one of the media owners that hired the lab to come up with a new marketing vehicle that would appeal to brands and we came up with Spark to enable brands to buy influence on the New York Times and a new ad unit that pulls in the top ten trending stories on Twitter at any one time. The ad unit is constantly being refreshed with the Top 10 Trending Stories and Top 10 Influential Stories on the New York Times at any one time as was determined by what was happening on Twitter.
What did you learn and how will you apply those learnings to other media developments?
It was essentially this new way to buy media and creating a way to buy influence as opposed to just impressions or popularity or just buying a unit on a publisher homepage. We thought influence was the most important thing about the New York Times and we did research amongst our own media planners to see what they valued most from the brand. It was the strength of its brand and influence over other news entities. So how do you harness all that influence so the brands could actually align with that influence? There was a disconnect between what the New York Times stood for and what you could actually buy on the New York Times.
In addition to developing emerging ad units, you conduct in-depth research, such as report The Second Screen Fallacy, which looked at TV/mobile viewing habits. Is client budget really being allotted to second-screen buys?
On average, 70% of our clients’ budgets across Mediabrands are spent on TV. That’s on average, so some spend far more or far less, but on average that’s remained quite stable so obviously the living room is of keen interest to everybody, as are what are the changing behaviors in the living room and how can we begin to mobilize to take advantage of these new opportunities and what are the threats that we need to be aware of?
This seems to go beyond just a second screen.
We really tried to look at underlying drivers of why things are happening. Is it really just a living room behavior or is it something that’s much bigger? I think it’s mobile-first. It’s not about one screen, two-screen, three. Just to give you an example, Michael Masters, the cofounder and CEO of Adtonik looks at TV as a screen or data [source] that helps inform his mobile targeting and I think that’s what multi-screens do at the end of the day. They inform each other. Mobile can inform outdoor. Vistar Media has created as close to programmatic digital out of home as you can get. They’re using the mobile device to personalize digital-out-of-home.