The Secret to a Genius Marketing Analytics Organization

April 29, 2019
Contributor: Heather Pemberton Levy

By studying 10,000 job postings, Gartner experts uncovered how Genius brands create successful marketing analytics organizations.

CMOs continue to list analytics as a top priority for their marketing organizations. Yet some organizations still lose their data scientists because they haven’t adequately supported them with data engineers. Or they haven’t yet learned the crucial need for data interpreters.

At Gartner Marketing Symposium/Xpo™ 2019 in San Diego, Christi Eubanks, Managing Vice President, Gartner for Marketers, and Jonathan Gibs, Chief Data Officer, Gartner for Marketers, shared the secrets of how genius brands build their marketing analytics organizations. The “secrets” were distilled by a Gartner TalentNeuron™ analysis of 10,000 job postings from the Gartner L2 Digital IQ Index, which benchmarks 3,000 brands across 30 categories with 1,250 data points per brand. Not surprisingly, job postings requiring analytics have risen from 27% in 2010 to 34% in 2018 according to Gartner TalentNeuron data.

In the Gartner L2 Digital IQ Index, brands are assigned to one of five classes: Genius, Gifted, Average, Challenged and Feeble. How do Genius brands organize their marketing analytics teams to achieve digital marketing success?

“Since 2007, we’ve seen a lot of hiring for senior roles,” Eubanks said. “Not much has changed.”

Historically, most companies organized and operated by channels and platforms. But there’s a difference between how you organize and how you operate. Today, however, modern organizations are moving toward individual strengths, empowered decision making and an agile framework.

Feeble brands invest in a heavier management layer. Genius brands put their hiring weight into more workers in technology, analytics, and with a stronger strategy bent. They align their operational model to their data stack.

“Genius organizations aren’t hiring more managers,” Eubanks said. “They’re hiring more people to get the work done.”

Gartner research finds that brands it classifies as genius brands align their operational model to their data and analytics stack.

The data study also showed three sets of emerging data and analytics skills: Data engineering, data science and advanced engineering, visualization and reporting.

Gartner research shows three sets of data and analytics skills have recently emerged: data engineering, data science and advanced engineering.

“We’ve seen flatlining in market research and web and marketing analytics,” said Gibs.

For example, Domino’s Pizza looked for someone to spend half their time on cross-channel reporting and insights. The company wanted a person to execute all phases of analysis and understand data quality, one who could also build bridges across teams to get the right data sources.

Skills change doesn’t equal higher salaries

While the organizational needs remain the same, the skills have changed. Organizing data becomes data engineering, analyzing data turns into data science, and socializing data shifts to data visualization. For more examples, look at the evolution of top skills keywords in the last four years (as shown below).

Gartner outlines the evolution of top marketing analytics skills keywords from 2014 to 2018.

Gartner: The evolution of top marketing analytics skills keywords from 2014 to 2018

If you’re worried that more sophisticated skills spell higher salaries, the Gartner experts made it clear this isn’t the case. The technical skills skew towards more junior talent. In fact, Genius brands focus on hiring more emerging skills and sequence the skills to create a pipeline of data to enable reporting it.

“Make sure you start with data engineering, like the Genius brands, and layer it up from there,” said Gibs. “If you start with the data scientists, they’ll end up trying to wrangle the data and then leave.”

“The lesson is to build your foundation first and then to advance your analytics.”

The role of the interpreter

Genius brands also realize the need to pair strategy with data and invest more in interpreters as well as analysts. The role of the interpreter requires a strong marketing and business knowledge base in order to connect data to value and help communicate insights to leaders.

Once you’ve established a plan for your desired skills and roles, start looking within your team or across the organization as the skills may already exist and merely depend on new career pathing strategies.

Read more: Design the Right Marketing Organization for the Next Decade

You may also be interested in
“I use Gartner to bolster my confidence in decision making.”

Stay smarter.