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    You are at:Home»Technology»Why legacy media mix models are failing marketers — and what should replace them
    Technology

    Why legacy media mix models are failing marketers — and what should replace them

    TechAiVerseBy TechAiVerseMay 3, 2025No Comments3 Mins Read3 Views
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    Why legacy media mix models are failing marketers — and what should replace them
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    Why legacy media mix models are failing marketers — and what should replace them

    Sponsored by Keen Decision Systems  •  April 30, 2025  •

    Bradley Keefer, CRO, Keen Decision Systems

    Legacy media mix planning software remains widely used across agencies. These tools offer a structured process and a game plan marketers can follow, but they were built for a media environment that no longer exists.

    Traditional media mix tools rely heavily on surveys and reach curves, which can’t account for modern channels like OTT, influencer marketing and retail media. This rigidity and dependence on outdated data sets make it difficult for them to keep pace with the current marketing and economic landscape.

    As a result, marketers are working with tools that offer direction but little precision — a poor fit for a landscape that demands speed, flexibility and real-time decision-making. 

    Marketers need to invest in planning tools that account for how media actually impacts their brand. This means moving beyond static assumptions and investing in platforms that account for diminishing returns, channel interactions and external market conditions.

    The importance of understanding diminishing returns

    Traditional models don’t account for the diminishing returns of ad spending. For instance, if a retail brand wants to allocate its entire Q3 budget to Amazon Prime Day, a traditional model might fail to recognize when the investment stops producing meaningful gains. Modern tools that analyze spend efficiency by channel and week, accounting for a brand’s uniqueness, can help marketers find the optimal level of investment before returns drop off.

    Another blind spot in legacy systems is their treatment of channels in isolation. These models often overlook how one channel might influence performance in another, leading to lopsided investments. Their rigidity prevents cross-channel testing and results in inaccurate evaluations of how channels interact.

    By adopting more advanced tools, marketers can better optimize their media mix, aligning spend with performance and improving ROI. These tools help ensure an ad budget reaches its potential, reduce waste and identify cross-channel halo effects. For instance, a social campaign might boost email sign-ups that later lead to conversions. Understanding these ripple effects helps marketers see how channels influence one another and avoid misallocating budget based on siloed results.

    Marketers also need planning tools that account for brand velocity and the realities of their operating environment. With ongoing uncertainty around external factors like tariffs, advertisers may need to adjust their channel mix or scale back spending quickly. Traditional models often lock budgets for months, limiting the ability to respond to market shifts. This leads to wasted spend and leaves brands trailing more agile competitors. Tools that support continuous testing and scenario planning give marketers the flexibility to adapt in real-time, shifting from reactive to proactive. For example, a CPG brand facing rising costs might reallocate its budget to trade coupons to help offset consumer price increases.

    The modern marketing environment demands planning tools that move at the speed of the market. Platforms that plan down to the dollar, channel and week provide the real-time insights needed to build smarter, more responsive campaigns. By layering external datasets with brand-specific data, marketers can create customized, tactic-level plans based on category, revenue tier, media spend and past performance. This approach replaces static direction with dynamic strategy — helping campaigns stay relevant, efficient and tied to real outcomes.

    Sponsored by Keen Decision Systems

    https://digiday.com/?p=577185

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