CMOs in the Crosshairs -- Can A Different Media Mix Restore Brand Growth?

Does personalized targeting / programmatic advertising really work? Legacy brand growth significantly slowed when the industry shifted from traditional to digital/social advertising fifteen years ago.

Credit: John Jonik, The New Yorker, The Cartoon Bank

CMOs have a tough and increasingly complex job, especially since the advent of digital / social advertising and the migration of media from traditional advertising to “personalized, data-driven advertising” from 2009.

CMOs turn over at roughly twice the rate of the CEOs to whom they report. According to Spencer Stuart's 2024 CMO Tenure Study, the average tenure of Chief Marketing Officers (CMOs) among the top 100 advertisers averaged only 3.1 years.

• A Gartner study of 125 CEOs and CFOs, highlighted in a 2025 article by Adweek, showed that 69% of the surveyed executives indicated they would consider removing a Chief Marketing Officer (CMO) who fails to deliver promised results.

• Nearly ten years ago, AdAge published an article “CMOs First on Firing Line When Companies Miss Growth Goals,” basing its findings on a 2016 Accenture Strategy study that found that 37% of CEOs say that the CMO is the most likely C-suite player to get fired when companies miss growth targets.

• Even the ANA is concerned. Bob Liodice, President and CEO ANA, wrote “Despite all of the creative and media transformation that has happened, advertisers are not growing” in an article titled Decades of Complexity Overwhelms CMOs published by the Growth Guidance Center in early 2023.

The brand / product growth problems since 2009 cannot be due 100% to CMO choices about media mix. There are other problems — competition from e-commerce, from private label products and higher relative prices for branded goods. Nevertheless, the dramatic shift of media mix cannot be discounted as a major factor.

CMOs are, of course, receiving a lot of advice from Procurement, Finance, Google (via DoubleClick and Admob), Yahoo (Right Media), Meta, Accenture, Deloitte Digital, IBM, EW, PwC and others who have a vested interest in seeing CMOs spend more on low-cost digitalization than on higher-cost brand equity building.

The metrics used to justify this shift involve not only the low cost per CPM but high numbers of “clicks” and indications of “purchase intentions,” which for some reason are always positive…even though actual sales have gone nowhere for 15 years.

CMOs are receiving bad advice from too many sources, and not enough insightful advice from those who can help them figure out what media mix might actually rekindle brand growth again.

CMOs need to reestablish their credibility by unlocking the key to product growth rates and following through. This will, most certainly, seem like a risky venture — success cannot be promised in advance, and marketing investment funds will have to be reallocated in different ways.

One hopeful development for CMOs is the emergence of professional service entrepreneurs who are developing AI agents to query large masses of data — marketing inputs and outcomes — to tackle the CMOs’ growth problem.

I have previously written about Mutinex, a marketing mix model developed by Henry Innis, which seeks to optimize brand growth through its analysis of a huge client dataset of marketing inputs and sales results.

Importantly, Mutinex offers an AI query function for CMOs who can ask such general questions as (this is a real example):

• Based on the last 3 months of data compared to the total dataset you have, what are the 3 critical issues I should pay attention to as it relates to business growth?

• Explain them and justify your rationale and provide me with a critical set of actions so I can brief my agencies and brand managers as to how they should start formulating a plan.

Many other entrepreneurs are developing AI agents that will help C-Suite Executives corral their corporate and marketplace data to make better, faster decisions without having to rely on the uneven and slow analytical performance of junior analysts.

One such company is ClearSpark AI, based in Vancouver, Canada, which focuses on developing AI capabilities for small businesses — allowing them faster, more sophisticated analyses of data through unstructured queries (like the Mutinex query, shown above).

CMOs need to jump on the bandwagon — they are under pressure to “develop AI capabilities in marketing,” whatever that means. What they should be doing is using AI to question their current marketing strategies and the poor results that have resulted from them.

Figuring out the answer is worth millions to their companies — and greater longevity and success for CMOs themselves.