How to Analyze New vs. Repeat Funding Users in a Cohort Since June Last Year

Khayalethu L. · 2026-03-25T10:05:29.874Z

I have created a cohort of users that viewed a certain page and went on to get funding since June last year - how do I figure out how many were new (funding count = 1) or repeat (funding count >1)? And of the new, how many went on to receive funding again (funding count >1 / or "is_readvance" = 1 for true)? I am afraid if I create a cohort with the condition, where funding count = 1, then I'll miss the initial new users who went on to receive funding again.

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kapa.ai
APP
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This is a great use case for Mixpanel's cohort and analysis features. Here's how you can approach it:
Breaking Down Your Existing Cohort
Since you already have a cohort of users who viewed the page and received funding since June last year, you don't need to redefine that cohort. Instead, you can use it as a filter and then break down the analysis further.
1. Segment by Funding Count (New vs. Repeat)
Rather than creating separate cohorts with funding count = 1 or funding count > 1 (which, as you correctly noted, would cause you to lose users who started as new and later became repeat), you should:
Use your existing cohort as a filter in an Insights or Funnels report.
Break down by funding count (or a derived property) to see the distribution.
In Mixpanel's Insights report, you can filter by your cohort and then use the breakdown feature to segment by a user property like funding count. This way, all users in the cohort are included, and you can see how many fall into each bucket. [Using Cohorts in Analysis]
2. Tracking New Users Who Later Received Funding Again
Your concern is valid — if you create a cohort with funding count = 1 as a static condition, it will only capture users whose current funding count is 1, missing those who started at 1 and later progressed. This is because:
"User profile properties only store the most recent value, cohorts involving user profile properties will use the current value for those properties (even if the value changed over time)." [Cohorts]
The recommended approach is to use a Funnel report instead of cohorts for this conversion question. Funnels are better suited for answering "how many users did X and then went on to do Y" because they respect the time ordering and conversion window. [Cohorts: How Computed]
For example:
Step 1: Received funding (where funding count = 1 or is_readvance = 0 at the time of the event)
Step 2: Received funding again (where is_readvance = 1)
This way, Mixpanel evaluates the event properties at the time the event occurred, not the current profile value.
3. Using Historical User Properties (if applicable)
If funding count is tracked as a historical user/group property (not just the latest value), Mixpanel does allow you to add time and measurement to cohort conditions to specify the time range over which to search for the property value. [Cohorts]
In summary:
Use your existing cohort as a filter, not a redefined cohort, to preserve all users.
Use Funnels to track the conversion from new (first funding) to repeat (subsequent funding), leveraging event-level properties like is_readvance at the time of the event.
Avoid relying on current user profile properties like funding count for historical segmentation, as they only reflect the most recent value.
ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.

kapa.ai
APP
·
·
This is a great use case for Mixpanel's cohort and analysis features. Here's how you can approach it:
Breaking Down Your Existing Cohort
Since you already have a cohort of users who viewed the page and received funding since June last year, you don't need to redefine that cohort. Instead, you can use it as a filter and then break down the analysis further.
1. Segment by Funding Count (New vs. Repeat)
Rather than creating separate cohorts with funding count = 1 or funding count > 1 (which, as you correctly noted, would cause you to lose users who started as new and later became repeat), you should:
Use your existing cohort as a filter in an Insights or Funnels report.
Break down by funding count (or a derived property) to see the distribution.
In Mixpanel's Insights report, you can filter by your cohort and then use the breakdown feature to segment by a user property like funding count. This way, all users in the cohort are included, and you can see how many fall into each bucket. [Using Cohorts in Analysis]
2. Tracking New Users Who Later Received Funding Again
Your concern is valid — if you create a cohort with funding count = 1 as a static condition, it will only capture users whose current funding count is 1, missing those who started at 1 and later progressed. This is because:
"User profile properties only store the most recent value, cohorts involving user profile properties will use the current value for those properties (even if the value changed over time)." [Cohorts]
The recommended approach is to use a Funnel report instead of cohorts for this conversion question. Funnels are better suited for answering "how many users did X and then went on to do Y" because they respect the time ordering and conversion window. [Cohorts: How Computed]
For example:
Step 1: Received funding (where funding count = 1 or is_readvance = 0 at the time of the event)
Step 2: Received funding again (where is_readvance = 1)
This way, Mixpanel evaluates the event properties at the time the event occurred, not the current profile value.
3. Using Historical User Properties (if applicable)
If funding count is tracked as a historical user/group property (not just the latest value), Mixpanel does allow you to add time and measurement to cohort conditions to specify the time range over which to search for the property value. [Cohorts]
In summary:
Use your existing cohort as a filter, not a redefined cohort, to preserve all users.
Use Funnels to track the conversion from new (first funding) to repeat (subsequent funding), leveraging event-level properties like is_readvance at the time of the event.
Avoid relying on current user profile properties like funding count for historical segmentation, as they only reflect the most recent value.
ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.

1 comment

Breaking Down Your Existing Cohort

1. Segment by Funding Count (New vs. Repeat)

2. Tracking New Users Who Later Received Funding Again

3. Using Historical User Properties (if applicable)

Breaking Down Your Existing Cohort

1. Segment by Funding Count (New vs. Repeat)

2. Tracking New Users Who Later Received Funding Again

3. Using Historical User Properties (if applicable)