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Predictive analytics can help underwrite these quantities by predicting the chances of illness, default, bankruptcy, etc. Predictive analytics can streamline the process of customer acquisition by predicting the future risk behavior of a customer using application level data. Predictive analytics in the form of credit scores have reduced the ...
Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing , site selection , and customer relationship management .
Customer attrition, also known as customer churn, customer turnover, or customer defection, is the loss of clients or customers.. Companies often use customer attrition analysis and customer attrition rates as one of their key business metrics (along with cash flow, EBITDA, etc.) because the cost of retaining an existing customer is far less than the cost of acquiring a new one. [1]
Retention cost, the amount of money a company has to spend in a given period to retain an existing customer. Retention costs include customer support, billing, promotional incentives, etc. Period, the unit of time into which a customer relationship is divided for analysis. A year is the most commonly used period.
Uplift modelling uses a randomised scientific control not only to measure the effectiveness of an action but also to build a predictive model that predicts the incremental response to the action. The response could be a binary variable (for example, a website visit) [1] or a continuous variable (for example, customer revenue). [2]
The overall scope of the CLM implementation process encompasses all domains or departments of an organization, which generally brings all sources of static and dynamic data, marketing processes, and value-added services to a unified decision supporting platform through iterative phases of customer acquisition, retention, cross-and upselling ...