What marketing and research must do differently in a data driven age
Through a special arrangement, presented here for discussion is an excerpt of a current article from the Joel Rubinson on Marketing Research Consulting blog.
Gartner defines data driven marketing as "acquiring, analyzing and applying information about customer and consumer wants, needs, context, behavior and motivations."
However, the marketer and marketing researcher should ask: "But what should I actually 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.
Consider this hypothetical example: Imagine a consumer comes to a website that creates an impression-serving opportunity, which the publisher puts out for real time bidding. Very limited information is passed along with the bid request other than a user identifier. Let’s say that, in reality, this user prefers whitening toothpastes, and is a male Millennial. It is up to the advertiser to know this about the user by building a database that attaches this profile information.
Let’s imagine that Procter & Gamble knows this and 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 so Colgate knows none of this. P&G will win this opportunity that would have been just as valuable to Colgate if only they had the user in their database. If this happens over and over again, P&G’s competitive advantage just from data-driven marketing becomes huge.
Why is this a tectonic change? Because in traditional advertising processes advertisers buy the right to advertise to an audience accumulated by the media property. It is the responsibility of the media company to know their audience through their own proprietary and syndicated research. With the rise of programmatic buying, it is now the advertiser who must know and actually build their own audiences and choose the impressions they want to bid for.
To compete effectively in a data driven age, the advertiser must commit to:
- A technology stack that will handle this massive data load and act 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 valuable about;
- Replacing hunches with data science as the basis of media planning;
- A marketing research team that connects survey data to digital, social and mobile information so their brand strategy can be connected to tactical media implementation.
How do you see consumer brand advertising working differently in a programmatic versus traditional ad world? How well equipped are CPG marketers today to use data driven marketing approaches?
Camille P. Schuster, PhD.President, Global Collaborations, Inc.
Camille P. Schuster, PhD.President, Global Collaborations, Inc.
Camille P. Schuster, PhD.President, Global Collaborations, Inc.
Camille P. Schuster, PhD.President, Global Collaborations, Inc.
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4 Comments on "What marketing and research must do differently in a data driven age"
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The world is certainly changing and new approaches and skills are needed. Hiring data scientists and adjusting strategy is essential and it seems that all CPG companies are scrambling to implement these changes — with varying degrees of success. One thing that I see far too few organizations working towards is democratizing data across their organization and giving people beyond the marketing and analysis teams the opportunity to understand data and use it to their advantage.
Today’s analytical environment is different from what has been done in the past for many reasons. First, the amount of data is huge. Second, data is available from many different departments in the organization. Third, analysts need to start with and focus on business questions. Research for the sake of research is not helpful. Fourth, the data does not provide answers. While the data can be used to understand relationships and identify typical behaviors, it does not reveal strategic business decisions. Fifth, analysts who can interpret the data and make a link with strategic business decisions are critical for success. This is a job category for which there are not enough qualified people, so … Sixth, companies need to recruit, hire, and/or train qualified analysts.