Rishad Tobaccowala, media guru, tells us we have entered the age of data driven marketing. Tom Davenport says it’s about competing on analytics. Gartner defines data driven marketing as…acquiring, analyzing and applying information about customer and consumer wants, needs, context, behavior and motivations.
And yet, the typical marketer and marketing researcher should say, “Yeah but this is all high level stuff. What does this really mean? What should I do differently to be data driven?”
One concrete way of understanding this is by thinking through how differently advertising works in a programmatic vs. traditional ad world.
Imagine a consumer comes to a website that creates an impression serving opportunity which the publisher will put out for real time bidding. Very limited information is passed along with the bid request other than some identifier. TOTALLY HYPOTHETICAL EXAMPLE (I DO NOT CURRENTLY WORK WITH EITHER COMPANY)…let’s say that this user prefers whitening toothpastes, is a male millennial, and is a social single. Now here is the first tectonic change in marketing…it is incumbent on the advertiser to know this…by building a database that contains this user’s ID and where this information has been attached because the publisher does NOT pass along this information into open exchanges. (Cookie syncing required but I won’t get into the tech stuff here). So let’s imagine that Procter knows all this about this user so an ad served to them for Crest 3D Whitening products is a valuable opportunity. Let’s say this same user is NOT in the Colgate database; then Colgate will know NONE of this! They will probably not bid on the impression, and Procter will win this opportunity that was just as valuable to Colgate if only they had the user in their database. If this happens over and over again because Procter has a more serious commitment to competing on data, the competitive advantage just from data-driven marketing becomes huge. Furthermore, the advantage can widen over time because whether or not that user responds to the ad can be added to their data profile.
Why is this a tectonic change? Because in traditional advertising processes it was not the responsibility of the advertiser to know the audience. That was the responsibility of the media company to know their audience through their own research and syndicated research that was viewed as currency. All the advertiser needed to do was specify a target population, using demo based. With the rise of programmatic buying, it is becoming the ADVERTISER who must know and actually build their own audiences based on user knowledge and cherry picking the impressions they want to bid for.
To compete effectively in a data driven age, the advertiser must commit to five things:
- A technology stack that will handle this massive data load and act on it in real time
- A content marketing and service strategy that turns the advertiser into a media company so they collect their own first party data at scale
- A data partnering strategy to expand their knowledge of users and increase the reach of users they know something about
- Replacing media budgeting and planning processes based on hunches with evidence wherever possible
- A marketing research team that connects survey data to digital, social, and mobile information in every way possible so brand strategy can be connected to tactical media implementation
As a lifelong researcher, point 5 is particularly important to me so let me expand on that. In a digital age, it is market research’s responsibility to make sure that their marketers stay strategic at all times, while executing tactically on data to maximize the yield of marketing activities. It is the job of research to enable this magic trick. The three biggest areas needing reinvention are segmentation research, brand tracking, and new product testing. Segmentation research must be redesigned so that segments are created with digital profiling data as part of the analysis. If the segments are not findable for digital advertising they are not very actionable, and probably were beguiling but wrong in the first place as they cannot differentiate behaviors. In terms of brand tracking, there are two areas for reinvention. First, brand health cannot be completely captured by survey results. You need digital and social KPIs that reflect how much consumers choose to seek out your brand, which in turn, drives financial performance. I have urged my clients to stop referring to ”brand tracking”, and start thinking of it as “brand guidance” which is what marketing really needs. I was gratified that Coca-Cola, with whom I consulted, adopted this name change in redesigning their global “brand guidance system” and that others are now approaching me actually using this new terminology. When you think “guidance”, it will also focus you on the future. Predicting the next quarter is more important than reporting on the last quarter. Also, by matching digital and social profiling characteristics into survey respondents and analyzing which characteristics most differentiate those who are responding to your digital advertising you also get a new view into the soul of the brand in a way that will directly lead to adjusting ad targeting strategies for improved ROI. Volumetric concept testing is perhaps the biggest laggard of all. We think the forecast is the end goal. No, generating successful levels of trial is the goal! Research must create targeting strategies by creating what I call “Concept acceptors at scale” (CAAS) by appending digital, social, and shopper data profiling information to such testing so messages and offers can be precision-targeted.
Market research might think it has always been data driven but it really has been study driven in a data poor world. Now, in a data rich environment being data driven takes on a whole new level of meaning that marketing research must understand if it is going to remain relevant.