Using Retention Analysis

Retention Analysis Usage Tips

Retention is commonly analyzed based on simple visits, but it can also be analyzed based on key user behavior events (events) in the product, such as sign-up, subscription, or purchase. Checking retention for each key funnel in the product you want to track lets you discover insights different from Funnel Analysis.

1. Acquisition

What is the daily retention rate for users who revisited the service in the last 7 days?

Selecting Any Event counts all events aggregated by Hackle, making it suitable for measuring 'visits'.

• Start Event: Any Event

• Goal Event: Any Event

• Period: Daily, last 7 days

  • Setting the period lets you view the basic D+3 retention and D+7 retention, and you can also view events for a specific period. Alternatively, for services with long visit cycles, you can view weekly/monthly retention.

Data configuration

Data query

Retention shows whether users who triggered the [Start Event] at Day 0, Week 0 also triggered it in subsequent Days or Weeks. You can interpret this by referring to the table below.

How to read Retention

2. Usability

How can I view daily retention after sign-up?

When you want to view retention after a specific action, set the [Start Event] to get the data you want.

Data configuration

• Start Event: signup

• Goal Event: any event

View data

You can view the aggregated periodic retention as shown below.

Based on user count (volume), you can check the unique user count and retention (%). The higher the retention, the darker the shading of each table cell.

How often do users perform a specific action (like, send message, follow, etc.)?

Depending on the characteristics of the service, you can select critical events that you monitor closely—such as likes, send message, follow, search—and view their occurrence frequency.

Data configuration

• Start Event: Any Event

• Goal Event: e.g., favorite, click_follow, complete_subscribe, etc.

• Depending on the service characteristics, you can set user attributes that are important to monitor. For example, you can view by user membership tier or by specific region. e.g., User Group > country = America

3. Purchase/Payment

How does daily visit retention differ between all users and paying users?

To view the retention of user segments with different characteristics, you can analyze metrics by adding 'User Groups'.

Analysis Items

• Start Event: Any Event

• Goal Event: Any Event

User Groups

• 1 All users

• 2 Users who completed a purchase

  • Event: Select the event that confirms purchase completion (e.g., complete_purchase)

  • Period: Set last N days

  • Count: Set N or more times

View data

• You can see at a glance the difference in retention metric (%) between the two groups—all users and paying users—for the same return visit retention.

What is the weekly repurchase retention for users who visited the service in the last 30 days?

Depending on the Goal Event setting, you can check the frequency of a specific event. For example, selecting a purchase event lets you check the purchase frequency.

Metric configuration

• Start Event: Any Event

• Goal Event: Purchase completion event (order_complete)

• Period: Weekly, last 30 days

User Groups

• 1 All users

• 2 Paying users Users who have made at least one payment in the last 30 days

View data

You can see how often all users and users with a payment history make purchases, as shown below.

The query period and interval can be changed according to your service's characteristics.

How can I see whether users who came from a specific path or campaign actually made a payment?

In this case, setting the path or UTM you want to aggregate in the Start Event counts users based on those who triggered that event.

Data configuration

• Start Event

  • Event: Any Event (all events occurring)

  • Property: UTM users or specific event

    • You can separately select only users who came through marketing via utm source, utm campaign, etc.

• Goal Event: Purchase completion event

View data

• You can check as follows the number and frequency of actual payment completions among N users acquired through marketing. If you want to reflect the promotion period, you can select a specific date. For services with long purchase cycles, weekly/monthly viewing is recommended.