It's Time To Start Respecting Our Data

Marketers, like most professionals, are eager to leverage the potential of data. According to DialogTech, more than 82% have expressed the need to use metrics to demonstrate their campaign's return on investment. Unfortunately, more than half believe that metrics do nothing to improve their efforts or drive their business, and these suspicions aren't entirely unfounded.

During his September 2017 keynote speech at Advertising Week in New York, Mark Coffey, SVP of strategic operations of GasBuddy, spoke about the proliferation of data and how its mere presence doesn't guarantee impact. A deluge of data, in and of itself, offers brands no competitive edge, and often, Coffey argued, it leaves them even more challenged to reach and connect with consumers.

I'm confident the problem isn't the data itself — but how the data is used. Measurement for the sake of measurement is useless, and incorrectly applied metrics only inflate marketing budgets unnecessarily. Costs may rise, but conversions won't follow.



The immediate impact is ineffective campaigns. But when metrics are incorrectly applied and interpreted, it also funnels investments into campaigns built on false premises. Rather than being an asset, data proves to be an ongoing impediment.

What Does It Mean to Respect Our Data?

Data is expensive to track, store, and analyze, and marketers aren't eager to bet their reputations on a poorly planned campaign. That begs the question: If data promises so much, why does it deliver so little?

I know from personal experience that applying data to marketing is both intimidating and overwhelming. Even a modest campaign generates a huge number of data points and a massive amount of overall information. Just 15 years ago, the average consumer used two touchpoints when choosing an item, according to Marketing Week. Today, consumers use an average of six.

Diving into a sea of data is daunting, but it takes a holistic approach to marketing to understand what's working and what's not. A survey by Aspect found businesses that adopt an omnichannel approach experience 91% better year-over-year retention rates — which isn't surprising considering 90% of customers expect consistent experiences across channels.

Those who focus on the entire marketing mix ultimately experience the best results. The goal is not to limit the amount of data being analyzed, but to simplify the process of analysis. Respecting data means acknowledging that individual elements have value but that the synthesis of those elements is what ultimately determines success.

Going Small

For marketers to use data successfully, I believe we must reject a one-size-fits-all approach and begin developing individualized strategies. I call this "small data" because it focuses on identifying the unique elements that make all data relevant.

It starts by questioning every assumption. Individual metrics claim to reveal something specific, but we can't assume that all data is a perfect indicator. The goal is to identify the metrics that are most indicative within the context of a specific campaign.

A zero-based approach to planning is also crucial. We must align our campaigns with the conversion cycle, then determine the fewest number of tactics necessary to achieve the desired result. It could be more or less than our last campaign. But what's important is that the approach is specific to this campaign, not based on precedents or presumptions.

Finally, we must identify the single metric that will indicate the success or failure of the campaign. It may take multiple metrics, but the fewer, the better. The goal is to streamline the information we look at and focus attention on the most impactful indicators.

As marketers, we're not doing ourselves any favors by applying the wrong metrics or including too many to our campaigns. It's time to drill down and respect our data.

1 comment about "It's Time To Start Respecting Our Data".
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  1. James Smith from J. R. Smith Group, November 17, 2017 at 10:42 p.m.

    Ian; Thanks for sharing the insights. Regarding, single or "fewer the better" success metrics...we might differ.  The relentless push for ROI as the dominant metric, while understandable, is often counterproductive in the longer run.  Today's data-sphere is complex and analysts continually strive to make sense of it...or so we would hope.  Do you think we also need to focus on educating C-suite execs regarding oversimplification?

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