# Metric Management Metrics are used for A/B Test result analysis and other purposes. Because metric measurement is required across many internal teams, the Metric Management menu is provided to help you manage a large number of metrics systematically. ## Creating a Metric Manually Click the **`Create Metric`** button in the top right of the **`Metric Management`** menu in the left navigation. ![](/files/IfxTsnYv6P2LUUTlfNGD) Clicking the **`Create Metric`** button displays the following dialog. Metrics are divided into **`Event Metrics`** and **`Time Metrics`**. Event Metrics measure whether a user performed an action or how frequently, such as purchase conversion rate, average click count, or average order value. Time Metrics are used to measure specific durations, such as time spent on a page or the time from order form to order completion. The setup steps for each are described below in order. ![](/files/rfZrq4fqpZma4lmmIsTi) ### Creating an Event Metric Clicking **`Event Metric`** shows the following screen. You can see the metric name, the metric configuration for defining the measurement method, and additional settings below. In particular, the metric configuration area lets you set the denominator and numerator of the metric separately. ![Create Metric popup](/files/VvoiF3lx8bD9libZwBqZ) #### Step 1. Enter Metric Name and Description Enter the name and description of the metric. #### Step 2. Data Configuration Configure which users to target and what data to analyze.\ Setting 'which users to target' is called **denominator configuration**, and setting 'what data to analyze' is called **numerator configuration**. 1. Numerator configuration\ An **`Event`** is required for configuration.\ You can select an existing event or create a new one.\ If you need help creating a new event, refer to the \[Create Event]\(../이벤트 관리/create-event.md) documentation. 2. Denominator configuration\ You can choose from 2 options. * All Users: Refers to all users who accessed the service * Specific Event: Refers to users who triggered the selected event. For example, if you enter 'login' as the event, it means you want to include only users who triggered the 'login' event among all users as the denominator. Note: using a Specific Event basis requires a paid plan of Pro or higher. {% hint style="info" %} Why are events needed? For example, a company is considering changing the color of a purchase button. To evaluate whether the change is effective, they created a data analytics chart to check the metrics 'Number of purchase button clicks' and 'Purchase conversion rate'. * To calculate 'Number of purchase button clicks', you need to collect the number of times users clicked the purchase button. Therefore, you create a 'purchase button click' event and aggregate the number of times that event occurred. * To calculate 'Purchase conversion rate', you need to find out how many purchase completions occurred. Therefore, you create a 'purchase complete' event and collect the number of times that event occurred. In this way, it is important to find out how many times the event related to a metric has occurred in order to determine whether the metric has improved. {% endhint %} {% hint style="info" %} How does entering an event integrate with the actual code? 1. When you select an event that was automatically collected via SDK integration\ In this case, you selected an event that already exists in the code, so data calculation is possible automatically. 2. When you select a manually entered event\ In this case, you selected an event that does not yet exist in the code, so you need to add that event at the desired location in your code and then start the test for smooth data calculation. {% endhint %} #### Step 2-1. All Users Basis All users who accessed the service are set as the metric denominator. You then configure the denominator calculation type and the numerator.\ For the numerator configuration, you can select the **measurement event**, **calculation type**, and **filter**.\ Results are provided based on the calculation type and filter conditions of the selected event relative to all users. ![All Users basis - Select event and calculation type](/files/PE1qnDuIDb7XFoHWAUkx) **Filters** help you set more detailed metrics by using user or event property information. For example, a fashion category manager at a commerce company may need to measure 'fashion product purchase conversion rate', and in this situation they can use filters to set the desired metric. In the filter's first field, select the desired user or event property. In the second field, select multiple desired values for the chosen property.\ Using AND conditions, you can set up to 5 filter conditions. {% hint style="warning" %} If you create a metric by selecting a filter, you cannot use the Data Segment Analytics feature. This feature is planned for future support. {% endhint %} When **All Users** is selected as the denominator, you can configure 5 types of metrics. | Numerator | Denominator | Description | Example | | ---------- | ----------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------- | | User Count | User Count | Calculates the ratio of users who triggered the selected event out of all users. | Purchase conversion rate, banner click rate, search conversion rate | | Count | User Count | Calculates the average number of times all users triggered the selected event. | Average button clicks per user, average purchases per user | | Value | User Count | Calculates the average value generated by all users from the selected event. | Average purchase amount per user | | Value | Count | Calculates the average value generated from the selected event relative to all users' visit count. | Average page loading speed (Latency) | | Count | Count | Calculates the average occurrence count of the selected event relative to all users' visit count. \* Note: Statistical analysis is possible only when all users' visit count is greater than the event occurrence count set as the numerator. | Average product page views per visit | #### Step 2-2. Specific Event Basis When you select the Specific Event basis, you must configure both the denominator and numerator. Filter configuration is also available if needed. In this case, you can select the event that serves as the denominator, setting either the users who triggered that specific event among all users, or the event occurrence count, as the denominator. ![Custom configuration - Set event occurrence and basis](/files/8LqAeftQyzqMZNOktOix) For the numerator configuration, you select both an event and a calculation type, just as with the denominator. However, for the denominator configuration, the available event and calculation type selections depend on which calculation type was selected for the numerator. Only cases where the user triggered the denominator event and then triggered the numerator event are included in the metric calculation. {% hint style="info" %} Only cases where the user triggered the denominator event and then triggered the numerator event are included in the calculation. When 'Specific Event' is selected, only cases where the user triggered the denominator event and then triggered the numerator event are reflected in the metric calculation. {% endhint %} ![When Specific Event is selected as the denominator - Calculated considering the before/after relationship between denominator and numerator event occurrences](/files/IDR1Rul72ra3CAK0jkDX) The metric types available when **Specific Event** is selected are as follows. | Numerator | Denominator | Description | Example | | ---------- | ----------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------- | | User Count | User Count | Calculates the ratio of users who triggered the numerator event after triggering the denominator event. | Purchase conversion rate vs. add to cart, button click rate vs. landing page entry | | Value | User Count | Calculates the average value generated from the numerator event after users triggered the denominator event. | Average purchase amount per buyer | | Value | Count | Calculates the average value generated from the numerator event after the denominator event occurred, relative to the number of times the denominator event was triggered. | Average Order Value (AOV) | | Count | Count | Calculates the number of times the numerator event occurred relative to the number of times the denominator event occurred. \* Note: Statistical analysis is possible only when the denominator event count is greater than the numerator event count. | Search result click conversion rate vs. search attempts | #### Step 3. Success Criteria The success criteria are selected to define the characteristic of the metric. For example, purchase amount is a metric where higher is better, while return count is a metric where lower is better. ![Enter metric description and select metric success criteria](/files/dYQh8vOqRAYjPqNS7q32) * **`Increase from baseline`**: When a **higher** metric value is better\ \*\* Example metrics: purchase conversion rate, search count, subscriber count, etc. * **`Decrease from baseline`**: When a **lower** metric value is better\ \*\* Example metrics: payment cancellation count, page loading time, etc. #### Step 4. Create Click the **`Create`** button in the bottom right to complete creating the metric manually.\ The created metric will appear in the Metric Management menu. ### Creating a Time Metric #### Data Configuration You need to define the interval you want to measure time for. This is configured in the numerator and denominator sections. 1. Numerator configuration\ Set the start point of the interval you want to measure as the 'Start Event' and the end point as the 'End Event'. * Example: Measure the time taken to complete the membership registration process. The Start Event can be 'entering the page to fill in membership registration information' and the End Event can be 'membership registration complete'. Below the start and end events, there is a section to set 'Calculation Conditions'. Only cases where the start event → end event is reached within the time set in the calculation conditions are reflected in the calculation. * Example: Measure the time from app open to order completion. In this case, order completions that do not occur within 1 hour of app open can be excluded from the calculation. 2. Denominator configuration\ Set the calculation type for the time metric. You can select either 'User Count' or 'Conversion Count', and selecting each measures the following metrics. * User Count: Average time spent per user (e.g., time spent in the service) * Conversion Count: Average time taken to complete a conversion (start event → reaching end event) (e.g., time from entering the order form to order completion) The metric name and additional settings are the same as for Event Metrics. ![](/files/pxUPoqr80XHt2RiuVtLa) ### Metric Detail Page Clicking a metric registered in the Metric Management menu takes you to a page where you can view its details. On the detail page, you can view or edit the following. * View the metric's denominator and numerator configuration. * View the list of A/B Tests to which this metric has been added. * Edit the metric's name and description. * Manage the metric's tag information. * When the 'Guardrail Metric' toggle in the top right is turned on, this metric is automatically added to the 'Guardrail Metric' section when registering metrics for an A/B Test. ![](/files/h0beW5buZ6AvkMKx0XXx) ### Deleting a Metric To delete a metric that is no longer in use, click the trash can icon in the top right of the detail page. ![](/files/5oAnsk0oe9X6ss9Mhh1k) Deleting a metric from the Metric Management menu does not affect metrics currently in use in A/B Tests or Data Analytics. 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