We then aimed to boil these parameters into a single score to determine customer temperature and ranking the customers. Using the customer’s spend as the control, we tested to see which parameters were significant in a customer’s spend by first getting p-values via multiple linear regression. We’ve started generating insights cross correlating data on off-product events such as outages and support response times to determine if they affected a customer’s propensity to stay on the platform.