> ## Documentation Index > Fetch the complete documentation index at: https://moengage-user-guide.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Behavior Analysis # Step 1: Define Events An event refers to any action a user performs on your app that is tracked. You can add up to 10 events simultaneously. Screenshot 2025-01-02 at 12.43.32 PM.png Each event can be further filtered using **+ Attributes**. Add event filters for specific actions performed by users such as Platform, App Version, and so on. 2025-01-02_12-48-01 (1).gif Use **+ Attributes** again and combine multiple attributes using **AND**/**OR** for each event. For example, use the **OR** filter to combine data across two platforms. If you want to get data for a specific platform and look at the visits to a specific website, use the **AND** filter. 2025-01-02_12-54-33 (1).gif With **Split by**, you can compare the data using a specific attribute. To compare, click **+ Split By** and select the attribute from the list with which you wish to compare. You can add a maximum of 10 attributes. For example, to obtain a chart for the number of songs played across different platforms. Select *product\_viewed* as the event and select *Platform* in the **Split By** list. Screenshot 2025-01-02 at 1.09.29 PM.png You can add a maximum of 10 events to your behavior chart using **+ Add Event**. # Step 2: Filter Users By default, you can perform behavior analysis on all users. However, you can also query for a group of users filtered using User Properties, User Activity, User Affinity, or Custom Segments. Filtering users is similar to creating a segment. For more information, refer to [Create Segment](/user-guide/segment/segment-operations/create-segments). 2025-01-02_13-25-45 (1).gif # Step 3: Choose an Analysis Option After defining your events, you can choose how to calculate the data. The following options are available: Screenshot 2025-01-02 at 5.19.16 PM.png * **Total events**: This option provides the total count of selected actions or events performed by the user. * **Unique users**: This option provides the number of distinct users who have completed the selected event. * **Total events per user**: This option provides an aggregated count of the total events per individual user. For example, you can get the average number of songs played per user. The aggregation types available are shown below: 2025-01-02_18-04-36.png * **Unique sessions**: This option provides the total number of unique sessions in which the selected event was performed. * **Aggregation**: This option aggregates the count of the selected event or action. The supported aggregation functions are sum, minimum, maximum, average, median, percentile, and distinct count. The aggregation option is available only for numerical attributes. 2025-01-02_17-37-39 (1).gif You can aggregate attributes of an event. These attributes are available in the list after selecting your aggregate function type. The available attributes depend on the defined events at the beginning of the analysis. For more information on advanced Behavior options, refer to [Advanced](/user-guide/analyze/analytics/behavior/advanced-behavior-analysis). # Step 4: Select the Comparison and the Duration In addition to the ability to split an event by attributes, you can also compare all selected events based on common user attributes using the **Compare by** option on the **Behavior Options** tab. For example, you can compare the number of successful orders placed by users of different subscription tiers. Screenshot 2025-01-03 at 12.08.46 PM.png You can select a maximum of 10 attributes, including the **Split by** attributes.\ After choosing the *Compare by* attributes, specify the duration of the analysis. Screenshot 2025-06-16 at 3.41.28 PM.png # Step 5: Choose Charts After your query is generated, choose your preferred visualization type. You can change between Line, Area, Bar, Column, and Pie charts. Every chart has its own significance. * Line charts are widely used for analyzing data trends, changes, or patterns. They are frequently used to display and compare data over time. Screenshot 2025-01-03 at 12.29.51 PM.png Line charts can be viewed in the following ways: LineChart_LiLoCum.png * **Linear**: The chart displays data with a continuous line. * **Logarithmic**: The chart scales the values on the Y-axis to logarithmic values. * **Cumulative**: The chart will accumulate all values up to the most recent period shown in the chart. * Area charts combine a line chart and a bar chart to show how data changes over time. These charts show how one or more groups' numeric values change over time. They are often used to show trends in data, such as the growth of revenue. Screenshot 2025-01-03 at 12.51.06 PM.png * A bar or column chart is a graph used to compare different measures across various data categories or series. Screenshot 2025-01-03 at 12.58.53 PM.png Screenshot 2025-01-03 at 12.59.43 PM.png * Pie charts are commonly used to visualize categorical data that can be divided into distinct parts. They display the relative proportions or contributions of various categories within a whole. Screenshot 2025-01-03 at 1.00.54 PM.png Line, area, column, and bar charts are scaled relative to percentages using an absolute number or a percentage. You can switch between numerical and percentage views for line, area, bar, and column charts. AbsolutePercentage.png ### Granularity You can also break down the report into Hourly, Daily, Weekly, or Monthly granularities for easy visualization. Based on the granularity you select, unique users will be displayed. gran.png Behavior chart 2.gif ### Compare to Past This will allow you to compare the current chart with past trends during behavior analysis. You can compare any data point over a period of time with the corresponding data point from the previous period. 2025-01-03_13-17-17 (1).gif You can compare the chart for the following periods: * Previous Day * Previous Week * Previous Month * Previous Quarter * Previous Year * Custom Range # Step 6: Tables In addition to charts, the data is also available for analysis in a tabular format. You can sort the table or change its view using the transpose feature. Additionally, you can download the data in CSV format. For more information, refer [here](/user-guide/analyze/analytics/getting-started-with-analytics/overview). Note that the analysis will only display 10,000 rows in the table. You can only see 10,000 rows on the dashboard and after exporting the data to CSV. # Save to My Studio or Custom Dashboard Your analysis is now ready. To access this later, you can save the analysis. To save: 1. Click the icon in the upper-right corner and click **Save to My Studio.** 2. Additionally, you can save the analysis to a custom dashboard. Choose the required option from the list. Screenshot 2025-01-06 at 3.35.49 PM.png 3. Select the dashboard where you want to save the analysis. You can choose an existing dashboard or create a new one. Screenshot 2025-01-06 at 3.39.23 PM.png 4. Enter a name for your analysis to help you identify. 5. Enter a brief description of the analysis. 6. Click **Save**. You can access the analysis by navigating to **Analyze** > **My Studio**. To access the custom dashboard, navigate to **Dashboards**. # Next Steps * [Advanced](/user-guide/analyze/analytics/behavior/advanced-behavior-analysis) * [My Studio](/user-guide/analyze/dashboards/my-studio)