February 15, 2017 James Burke

Analytics 101: Measurement without Metrics

When businesses begin to talk about the idea of “measurement strategy” – behemoth that it is – goals very quickly fall out of focus, while metrics take center-stage.

This has been our experience and we love to talk about it.

Conversations swirl around KPIs, industry benchmarks, and percentage-improvement stakes. However, we work with our clients to help them answer the most crucial question, “what’s important to the success of my business?” We would tell you that your first measurement conversation should not even come close to touching on metrics. There is an inherent tendency to be consumed by the importance of analyzing data, to the point where the data begins to be seen as valuable in and of itself. It becomes easy to forget that the sole purpose of every brand experience is to feed a larger marketing funnel.

Businesses need consumers to be aware of their presence, and to understand their value proposition. They need to be considered, and ultimately purchased, in order to survive. These are what goals look like, and the usability of data hinges entirely on the context that these goals provide. As data-driven businesspeople, it is here that our focus should lie.

So, how can you take action on this thinking? We are glad you asked.

  • First, identify your business goals, and map them out as part of a marketing funnel or similar down-stream flowchart.
  • Next, list out the activities that you believe drive each goal. Examples of activities include digital advertising, CRM, sponsorships, and local events.
  • Thirdly, decide what success looks like for each activity. Avoid speaking in terms of metrics here; and instead articulate statements such as “we need to drive repeat purchase,” or “we need to push sales messaging to new people.”

With your success statements clearly outlined for each activity, you can begin to think about how to best map these statements to tangible data points. There is a new challenge that awaits you, in understanding how to map and construct your data infrastructure for effective and efficient use – but that is for next time. Stay tuned!


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