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Hi, 

We are new to Gainsight and are implementing the Essentials Plus package.  We currently are deriving our churn prediction score through data stored in our data warehouse.  As we implement the Essentials plus package, should we be looking to add the raw data into the platform and allow the platform to use predictive analytics to derive the churn prediction, or should we add in our current churn prediction score that is being derived in the warehouse using ML?  What is the best practice?  Or is there a hybrid approach putting in the current prediction score?
Thanks in advance.

Hi @clairemillsap, hope you are well!

 

Came across this post and curious to know the approach you’ve taken here. I believe you can initially bring in the raw data into the platform and utilize the predictive analytics in Gainsight. If you already have a successful ML model for churn prediction in your data warehouse, you can then consider a hybrid approach:
1. Import your existing churn prediction scores into Gainsight.
2. Compare these scores with those generated by Gainsight's analytics over time.


This comparison should help identify the more effective churn prediction method for your needs. 

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