Why CFOs Overlook Marketing's True Impact | AdExchanger
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Why CFOs Overlook Marketing's True Impact | AdExchanger
"But that wouldn't happen if marketers had access to better measurement that gave them clarity on what truly drives business growth, argues Henry Innis, CEO and co-founder of marketing mix modeling platform Mutinex. "We don't have a perception that marketing is a growth driver in the boardroom," Innis says on this week's episode of AdExchanger Talks. "That's the tough truth for most marketers; we're seen as a fungible cost.""
"Obtaining that clarity can be expensive and time-consuming, though. Traditional MMM models look backward, focus mainly on media spend and frequently require bespoke rebuilds. Mutinex uses an AI-based MMM system that draws on a wide range of business data and automates data processing so advertisers get insights more quickly and with less manual effort. More streamlined measurement tools set the stage for difficult but necessary conversations about marketing's true value."
"In other words, since marketing is closely linked to revenue growth, cutting marketing spend should logically lead to lower revenue expectations. If only CFOs would see it that way. "To get to that point," Innis says, "you don't just need a pretty dashboard with a bunch of ROI charts; you need well-governed, reproducible models that can stand up to financial scrutiny and audit.""
Marketing is often perceived in the boardroom as a fungible cost rather than a growth driver. Traditional marketing-mix-modeling (MMM) approaches look backward, focus mainly on media spend, require bespoke rebuilds, and can be expensive and time-consuming. AI-based MMM can ingest a wider range of business data and automate data processing to deliver faster insights with less manual effort. Well-governed, reproducible models are necessary to withstand financial scrutiny and link marketing spend to revenue forecasts. Clearer, auditable measurement enables honest conversations about budget cuts, and AI-assisted MMM can reduce human error and bias.
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