Predict Customer Churn with StatIQ

Hi ​@EdenHaha ,
As fat as I know—StatIQ doesn’t currently support classification models with a predict function the way PredictIQ does. Churn prediction typically needs logistic regression or a decision-tree classifier.

As a workaround, one option could be:
    •    Convert the churn outcome into a binary variable (e.g., 1 = churned, 0 = retained).
    •    Run a linear regression anyway. While not technically ideal for binary outcomes, it can give directional insights—especially if you’re just trying to flag high-risk segments.
    •    Then, set a threshold (like 0.5 or based on percentiles) to categorize predicted values as churn/no churn.

It’s not perfect, but it might get you part of the way there if you’re just trying to prioritize outreach.

If your team uses SPSS or R outside Qualtrics, you could also export the data and run a proper logistic model externally.

Hope it helps.
-- Rochak

Hi ​@rochak_khandelwal and ​@EdenHaha - Stats iQ does offer logistic regression using a binary variable as the dependent variable. You don’t need to use a linear regression for a binary classification.  Please feel free to reach out to me if you would like to see an example.  I’ll DM you separately. 

​@carolsuehaney : Thanks for the update!