Gartner Marketing Data and Analytics Survey: Adapt to Automation

By prioritizing skill development, marketing and analytics leaders can enable analytics teams to complement, rather than be threatened by, automation.

Marketers invest sizable resources in analytics, but many aren’t getting the payoff they expect. The Gartner Marketing Data & Analytics 2020 survey shows that analytics influences only 54% of marketing decisions. The top reasons for this are poor data quality, results that are not actionable and unclear recommendations.

And yet, marketing executives see huge potential for analytics. Eighty-five percent of those surveyed said that by 2022, “significantly more” of their organization’s marketing decisions will be based on marketing analytics.

But to extract more value from analytics, marketing leaders must focus on building skills that address the reasons analytics are seen as underperforming — and concentrating on value-adding analytics activities outside those that are or soon will be automated.

“It’s critical to invest more time and resources in upskilling your analytics team to have a broader influence over bottom-line results and adapt to new trends in automation,” says Lizzy Foo Kune, Senior Director Analyst, Gartner.

Few data and analytics teams are proving their worth

Marketing analytics teams currently spend too much time on low-value tasks, such as data integration and formatting, ad hoc queries and requests, and generating reports and dashboards — activities that are ripe for automation.

Gartner survey of marketing analytics teams' time spent on activities in 2018 and 2020.

More than half (56%) of marketing leaders expect the size of their analytics teams to stay the same or shrink, but that likely reflects the perceived value — or lack of value — contributed by analytics teams today.

Only 23% of marketing leaders cite skill development as a top priority for their marketing analytics teams, down from 39% in 2018. And marketers who say their analytics teams have not had the expected influence are more than three times as likely to be planning to reduce the size of those teams over the next two years.

The three most-cited obstacles to analytics teams’ success are manual data preparation, connecting analytics to business value and connecting analysis to insight. Automating manual and repeatable tasks will enable analytics teams to focus on more value-adding activities, such as developing actionable insights from data.

Focus marketing analytics skills development on value-adding activities

Analytics teams looking to thrive alongside automation should prioritize skill development in value-adding activities such as advanced modeling, consultation and persuasive communication. This will enable analytics teams to expand the breadth of their influence and the depth of their impact.

“Reprioritizing your analytics effort to complement automation will elevate marketing analytics to a higher-value function that serves as a critical strategic partner to the CMO,” says Foo Kune.

The shift to automation is well underway. In the Gartner data and analytics survey, 43% of respondents say that “reporting needs are met through automated dashboards” frequently or almost always. In addition, half of the respondents currently have a customer data platform (CDP) that helps automate first-party data collection and profile unification. Over the next three years, 79% of respondents expect to have a CDP deployed.

By upskilling their current capabilities to support analytics automation, analytics teams can deliver the return on investment that marketing leaders expect.