Understanding customers begins with the basics


Aggregation takes a set of data and pulls it into a single value.

For example, the number of unique active users over the last 30 days, or the total number of times a given product feature was used in the last week. When viewed over time, aggregated metrics show a trend of changes in customer behavior.


Segmentation lets you define a group of customers by some characteristic.

For example, accounts with MRR over $2,000, or users that have used a certain product feature in the last week. You can then view aggregated metrics over just the customer segments you are interested in, allowing you to compare and contrast these segments.

Aggregation and segmentation are a good place to start for any customer analysis. They give you a rapid understanding of an account, and allow you to test assumptions.

For example, you can compare and analyze the differences between successful accounts (e.g. those with a good health score) and accounts that are at-risk (e.g. those with open red alerts).

  • How frequently does each group use the product?

  • Do they use different feature sets?

Identify factors that affect success within segmentation

You might discover that certain features used mainly by successful customers provide more value, and initiate campaigns to drive usage of those features by other customers.

You can dive even deeper using segmentation analysis to analyze sub-segments of your customers.

  • How do healthy and struggling customers compare within industries?

  • Does product usage differ by geography or customer tier?

  • Do users submit more tickets at different points in their customer journey?

Understanding the factors that affect success within different segments allow you to create action plans that more directly target those customers' issues. You can even compare an individual at-risk account to similar accounts (e.g. same industry, stage, size) that are doing well to develop recovery strategies.

Map the profile of successful customers

Aggregation and segmentation can also help Customer Success Managers understand the profile of successful accounts.

  • Do healthy, active accounts tend to come from certain lead sources?

  • Do they use the product in different ways than other customers?

  • Are they of a certain size or in a specific market or geography?

By understanding the profile of successful customers, you can help your marketing team target more customers like these. Understanding and focusing acquisition programs on customers who are more likely to succeed with your solution can accelerate the growth of your company. 

The challenge of effective aggregation and segmentation is the vast amount of data there is to explore. Over time, Customer Success teams will develop intuitions that will speed this process, while data-driven CSM solutions like Natero will help provide additional insights.