The On Boarding Trend, the orange left arrow, indicates the product’s effectiveness in its first month of use and its trend over time which is nothing less than a metric for user on boarding effectiveness. The first cell in each column indicates the monthly active rate for the cohort’s first month as users. In our hypothetical data set, that number grows varies from 35% to 41% over time. The product team has done a reasonable job of improving user on boarding and engaging users when they sign up.

The Longitudinal Trend, the top red arrow, indicates how the activity rate changes as users continue to use the product. The first row is the oldest cohort of users with the most recent data, the ones who signed up most recently. The bottom row is the newest cohort. Time flows right in this chart.

In our hypothetical data, there are two important conclusions. First, our user base becomes less active over time and over the past 12 weeks, we see the activity rate falling, indicating the product isn’t keeping the attention of its users. Second, the decay in user activity is relatively constant across all cohorts meaning the product improvements over the past 12 weeks haven’t made an impact.

The Cohort Trend, the bottom yellow arrow, indicates the current contribution to activity of each of the cohorts. In our hypothetical example, the older cohorts contribute 1/10th the activity of newer cohorts. This means user re-engagement through marketing or product efforts should be explored in addition to finding new ways to retain users.

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