It's easy to see that the world is no longer black and white. However, why are businesses still treating customers that way? Businesses and their processes cannot be two-toned - especially when customers are involved.
Take churn for example. Businesses need to anticipate if and when a customer is going to close an account or cancel a subscription? It's not a deterministic yes or no question. It's only black and white after the effect. Before that, it's a probability. And it's a probability that can change at the drop of a hat. After every response, after a click, a dropped call, a dispute, the likelihood of churn may go up or down, and that's just the probability.
What a company needs to determine is how much this customer is worth to retain. Of course, you may have only a split second to decide all this. These are all questions best answered using predictive analytics. Why make assumptions when you have the data? You can't just go with the averages and hope for the best. Hope is not a strategy.
And it's not just retention either. You need to consider collections, sales, and underwriting. All of those processes depend heavily on customer behavior.
The effectiveness in determining the right cross-sell or up-sell offer as well as the customer experience and related satisfaction play a big role in this formula. A relatively small change in the retention rate has a huge impact on customer lifetime value. Later on, we'll consider the business contribution of predictive analytics and focus on improvements in customer insight related to the cases that drive the business
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