kapa.ai How do I calculate average session duration per album
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To calculate the average session duration per album in Mixpanel, you'll need to use a combination of session tracking and property aggregation features. Here's how you can approach this: 1. First, ensure you have Sessions feature set up in your Mixpanel project. This will automatically generate "Session Start" and "Session End" events with a "Session Duration (seconds)" property.2. You'll need to track an album property with your events to associate sessions with specific albums. This could be done by including an album ID or name property with your events.3. In Insights, you can use the "Aggregate Property per User" measurement to calculate the average session duration per album: - Select "Session End" as your event - Choose "Aggregate Property per User" as your measurement - Select "Average" as the aggregation type - Choose "Session Duration (seconds)" as the property - Break down by your album propertyThis approach will give you the average session duration for each album across all users. If you want to convert from seconds to minutes, you can apply a formula to divide by 60 as mentioned in the Sessions FAQ.For a more detailed analysis, you could also look at the distribution of session durations per album using the "Distribution" aggregation option instead of "Average" to see if there are significant variations in how users engage with different albums.Remember that the accuracy of this analysis depends on how well your events are tagged with the correct album information during the user's session.
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kapa.ai How can I check my activated users and reactivated users?
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To check your activated and reactivated users in Mixpanel, you can use a combination of Cohorts, Insights, and the RAE (Reach, Activation, Engagement) framework. Here's how to approach this:
Tracking Activated Users
Activated users are those who have completed your product's key activation steps. To track them: 1. Define your activation metric: First, determine what constitutes "activation" in your product. This should be tied to your product's value moments as described in the RAE Framework.2. Create an Activation Cohort: - Go to the Users page - Set up filters based on your activation criteria (e.g., users who completed specific key actions) - Save this as a cohort named "Activated Users"3. Track Activation Rate: In Insights, you can measure the percentage of new users who become activated by: - Selecting your activation event - Using "Unique Users" as your measurement - Breaking down by "New User" or "First Time User" property
Tracking Reactivated Users
Reactivated users are those who were dormant but have returned to active usage: 1. Create a Dormant Users Cohort: - Define users who haven't performed key actions in a specific timeframe (e.g., 30+ days) - Save this as "Dormant Users"2. Track Reactivation: - In Insights, select your key activity events - Filter for users who are in your "Dormant Users" cohort - Use "Unique Users" measurement to see how many dormant users have returned3. Monitor Dormant to Active Percentage: As mentioned in the RAE Framework, tracking the "Percentage of Dormant to Active Users" is key for resurrecting users who have gone dormant.
Using Mixpanel's Advanced Features
For B2B products, you can leverage Account Analytics to track activation at the account level: - Use Activation Metrics to query "Number of users who did an action" aggregated by account - Create queries like "Show me accounts where users have 'logged in' more than 10 times" or "Only show me accounts with more than 2 'active users'"For deeper analysis, you can use Mixpanel's measurement options in Insights to track DAU, WAU, and MAU (Daily, Weekly, and Monthly Active Users) to understand your active user base over different time periods.By combining these approaches, you'll get a comprehensive view of both your newly activated users and those who have returned after a period of inactivity.I hope this helps! Let me know if you need more specific guidance on setting up any of these analyses.
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kapa.ai How to calculate for first-week engagement?
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To calculate first-week engagement in Mixpanel, you can use several approaches depending on what specific metrics you want to track. Here's how to set this up:
Using First Time Filters
You can analyze first-week engagement by using Mixpanel's First Time Filters to focus on new users: 1. In Insights, select your key engagement events 2. Add a First Time Filter to identify users who performed an event for the first time 3. Set your date range to include the first week after user acquisitionAs noted in the documentation: "You can do this by adding a First Time Filter to any event in Mixpanel. This filters the event down to only the first instance of the event performed by a user" Analyzing First Time Users.
Using Retention Analysis
For a more comprehensive view of first-week engagement: 1. Go to the Retention report 2. Set your initial event (A) as "Sign Up" or first app open 3. Set your return event (B) as your key engagement actions 4. Look at the Day 1-7 retention buckets to see how many users returned within their first weekYou can also switch to "Calendar Retention Mode" if you want to analyze engagement based on calendar weeks rather than rolling 7-day periods: "Calendar interval retention - Considers time intervals based on 'calendar' time" Calendar Retention Mode.
Using Frequency Analysis
To understand how frequently users engage in their first week: 1. Go to the Retention report 2. Switch to "Frequency" view 3. Set the interval to "Each Week" 4. Look at how many unique days within the week users performed your key actionsThis approach shows "how many users did the event 'Complete Purchase' on unique days in a week" Frequency View.
Measuring Active Users
You can also track first-week engagement through active user metrics: 1. Create an Insights report 2. Select your engagement events 3. Choose "Weekly Active Users (WAU)" as your measurement 4. Filter for new users onlyAs explained in the documentation: "The number of users who performed [event] within the last 7 days. Example: What's the count of users who watched a video in the week?" Measurements.By combining these approaches, you'll get a comprehensive view of how new users engage with your product during their critical first week, which is essential for understanding your activation success and predicting long-term retention.Would you like more details on any specific aspect of first-week engagement analysis?
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kapa.ai How to calculate the metric 'First Listen'?
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I can help you calculate the "First Listen" metric in Mixpanel. This would be considered a first-time event analysis, which Mixpanel has specific functionality to support.
Using First Time Filters
The most straightforward way to calculate "First Listen" is by using Mixpanel's First Time Filter feature: 1. In Insights, select your "Listen" event (or whatever you've named your listening event) 2. Add a First Time Filter to this event 3. This will filter the data to only show the first instance when each user performed the listen actionAs explained in the documentation: "You can do this by adding a First Time Filter to any event in Mixpanel. This filters the event down to only the first instance of the event performed by a user" Analyzing First Time Users.
Analyzing First Listen Metrics
Once you've applied the First Time Filter, you can: 1. Break down by properties to see what content users are listening to first 2. Analyze trends over time to see how many new users are having their first listen each day/week/month 3. Create funnels to see how quickly users progress from signup to first listen
Additional Analysis Options
You can also use this first listen data to answer questions like: - Which referrers do most first-time listeners come from? - How well do users retain after their first listen? - What events do users perform before and after their first listen?As noted in the documentation, "Mixpanel computes this on-the-fly by scanning each user's history to determine if this was the first instance of the event performed by the user, based on timestamp" Analyzing First Time Users.Would you like more specific information about any particular aspect of tracking first listens in Mixpanel?
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kapa.ai how to get the last seen for the users?
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I can help you understand how to get the "last seen" information for users in Mixpanel. This is a common need when analyzing user engagement patterns.
Understanding "Last Seen" in Mixpanel
In Mixpanel, the "last seen" information is stored in two ways: 1. As the $last_seen
user profile property, which is automatically maintained by Mixpanel and contains the timestamp when a user profile was last updated (not when they last performed an event)
2. As the last_seen
attribute in user objects when querying via JQL (JavaScript Query Language)
Viewing Last Seen in the UI
The simplest way to see when users were last seen: 1. Go to the Users tab in Mixpanel
2. Look for the "Updated at" column, which shows the $last_seen
property
3. You can add this column via "Edit Columns" if it's not already visible
Accessing Last Seen via API
You can export user profiles with their last seen data using the Engage API: LBKScurl --request POST \ --url '[https://mixpanel.com/api/query/engage?project_id=YOUR_PROJECT_ID](https://mixpanel.com/api/query/engage?project_id=YOUR_PROJECT_ID)' \ --header 'accept: application/json' \ --header 'authorization: Basic YOUR_TOKEN' \ --header 'content-type: application/x-www-form-urlencoded'LBKS
The response will include the $last_seen
property for each user profile: LBKS{ "results": [ { "$distinct_id": "user123", "$properties": { "$last_seen": "2023-06-09T23:08:40", // other properties... } } ] }LBKS
Exporting Profiles
Important Notes About Last Seen
It's important to understand that: 1. The $last_seen
property is only updated when a profile property is set or updated, not when a user performs an event
2. If you use the $ignore_time
parameter set to true
(typically for server-side updates), Mixpanel will skip updating the $last_seen
property3. This property is different from tracking when a user last performed an action in your productDefault Properties
Using JQL for Advanced Queries
For more advanced queries, you can use JQL to access the last_seen
attribute: LBKSfunction main() { return People() .map(function(user) { return { distinct_id: user.distinct_id, last_seen: new Date(user.last_seen) }; }); }LBKS
User Object SpecificationIf you need to track when users last performed specific actions (rather than when their profile was updated), you should track those events separately and create custom reports based on those events.
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kapa.ai how can I get the content piece with highest number of churns?
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I can help you identify the content piece with the highest number of churns in Mixpanel. This analysis will help you understand which content might be contributing to user drop-off.
Analyzing Content-Related Churn in Mixpanel
To identify the content piece with the highest number of churns, you'll need to use cohort analysis and breakdown features in Mixpanel: 1. Define your churn cohort: First, create a cohort of users who have churned based on your definition of churn. As mentioned in the Ultimate guide to cohort analysis, you can define actions (or lack of actions) that are most likely to lead to churn.2. Analyze content engagement before churn: - Go to Insights report - Select your content view/engagement event - Filter for users who are in your "churned" cohort - Break down by your content identifier property (content ID, title, etc.) - Sort by count (highest to lowest)This will show you which content pieces were most frequently engaged with by users who eventually churned.
Using Flows to Identify Problematic Content
You can also use the Flows report to see if specific content leads to drop-offs: 1. Start with your content view/engagement event 2. Look at the subsequent paths users take 3. Identify content pieces that have high drop-off rates (users don't continue to other actions) 4. Use the Top Paths view to condense this information into the most common problematic paths
Leveraging Mixpanel's Debugging Features
For a more detailed analysis, you can use Mixpanel's debugging features as described in their debugging blog post: 1. Build a funnel of your basic user flow 2. Look for significant drops 3. Break down by content properties 4. Identify which content pieces correlate with the highest drop-offsBy combining these approaches, you'll be able to identify which specific content pieces are associated with the highest number of churns, allowing you to investigate and improve those content items to reduce overall churn.Would you like more specific guidance on setting up any of these analyses in Mixpanel?Ultimate guide to cohort analysis: How to reduce churn and strengthen your product retention
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kapa.ai In the Users tab there is a column named 'Updated At'. What is that?
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The "Updated at" column in the Users tab refers to the $last_seen
user profile property in Mixpanel. This property shows the last timestamp when a user profile was updated, not when the user last performed an event in your product.According to the documentation: > User Profiles are mutable, which means new ones can be added and existing ones can be updated or deleted. Mixpanel automatically maintains an "Updated at" ($last_seen
) property, which contains the last timestamp that a user profile was updated. "Updated at" does not change if the user does a new event; it only changes when the profile is updated.User Profiles FAQIt's important to note that this timestamp is only updated when a profile property is set or updated. The "Updated at" property will not change in the following cases:
- When a user performs a new event
- For profile updates made via the UI
- If the $ignore_time
parameter is set to true
in your API callsDefault PropertiesIf you're looking to track when users last performed actions in your product (rather than when their profile was updated), you should track those events separately and create custom reports based on those events.
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