- You have the Architect or Admin permissions
With great power, comes great responsibility - so this document aims to empower you with the right tools to play around with this user role.
Objective: If you encounter feedback from Sales where there are certain scores that don't make sense - either the lead is not a good fit but scored as qualified or the lead is a good fit but showing up as unqualified - the best thing to do first is to check out if there are any overrides implemented in your model that are forcing certain leads to go into a specific segment.
There are of course many other ways to do this (example: configuring the trees, etc) but below is a typical first step to understand any false positives/false negatives.
- Access the Data Studio through the Customer Fit Model (App > Predictions > Go to Data Studio).
- Check out the Overrides tab and review where the "problematic" lead could fall under.
- Create a computation with that override definition by going on Customer Profile > Computations > New Computation. Ensure that you select "Customer Available (the computation will be visible in Customer Fit Insights)" tag. Click on Deploy and go back to the overview page of your model to reload your dataset with the aggregation. Wait for the processing to be completed.
- Once completed, go back to the Data Studio tab and check out the Insights for that particular computation. Here, you want to see what proportion of leads contribute to conversions. If lift is > 0.5 (best to be above 1) and with a significant number of leads/conversions, it means that the override is "performing". If not, iterate on the override until you find a better lift.
- Once you find a better override definition, recreate the override in the Overrides tab.
- Validate the performance of this update in the Validation tab. The benchmark is to get 20-30% of population to 60-80% of conversions as well as a linear conversion rate across each segment.