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Questions On Data Science
Length: 9 pages (2557 Words)
Answers to Questions
It is old marketing wisdom that it is better to retain an existing customer other than acquiring a new one. Companies, therefore, expend vast resources to handle instances where the customer may desert the firm either through setting up churn call centers and use of toolkits with specialized offers to the customers likely to desert. The act of a client leaving one firm and becoming a customer of another is referred to as customer churning. Late intervention employed by companies often enjoy 30 to 40 percent save rate of clients probable to churn. The interventions are taken towards reversing the decision of the customer to churn occur too late when the customer is already upset about the present value proposition offered by the company in question (Cios 37). The saves que model adopted by most companies is thus inadequate, especially in the present da where shoppers exchange information on how to maximize the potential benefits of a bluffed churn call while also collectively figuring out the reasons that would avoid long save conversations, thus getting out of the service. Further, companies possess declining ability to address churn. Companies are increasingly turning to the adoption of churn models aimed at identifying the root causes of customer churn, and addressing them before the company can lose substantive profitability owing to customer churn. Customer churn models rely on the available customer data held by the organization to help predict whether the customer is likely to churn shortly. Despite the increased efficiency achieved by modern statistical analysis, a churn statistical model lacks the capacity to inform the company on the root causes of customer churn.
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