Marketing Metrics: The Emperor Has No Clothes!

Clip books, impression numbers, web hits: who believes them? Maybe no one, according to a study reported on by AdAge. Such metrics are commonly used as indicators of ROI, but, according to survey findings, “the problem is that CFOs don’t seem to buy the CMOs’ claims” and meanwhile, “marketers don’t believe their numbers either.”


One example: “Only one in 10 marketer respondents said they could forecast the effect of a 10% cut in spending.” Why? Most approach marketing as an art, rather than a science. Sure, who wouldn’t want to know the relative value of a radio spot vs. a TV campaign vs. a guerrilla marketing effort. But, there are so many variables: how to separate out the power of the message itself, the state of the economy, or the impacts of other campaigns running at the same time? Hard stuff. As a result, many simply default to familiar strategies and metrics, making adjustments around the edges based on logic or intuition.

Indeed, “perfect” ROI evaluations can be demanding and costly. But opportunities abound for “good enough” approaches that are practical to implement, more likely to earn respect from executive management, and actually provide useful marketing insights. A few examples:


  • Simple tracking. Charting discrete marketing efforts against contemporaneous sales can, over time, reveal valuable trend information to guide decisionmaking and estimation.

  • Replace “reach” with “customer value.” When considering a marketing investment, weigh the cost against the value of the desired sales outcome. Even if this requires highly speculative assumptions about response rates, engaging in “what-if” scenarios can be a powerful tool for revealing weaknesses of traditional strategies.

  • Targeted testing. Tracking trends and modeling what-if scenarios will often reveal key questions worth spending some additional resources on answering. Designing “surgical strike” pilot studies or sampling efforts will limit their cost and complement your tracking and modeling efforts

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