Marketing tech is changing the world. And marketers are getting left behind



Credit: Bernard Goldbach, Flickr

In an early episode of Mad Men, Don Draper spars with a researcher about the value of the customer insights she’d collected. Don argued that creatives need to show the future, not the past, and that data couldn’t show a brand where to go.

Marketing has evolved a lot over the last 50 years. Data now commonly informs copy, and marketers often test and improve creative concepts before launching broadly.

One of the most important changes has been the introduction and evolution of marketing technology, or martech. These systems provide measurable feedback on ad performance and streamline marketing processes. And marketing groups are seeing the value of martech: Martech aficionado Scott Brinker reports that marketing departments now spend more on martech than they do on advertising.

Yet as martech gets more common and powerful, there’s an ongoing gap between what it can deliver and what companies are getting from it. A lot of it has to do with the Don Drapers of the world — strong creative leads who rely on instinct more than anything else—and a largely unchanged organizational structure that revolves around the opinions and ideas of those creatives.

When data and systems contradict what a creative person thinks or how she wants to work, too often the baby gets thrown out with the bathwater.

The analysis gap

 Once a martech system is up and running, marketing groups will be flooded with data. They need to have people and processes to deal with it.

Eighty percent of companies now have a marketing-technologist role, according to a recent survey by research firm Gartner. And yet, there’s still a analysis gap: Four in 10 businesses recently reported that their lack of appropriate analytical skills were a key business challenge, according to MIT Sloan Management Review. Employees either know marketing and lack analytics skills, or they have analytics skills but can’t fully call out the marketing implications.  

Imagine a sales funnel where engagement with a series of Web pages slowly pushes readers from awareness to consideration to purchase. While some marketers live and breathe the funnel and the assets, they may not understand how to interpret consumption data. And data owners aren’t familiar with the funnel. Even before convincing Don Draper of data’s value, there’s a lack of people who have a combination of quantitative and marketing skills.

One of the reasons for this is that marketing departments are not integrating data analysts into their critical processes. While more and more marketing departments are embracing agile marketing—the idea that the best results come through a process of constantly testing and iterating—organizational structures and internal processes still tend to be designed to facilitate the development of creative work and its path to launch.

The upshot is that analysts and technologists aren’t asked to answer the questions that can most impact creative and effectiveness and, lacking this dialogue, they don’t always know what the critical questions are.

This creates another problem. Marketers don’t usually have time to explore all of the new features of a fancy new martech system. And the people closest to the system don’t have enough practical experience to convince their colleagues that the new system closes an important capabilities gap.

Many features go unused, and the new system fails to move the needle in a meaningful way.

Another legacy of Don Draper is that marketers are rewarded when an activity launches, not when it’s iterated upon. This means that developing and applying data insights—parsing through results and finding opportunities to improve ongoing marketing activities—is at the bottom of the list of priorities, if it makes it on the list at all.

This obviously represents lost opportunity to improve performance that drives revenue. And when combined with the current trend toward agile marketing, the damage is worse. Agile marketing is powerful in that it removes the tendency to overplan and engineer perfect marketing without customer feedback. It cuts creative development costs and shortens development time. But it’s founded on the notion that ideas can improve through launching early and iterating. When this data-informed iteration is removed, ideas remain in their minimum viable stage.

Cross-discipline collaboration

We can gain a lot by getting more out of today’s systems. The first step is to work across groups, share learnings, hear what others are saying, and collaborate to find a mutually acceptable solution.

For example, marketers and martech vendors can work more closely together: marketers can share where they’re struggling to gain engagement or operate more efficiently, and martech vendors can explain exactly how their systems can help. And on the other side, data scientists and marketers can collaborate more: data scientists already recognize the need for people who understand how to access and use data, and are also fluent in business and marketing needs. If organizations can create opportunities for marketers to work more with data owners, both sides will improve the insights they can get out of analytics. These opportunities may look like a carrot organizations make data scientists more available to marketers or they may look like a stick, in that performance may depend on moving metrics.

Finally, the Don Draper role can use data to add fuel to his intuition. Whether in agencies or in-house, creatives and designers can be a powerful force when they work with analytics owners to tease the nuances out of data. The insights gained can spark great ideas and strengthen the power of existing ones.

The more that marketers can adopt these practices in a meaningful way, the more they’ll get out of their martech investments.

This post first published on The Huffington Post.

Topics: agile marketing, marketing strategy, publishing, martech, marketing technology

Katherine Ogburn, Director of Strategy

Katherine Ogburn, Director of Strategy

Katherine builds foundations for brands and marketing programs, and helps clients define marketing goals that are grounded in business needs and user-centric audience views. While much of her recent work has been for large companies such as Google, Intel, iShares, General Motors, and Microsoft, she also enjoys helping define identities and competitive differentiation for startups and small companies. Prior to Ready State, Katherine worked at MRM, McCann, FCB, and McKinsey. She has a master's in business administration from Columbia Business School, a master's in sociology from the University of California at Berkeley, and a bachelor's in Russian studies from University of North Carolina at Chapel Hill.