**Currently, this feature in closed beta, but available to try for all customers on MTU plan types. Please reach out to your Account Team or email us directly at email@example.com if you’d like to be included and we will gladly extend you early access to this feature in exchange for your feedback on how to improve it.
The most common question we find Funnels users asking after observing the conversion percentages from step to step: "Why did the users in my funnel convert or drop off?"
In order to find these answers, it is important to segment. Breaking down your funnel allows you to find how the conversion rates of different sub-groupings differ, discover how and with what audiences you are being successful, and formulate hypotheses and product strategies on how to spread that success as best as possible.
At a high level, segmenting is typically done in two ways: Demographic and Behavioral
- Demographic properties- such as City, Device, Referring Campaign, etc - tell you who your user is and how conversion rates differ for different attributes. These demographical insights can help you understand what target audience is successful and what customer base is underperforming. However, demographic properties are often harder to influence with product changes. They can tell you who is finding value in your product, but not necessarily what sorts of behaviors or habits are more likely to bring users towards converting.
- Behavioral segmentation allows you to understand what users did and slice and dice your data up by which paths and past behaviors lead to more conversions. This lets you spot particular sequences and actions that occur between funnel steps that promote conversion or places of friction that increase the likelihood of drop-off. Since you can more easily build product features that encourage or discourage particular user behaviors, much more so than change who they are in a demographical sense, these behavioral insights can typically be more actionable.
- For example, if you find that using multiple product features and touching more of the product's surface area increases a key conversion- this can influence strategy to improve onboarding to include more of the product. As these sorts of behavioral observations typically identify new potential habits that could be encouraged or changed, these insights regarding what users did are much more valuable to product teams.
Mixpanel already empowers segmenting with many types of demographic properties, but with Conversion and Drop-off Flows we take a large step forward in behavioral segmentation.
Mixpanel Funnels will now enable you to take a funnel and all of its criteria, view the user paths between each of the funnel steps as a sankey diagram, and segment that sankey by whether they converted or dropped off-- all in one single visualization.
By doing this, we will help you spot the critical actions that tip users toward conversion or drop-off. You can easily understand what users do after they drop-off.
Questions you can now answer
- What flows do users take between opening an app and making a purchase?
- Why did the successful users purchase?
- What flows do users take that don’t lead to a purchase?
- How do these two paths differ? What actions should I nudge towards or against?
- What did the users that dropped-off do instead?
Build product changes that encourage behaviors that cause conversion lift, and eliminate the friction that causes dropoff.
How to use Conversion and Drop-off Flows
First, go to the Mixpanel Funnels Report, and create any funnel you like by selecting 2 or more events steps.
Next, click on the conversion or drop-off population you wish to examine further and select View As Flow.
In this example, I want to see what events lead to better conversion or more drop-off between Step 1 Browse and Step 2 Add To Cart. This will send me to the Sankey visualization to see these event streams in a Flows report.
Up top, I can see that all of the Funnel's criteria is still maintained. In my example, I still am counting a Unique funnel, within 30 days, holding the Item Name property constant, and excluding users that Abandon Cart at any stage. I can also go back to the Funnel to change my criteria at any time.
The Sankey is automatically broken down by users that converted to Add to Cart or dropped off (whether that be by hitting an exclusion step, or failing to complete the funnel in the conversion window):
Hovering over any path I can see the size of the population and the percent converted to this action from the previous one.
In the example, I can see here that 10.6% converted immediately to Adding to their Cart.
I can also click any action to see the breakdown of how many users eventually converted or dropped off:
In this example, I can see that drop-off of users that Account Created after Browsing is 71.2%, which is higher than the 67.1% of the funnel. Is this a behavior to discourage browsing and Adding to Cart? Could it be time to develop a guest checkout experience to reduce this friction?
If you want to do an isolated analysis of conversions or drop-offs, I can apply a filter so that the report will include only conversions or only drop-offs. This is done by clicking on Filter in the query builder and selecting Conversion. Conversion = true will be conversions, Conversion = false will be drop-offs.
The rest of the controls are very consistent with what you can see in our Flows report. To learn more you can find a description of Flow's capabilities here.
We'd love any feedback or suggestions you have about additional ways we can help you learn from your conversions. To contact us, just email firstname.lastname@example.org – this goes to the entire R&D team that works on this product.
Thank you for participating in the Mixpanel Beta Program–we appreciate your time!
Product Manager, Mixpanel