Conversion Analysis allows you to define customer stage conversion events that you’d like to track and analyze behaviors of your customers who have converted versus those who didn't convert. By understanding the behaviors and product usage patterns of both the converted and non-converted customers, you are armed with the knowledge and insights to craft the best action plan to improve the processes and bring your target customers to a successful conversion.
For example, you can define a trial conversion event and compare activity and feature usage of both converted and non-converted accounts across their own individual trial period. This analysis offers useful insights on how these two sets of accounts used the product differently and how that trended over the course of the trial period. You can then identify the key features and the best time to engage with your current trial accounts to help them reach faster time-to-value with your product, leading to a higher chance of converting them to paid users.
Create a Conversion Chart
To create a chart for Conversion Analysis, you need to define a time frame for your conversion events, specify what state change indicates a successful conversion, or non-conversion and then select the type of analysis you’d like to perform for your conversion events.
Please note that a conversion event is defined based on the “Stage” history of your accounts, you’ll need to either provide Natero with “Stage” history of your accounts via the Account API or update it via the “Account Settings” page in order for us to successfully capture any conversion event you define.
1. Configure Time
Time window for conversion events
- Select a time frame during which conversion events occurred.
For example, if you’d like to analyze conversion events that happened in the last year, you can specify the time frame to start from January of last year and end at December of last year.
Days prior to conversion events
- Specify the number of days leading to each conversion event over which you'd like to analyze data.
For example, if you'd like to analyze feature usage of past converted and non-converted trial accounts over their trial period and your trial plan is 30 days, you would enter “30” days in this case.
Or if you'd like to compare activities for accounts that moved from “Onboarding” to “First Renewal” versus those that are still in “Onboarding”, and you are particularly interested in knowing how the activity of the first set of accounts looked 7 days prior to their stage change date compared to those who haven't changed. You would enter “7” days in this case.
2. Select Analysis Type
Select the type of analysis you’d like to perform for your conversion events:
Shows the activity summary of the converted and non-converted accounts including
- Tickets Open: Average number of tickets created per account, over the days prior to the conversion.
- Daily Logins: Average number of logins per account per day, over the days prior to the conversion.
- Daily Active Users: Average number of active users per account per day, over the days prior to the conversion.
- Daily Sessions: Average number of sessions per account per day, over the days prior to the conversion.
- Average Daily Session Time: Average of average daily session time per account per day, over the days prior to the conversion.
Shows the average usage count per account per day for all the features by both the converted and non-converted accounts.
Shows the average usage time per account per day for all the modules by both the converted and non-converted accounts.
Select how you'd like to sort the results.
- Alphabetical: Sort the results by Activity, Feature or Module name from A to Z.
- Percent Difference* - Module: Sort the results by Module name from A to Z. And then within each module, sort the results by percent difference between the two compared values, from the biggest to the smallest.
- Percent Difference - Overall: Sort the results by percent difference between the two compared values, from the biggest to the smallest.
*Percent difference is calculated as the difference in both values over the bigger value of the two.
3. Specify Conversion Criteria
A conversion event needs to be mapped to a change in account stages. In other words, Natero will identify a conversion event by looking at the stage change date where the pre and post state(s) is defined.
Select the initial stage for your conversion event. For example, if you'd like to analyze for trial conversion, your initial state would be “Trial”.
Check the state(s) that follows a successful conversion. For example, if a successfully converted account is identified as changing stage from “Freemium” to “Onboarding”, you would select “Onboarding” as the conversion state. Depending on how you define customer lifecycle stages, if your accounts can be in various stages after converting from “Freemium”, you might want to select all of them, e.g. an account can convert from “Freemium” stage to either “High-Touch Onboarding” or “Low-touch Onboarding”.
Check the state(s) that follows a non-conversion event. For example, if a non-converting account is identified as changing stage from “Freemium” to “Closed”, you would specify "Closed" as the non-conversion state.