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3 Tactics for Reading Customer Data

Jacob Brain


With mountains of customer data to analyze, you may feel the need to have “big blue” in your back corner to crunch the data to get any valuable information or insights. Reading customer data can reveal many interesting things, yet you don’t need a super computer or a team of nerds from MIT to get value from your data. Here are some tactics using a simple spreadsheet program that can provide big insights into your customer data.

Group by X

Sometimes the biggest insight is a matter of perspective. And a good way to change perspective is to change the way your order or group your customer data. You might be looking clearly at profit and margin of your customers. But what if you grouped them by frequency first, then looked at profit? What if your grouped them by product category? Any column in your customer data can be used as a grouping column and may provide insights. Sometimes, seemingly insignificant data points actually have a bigger influence than you might expect.

Creating Cohorts by Scoring

You might have a lot of variation in your customer data, which could make creating cohorts within your data a bit tough. A good solution to this is to score relevant data points, and create your cohorts from those scores. It simplifies the reading process and allows you some flexibility to explore the data.

Look at the Outliers

Taking averages of your data makes great board room and presentation material. But what about those outliers? Why is this one customer spending so much with you and this one, so little? What do they have in common, or not? If you had 10,000 customers, you could take the top ten and the bottom ten and gain a lot of insight around their behaviors alone. The polarity of their profiles should provide obvious data points and actionable insights. Combine this tactic with the group by tactic, and you can really start to chop up the data in new ways to glean insights.

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