Identify the Metrics, Methods, and Tools for Your Customer Analytics Initiative

By Jeff Sauro

During this step in setting up your customer analytics initiative, identify the metrics and methods you’ll use to answer your questions and achieve your goals:

  • Look for metrics that are meaningful to customers. Think on-time arrivals instead of on-time departures.

  • Identify what tools you’ll need for data collection.

  • Consider collecting customer data by surveying existing customers. Even something as simple as surveying customers requires several inputs.

The table shows how you can go from question (from the preceding section) to metric to method, and finally to the right tools for the two examples of customer loyalty and findability.

Metrics and Tools
Question Metric Method Tools
Why aren’t customers recommending a product? Net Promoter Score Survey existing customers to understand their current
likelihood to recommend and identify the root cause of why they are
or not recommending
Survey software
Access to customers
*A method to invite customers
**A method to analyze the data
What labels need to be changed to improve website
navigation?
Findability rate Findability study using tree testing and card sorting Tree testing software
Access to prospective customers
*A method to invite customers
**A method to analyze the data

* This can be through email, after a transaction, via phone, or embedded into a product.

** You need software and people with the right skills to conduct advanced statistical analysis such as cluster or factor analysis.

You also need to understand your baseline scores. It’s hard to know if you’ve improved anything if you don’t have a baseline measure.

After surveys, customer transactions and purchase data are popular sources for finding baseline data. You need

  • Access to customer data: This is often guarded in organizations because it contains both sensitive company and customer data.

  • Transaction dataat the right level of detail: Total revenue by product is often at too high a level to understand what’s driving purchases. In many cases, you want to obtain customer transaction data at the product level. This way, you can understand who these customers are (demographics and so forth), when they made the purchase, for how much, and how often (for repeat purchases).

Some of the most important insights companies gain from their customer analytics comes from merging survey data with transactional data. One of the biggest challenges is being able to properly match customer survey results with past and future transactions. You may need the help of a database administrator or IT person to be sure you can merge survey data with transactional data.