Improved technology has escalated the tension between brand-building and performance marketing, but it has also led to a resurgence of marketing mix modeling (MMM).
Improved marketing technologies are increasing the challenges of balancing creativity and performance, says Matt Andrew, partner & general manager, Americas at Ekimetrics. The platform helps leading brands around the world optimize their commercial decisions to create sustainable competitive advantage, through solutions that understand customer value, and maximize media, trade and promotional activity.
Better reporting means more demands on marketers to show results, but as more media budgets flow into programmatic auctions and algorithmic platforms, the learning about what works isn’t staying with the brand, but being absorbed by artificial intelligence models to the marketers disadvantage.
“As AI-enabled buying takes a bigger and bigger share of media, the learning is moving to the algorithm, not to the business,” Andrew says. “Businesses are more and more reliant on the algorithms getting better, rather than on knowing themselves as a business.”
“Marketers need to know what will drive incremental growth, how to allocate media and promotions and how to optimize the balance to react to the marketplace and stay relevant in a fast moving environment,” says Andrew. He noted research has found 50% of CMOs say proving marketing impact to the C-suite is their number one challenge, but at the same time 73% of CFOs don’t believe marketing drives measurable business.
These dynamics are leading to a “resurgence” of MMM, Andrew said. He noted all the marketing leaders Ekimetrics works with want to know what drives incremental growth. They want to strike the right balance between product innovation, promotions and pricing activity, loyalty, media spending and all the other factors that come into the marketing mix, he said.
Triangulating inputs
Technologies such as AI have made measurement more fraught, because marketers are not getting the same visibility about what their media dollars are doing, when algorithms now handle many media decisions, he said. The speed and scale of AI has also created higher expectations for every dollar spent on marketing.
“It’s made the conversation about how you create demand in the long-term a lot harder, because there is this expectation that every impression should deliver an effect immediately,” said Andrew.
Technology has also contributed to the siloing of marketing organizations. As staffers need to specialize, it falls to leaders to look at the big picture, said Andrew.
“You have to be pretty senior before you start even thinking about: How do I steer both the brand and the performance? Because there’s so many people with very specific roles,“ said Andrew. “The group of people that are saying: ‘How have we constructed our marketing so that we’re building a healthy brand in the long term?’ is a very small group of people. It’s hard to inject that mentality across teams that are set up in very functional, specific ways.”
Leadership has engaged in “triangulation” of data management including econometrics and MMM to identify opportunities, run experiments to test-and-learn and monitor in real time to optimize campaigns. Real-time campaign management sets a base for allocating budgets and maximizes the business impact of every piece of activity through the year, he explains. This creates a “learning agenda” for the entire organization that embraces both performance and brand-building, says Andrew.
“It’s not how do you drive one or the other, but how do you think about layering both together, and how do you construct the budget so that you have an execution for your activity that makes next year’s plan easier, and delivers on the needs now,” he says.
Because of marketing’s fragmentation, a good use of AI is to retain and leverage that organizational knowledge, acting as a memory bank for the enterprise — a useful task at a time when marketer tenures are brief, says Andrew. “There’s only so much that a human can keep in their head,“ he says.
The human factor
It is important not to cut humans out of the discussion, Andrew explains. Someone must be responsible for the ultimate decisions. A global marketer like L’Oreal isn’t going to let an AI agent decide a $10 billion budget is effective, he says.
“A human needs to take responsibility to say: Is this working? Is our business performing?” says Andrew. “In big enterprise businesses it’s always going to be the case that there’s a human that needs to be taking responsibility for the strategy and the direction that’s being taken.”
Additionally, humans have to make the call about whether a business decision is in the best interest of the brand’s long term equity, says Andrew. He singled out the case of LEGO, as an example of a company that is performing very well in spite of competing priorities.
The toy company has been delivering double-digit annual growth over the last decade, most of it is coming from adult audiences. However, LEGO still believes that “the kids are the heart of LEGO as a brand,” says Andrew. Even though they could make more money by accelerating their focus on adults, “the core is really important to them,“ Andrew explains.
It takes a human to decide to give up the short-term opportunity for the long-term belief of what’s going to make the company successful “over the next five, 10, 20 years—not just this year or this quarter,“ he says.
“I think the strategic content behind a company needs to sit with a human, for sure. And what doesn’t need to sit with a human — and I think that that’s really clear – is the translation of that strategy into the actual buying decisions,” says Andrew. “You get greater scale, you get greater efficiency, you get greater speed with AI agents, with AI auctions and AI buying methods. So the execution of a media plan, for sure, will become more and more AI-first. I think it’s something we’ll see and is happening already. But the strategy behind that needs to be human-led.”
Ultimately “every marketer needs to be concerned about growth and incrementality,” said Andrew, but he warns that “MMM is not a silver bullet that can do everything.” Triangulating the business around the learning agenda MMM leads to the long-term learning that builds strong business foundations, he says.
The result, he concludes is “focused not just on how do we deliver this year, but how do we do it in a way that makes it easier to achieve our objectives next year and the year after, build a healthier business over time and maximize the impact of every dollar that you have in the market right now.”
