Detailed Scenarios for Cohort Analysis

This article provides in-depth scenarios for key metrics in cohort analysis, focusing on both single-user and multiple-user cases. These examples illustrate how individual users and groups appear in Loyalty Rate and Conversion Rate analyses, offering a clearer understanding of these metrics in action.

Loyalty Rate Analysis Scenarios

The Loyalty metric tracks the percentage of new visitors who return over subsequent time periods, helping assess user re-engagement.

Single User Scenario

In this scenario, we follow a single user who visits the website or app multiple times, illustrating how their behavior is represented within the Loyalty Rate metric.

User Behavior
The user makes three visits:

• First visit: January 5

• Second visit: February 2

• Third visit: April 1

Analysis Representation

The image above shows this user’s visit dates and how they appear within the loyalty analysis. Although these visits span three calendar months, the metric uses a time span of 30 days, meaning that the January and February visits fall within the same Month 0 category because they occur within 30 days of each other. This demonstrates that “monthly” here refers to a 30-day period rather than strict calendar months, with the third visit in April categorized under Month 2.

Multiple Users Scenario

This example expands on the single-user scenario by adding a second user to create a more realistic cohort. This demonstrates how multiple users with varying visit dates are represented within the Loyalty Rate metric.

User Behavior

• User A: (same as single-user scenario)

  • First visit: January 5

  • Second visit: February 2

  • Third visit: April 1

• User B:

  • First visit: January 11

  • Second visit: February 13

Analysis Representation

The image above shows how both User A and User B appear in the loyalty analysis. Although these visits span multiple calendar months, the Loyalty Rate metric uses a time span of 30 days.

Conversion Rate Analysis Scenarios

The Conversion Rate metric tracks the percentage of users who complete a conversion (e.g., make a purchase) over time since their first visit, providing insights into how quickly new visitors engage in conversions.

User Scenario

In this scenario, we track a single user’s conversion behavior across four visits.

User Behavior

• First visit: January 5

• Second visit: January 7 (includes an order)

• Third visit: February 8

• Fourth visit: March 10 (includes an order)

Analysis Representation

The image above shows this user’s visits and orders, illustrating how the Conversion Rate is calculated for each month based on the number of orders and visitors within specific time spans:

• Month 0 (Days 0-29): Conversion rate is the number of orders divided by the number of unique visitors for that month. In this case, there is one order and one unique visitor, resulting in a conversion rate of 100% for Month 0.

• Month 1 (Days 30-59): Since there is a visit but no order, the conversion rate for Month 1 is 0%.

• Month 2 (Days 60-89): With one order and one visitor in Month 2, the conversion rate is 100%.