How CMOs Are Getting Past The Hype About AI By Finding The Practical Use Cases

It's still "early days" for AI, says Forrester analyst Thomas Husson, who reports that only 36 percent of global marketing decision makers actually use machine learning tech.

Despite rising calls for more regulation of how companies like Google, Amazon, Facebook, and the platforms that run on them harvest, manage, and deploy consumer data, the actual use of artificial intelligence and the data that powers it in marketing remains in the early stages, a Forrester report outlines.

The report, Artificial Intelligence Will Spark A Real Marketing Renaissance, notes that Only 36 percent of global marketing decision makers say they use AI. Meanwhile, 42 percent of marketers don’t see the need to use AI as another 41 percent say they don’t know how to use it.

Even when they do, 38 percent concede they lack the resources to make the most of AI tools. As such, “few brands — even those in media, insurance, and retail — have a mature AI approach,” concludes the report’s main author, Forrester VP and principal analyst Thomas Husson.

Just as CMOs have accepted the need to adopt “mobile-first” strategies, marketers now feel pressure to immediate add machine learning and more automated data programs to their mix.

While the “hype” around AI technologies, particularly the use of chatbots and automated personalization tools are still perceived as being more about experimentation and not being left behind when these programs become more mainstream, Husson’s report points to clear, practical ways of employing AI in a substantive way.

For one thing, AI can help address three clear challenges facing CMOs who are trying to impact real-world actions:

Data and analytics “crisis”: 40 percent of marketing leaders who responded to the Forrester global survey of 1,138 executives, say that increasing the use of data and analytics is top priority over the course of this year.

“For marketing, one of AI’s strengths is its ability to connect the dots within volumes of data in ways that human analysis is unlikely to discover without a team of data scientists,” Husson writes. “Marketers must supply AI-powered systems with accurate, updated, diverse, clean, and complete data. Then AI can iteratively search for insights so CMOs can take advantage of immediate benefits like personalization, insight detection, dynamic content optimization, and marketing automation.”

— Talent: Roughly 50 percent of global marketing decision makers point to recruitment and retention as a big headache, particularly when it comes to hiring and keeping data scientists. As Forrester notes, even recent graduates can command as much as $250,000 a year. Apart from compensation, brands must offer a productive, digitally innovative working environment. Interestingly, firms are even deploying AI techniques in recruiting, an approach that’s bearing fruit: Google uses AI to help deal with the 2 million resumes it receives annually.

— The Scale Question: The perennial question of marketers whenever it comes to an emerging technology. Is this a tool that can work for only a small amount of customers? Is it possible to run a particular program across channels, or will it be siloed by particulars (mobile versus desktop versus TV versus voice activation). “AI-powered martech can ingest data and customer context from multiple systems, deploy self-learning models that go beyond static predictions or machine learning, and activate brand interactions across touchpoints,” Husson writes. “AI can provide the scale CMOs need to create the contextual experiences customers demand — something that continues to be elusive as content and channels proliferate.”

In terms of bringing a “renaissance” for brands, agencies, publishers, and platforms, the primary role for AI is on freeing executives up to think and plan.

“Marketers waste too much time on manual processes,” Husson writes. “AI-powered tools will enable CMOs to improve the productivity and efficiency of their teams.”

He cites Sephora’s experience of to being able to free up resources in its marketing team by using machine learning to deliver automated, accurate e-commerce sales for its French website.

Or as the report quotes Jean-Baptiste Bouzige, the founder and CEO of French data science consultancy Ekimetrics, “By applying AI to offline and online data, we’re helping the CMO of an automotive brand to optimize its marketing mix modeling and anticipate its evolution to maximize each dollar spent.”

About The Author
David Kaplan David Kaplan @davidakaplan

A New York City-based journalist for over 20 years, David Kaplan is managing editor of A former editor and reporter at AdExchanger, paidContent, Adweek and MediaPost.