Measure for Measure Blog

Reports to Insights: Why We Do Analytics

Written by Andrew Edwards on . Posted in Digital Analytics

analytics insight

Digital analytics can be compared to an electrical current waiting for a device to which it can supply power. Like electricity, it can be a marvelous thing. But if there’s no lightbulb, there’s no light. All you’ve got is an outlet in the wall and a monthly bill.

Analytics insight is both the lightbulb and the light that shines from it. In the light, you can see what you’re working on and decide what, if anything, needs to change. Without insight, you might as well leave everything as-is, because in the dark, you might break something while trying to fix it.

Analytics is much the same. A great way of defining a useful report is to know whether you would change anything, depending on what the report said. Would it matter if you shone a light?

Much analytics reporting remains murky and not especially enlightening. And much of that has to do with ill-defined reports, data inaccuracy, and diffuse goal-setting.

The first steps towards insight are:

  • Narrow your scope of measurement. The tool will capture lots of data, it will do that by default. But what really matters to you? As noted above, what would you do differently if you had an answer to your question?
  • Define the most critical measurements. For instance, do you need a visitor to view a certain page, or click a certain link in order to make them a viable prospect or gauge their activity a “win” or a “conversion”? Focus reporting on that specific goal. You’ll still have lots of other data–but for this one goal, you need an answer.
  • A report will let you know whether your desired action was a success. Surrounding a specific nugget of information you will want to know such things as: what pages led them there, and which ones did the best/worst jobs?; what landing pages started their journey?; what campaign got them to the most successful landing page?

The most elusive part of “insight” is: what to do different now that you have the data! This won’t be found in the numbers. It will be a series of decisions based on how best to improve what’s not working, and how much of a chance to take on improving what seems to be working best.

Insight from analytics requires carefully thought-out reports, accuracy, correlation of data, the ability to visualize and synthesize; and some understanding of statistical concepts. Tools will provide about half of it. Predictive algorithms may, at times, deliver their own insights–often as to messaging with existing content. But real insight is the domain of the individual with access to good reporting plus the ability to take a chance on a new approach when it is most needed.

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