Request to Save Conversion Rate Chart Without Funnel Display

Ali A. · 2025-07-28T10:33:32.401Z

Please provide capability to save the chart as it is. Most of the time I only want to look at conversion rates along the total number of users. But when you save it like this, it shows the Funnel chart in the display

Request to Save Conversion Rate Chart Without Funnel Display | Mixpanel Community

5 comments

· Sorted by Oldest

Gabi M.
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I think setting the report as "metric" at top right helps with this You see the conversion rate and the number of users that converted
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Ali A.
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Nope it doesnt serve the purpose. Lets say I have 10 variation for an a/b test and looking at a funnel graph which is broken down on 'variation' its good to see , how many users each variation got and then how many converted along the conversion rate. A table view works just perfectly fine but we can't save it like that in a board
Gabi M.
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I see, many conversions like that are easier to see in a table view ✅ Out of curiosity, how do you approach analysing more than 2 variants for an A/B test? Experiments in Mixpanel allow for only 2 variants, so I guess it has to be calculated off-platform? This is something I'm in the middle of solving, so I appreciate if you could share you approach!
Ali A.
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Hi Gabi, I haven't used mixpanel experiments enough, However what we do is we send events whenever someone becomes part of an experiment and then we have a property of 'variant' in that event. You can simply put up a funnel chart and then break it down on 'variant' property. This would give you results of all the variants and how they performend. Can you share what tools are you using for running A/B Test, or its that you applied it through backend in code?
Gabi M.
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We do it through backend, and Mixpanel records events for each A/B test with variant as a property (I then make user cohorts based on it) The challenge is seeing if the difference between variants is statistically significant, which is why I use Mixpanel Experiment feature, that calculates the significance However, (as far as I know) it allows for only 2 variants, which means we have to find a way to analyse a test with involves 3 variants Especially because the more variants there is, the more comparisons we have to make (eg. A vs B, A vs C, B vs C) increasing the chance for type 1 error, so there needs to be a correction involved If you know a way to analysing it, I'm all ears!

Gabi M.
·
·
I think setting the report as "metric" at top right helps with this You see the conversion rate and the number of users that converted
Loading attachments
Ali A.
·
·
Nope it doesnt serve the purpose. Lets say I have 10 variation for an a/b test and looking at a funnel graph which is broken down on 'variation' its good to see , how many users each variation got and then how many converted along the conversion rate. A table view works just perfectly fine but we can't save it like that in a board
Gabi M.
·
·
I see, many conversions like that are easier to see in a table view ✅ Out of curiosity, how do you approach analysing more than 2 variants for an A/B test? Experiments in Mixpanel allow for only 2 variants, so I guess it has to be calculated off-platform? This is something I'm in the middle of solving, so I appreciate if you could share you approach!
Ali A.
·
·
Hi Gabi, I haven't used mixpanel experiments enough, However what we do is we send events whenever someone becomes part of an experiment and then we have a property of 'variant' in that event. You can simply put up a funnel chart and then break it down on 'variant' property. This would give you results of all the variants and how they performend. Can you share what tools are you using for running A/B Test, or its that you applied it through backend in code?
Gabi M.
·
·
We do it through backend, and Mixpanel records events for each A/B test with variant as a property (I then make user cohorts based on it) The challenge is seeing if the difference between variants is statistically significant, which is why I use Mixpanel Experiment feature, that calculates the significance However, (as far as I know) it allows for only 2 variants, which means we have to find a way to analyse a test with involves 3 variants Especially because the more variants there is, the more comparisons we have to make (eg. A vs B, A vs C, B vs C) increasing the chance for type 1 error, so there needs to be a correction involved If you know a way to analysing it, I'm all ears!