Analyzing Trial User Conversion Rates with Mixpanel

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Yes, you can definitely analyze this scenario using Mixpanel. Here's how you can approach this using Mixpanel's cohort analysis and funnel features: 1. Create a cohort: First, create a cohort of users who started their trial 30 days ago. You can do this using the Cohort Builder in Mixpanel. Set the criteria as "Users who did 'trial_started' exactly 30 days ago".2. Create a funnel: Next, create a funnel with two steps: - Step 1: "trial_started" - Step 2: "upgraded_paid" Set the conversion window to 30 days to match your trial period. You can adjust this in the Conversion Criteria settings.3. Apply the cohort filter: In your funnel analysis, apply the cohort you created as a filter. This ensures you're only looking at users who started their trial 30 days ago.4. Break down by price point: Assuming you have a property that captures the price point for each user (let's call it "subscription_price"), you can use this as a breakdown in your funnel analysis. This will show you conversion rates for each price point.5. Compare cohorts: To analyze different cohorts over time, you can create multiple cohorts (e.g., "Trial started 30 days ago", "Trial started 60 days ago", etc.) and compare them in the same funnel analysis. Mixpanel allows you to compare cohorts in your analysis.This approach allows you to: - Ensure you're only analyzing users who have had the full 30-day trial period - Compare conversion rates for different price points - Track how conversion rates change over time for different cohortsFor a more detailed walkthrough of cohort analysis in Mixpanel, you might find the Lifecycle Cohort Analysis Template helpful.Remember, Mixpanel computes cohorts dynamically at query time, so your analysis will always reflect the most up-to-date data How Cohorts are Computed.By using this method, you can effectively analyze your trial-to-paid conversion rates for different price points and cohorts, helping you determine the optimal pricing strategy for your subscription.

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I understand the challenge you're facing. Since the subscription_price is only available in the upgraded_paid event, we need to adjust our approach. Mixpanel offers a feature called Borrowed Properties that can help us solve this issue. Here's an alternative approach: 1. Use Borrowed Properties: Mixpanel's Borrowed Properties feature allows you to "borrow" a property from one event and use it in the analysis of another event. In this case, we can borrow the subscription_price from the upgraded_paid event and apply it to the trial_started event. As described in the Borrowed Properties blog post, "Borrowed Properties unlocks more analysis with the data you already have, without any lift from your engineering team."2. Set up the Borrowed Property: In the Mixpanel UI, you can set up the borrowed property. The trial_started event will "borrow" the subscription_price property from the upgraded_paid event.3. Create a funnel: Create a funnel with two steps: - Step 1: "trial_started" - Step 2: "upgraded_paid" Set the conversion window to 30 days to match your trial period.4. Apply cohort filter: Create and apply a cohort filter for users who started their trial 30 days ago, as suggested in the previous answer.5. Break down by borrowed property: Now, you can break down the funnel by the borrowed subscription_price property. This will show you the conversion rates for different price points, even though the property is only set in the second event.6. Compare cohorts: You can still create multiple cohorts for different time periods and compare them in your analysis.This approach allows you to analyze the impact of different price points on conversion rates, even when the price is only set at the time of upgrade. The Borrowed Properties feature essentially backfills the subscription_price to the trial_started event, allowing for more comprehensive analysis.Remember, as mentioned in the Mixpanel documentation, "Borrowed Properties aren't a shortcut for implementations (you should still create thoughtful tracking plans). They are meant to open up a new world of analysis by merging data that was previously difficult or impossible to plan ahead of time for your engineers."By using this method, you should be able to effectively analyze your trial-to-paid conversion rates for different price points and cohorts, helping you determine the optimal pricing strategy for your subscription.

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Given the 30-day trial period in your use case, the borrowed properties feature unfortunately doesn't provide a direct solution due to its 7-day lookback limitation. You'll need to consider one of these alternative approaches to accurately analyze your trial-to-paid conversions by price point.

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Yes, there is another way to achieve what you initially wanted without adding new properties or events. We can use Mixpanel's Insights report with some specific configurations to analyze your trial-to-paid conversions by price point. Here's how you can do it: 1. Use Insights report: Start by creating a new Insights report in Mixpanel.2. Set up the main metric: Set your main metric to count the "upgraded_paid" event. This will show you how many users are converting to paid subscriptions.3. Filter for trial period: Add a filter to only include "upgraded_paid" events that occurred between 29 and 30 days after the "trial_started" event. This ensures you're only looking at conversions that happened at the end of the 30-day trial period. You can set this up using the "time between events" filter in Mixpanel, as described in the Mixpanel documentation on advanced filtering.4. Break down by subscription price: Use the breakdown feature to segment your results by the "subscription_price" property of the "upgraded_paid" event. This will show you the conversion numbers for each price point.5. Normalize by trial starts: To get accurate conversion rates, you'll want to normalize your data by the number of trial starts. You can do this by adding a second metric to your Insights report that counts the "trial_started" event, filtered to only include events that occurred 30 days before the date range of your analysis.6. Use the compare to feature: Utilize Mixpanel's "compare to" feature to analyze different cohorts over time. You can compare the current period to previous periods to see how conversion rates for different price points change over time.This approach allows you to: - Analyze only users who have completed the full 30-day trial period - See conversion rates for different price points - Compare conversion rates over time without needing to create additional events or propertiesRemember, as mentioned in the Mixpanel blog on revenue analytics, "Mixpanel has made it easy to dig into product data by automatically calculating key product metrics." By leveraging these built-in capabilities, you can get the insights you need without additional implementation work.This method should provide you with the analysis you're looking for, showing how different price points affect conversion rates at the end of your 30-day trial period, all using the existing events and properties in your Mixpanel setup.

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Certainly! I apologize for not being clear enough in my previous explanation. Let me elaborate on the filtering part, specifically the third point about filtering for the trial period.Mixpanel offers a feature called "Time Between Events" which allows you to filter events based on their temporal relationship to other events. This is exactly what we need for your use case. Here's a more detailed explanation of how to set up this filter: 1. In your Insights report, click on the "Filter" button.2. In the filter menu, select "Time Between Events" (you might need to scroll down or search for it).3. Now, you'll set up the filter like this: - First event: "trial_started" - Second event: "upgraded_paid" - Time between: "is between 29 and 30 days"This filter essentially tells Mixpanel to only include "upgraded_paid" events that occurred between 29 and 30 days after the "trial_started" event for the same user.The reason we use 29 to 30 days instead of exactly 30 days is to account for any small variations in timing that might occur due to factors like time zones or slight delays in event tracking.You can find more details about this feature in the Mixpanel documentation on advanced filtering. The documentation states: "You can filter your events based on the time between two events. This is useful for understanding user behavior over time."By applying this filter, you ensure that you're only analyzing users who converted at the end of their trial period, which is crucial for your analysis of how different price points affect conversion rates at the end of the 30-day trial.This filtering method allows you to focus on the specific user behavior you're interested in (end-of-trial conversions) without needing to create any new events or properties in your Mixpanel setup.

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