Improve the efficiency and effectiveness in customer contacts
Another example of data mining is the application of decision rules in how to better approach customers.
A decision rule is a combination of customer attributes with a high chance of success to target a specific group of customers.
1. What is the profile of prospects who are more likely to become a customer?
2. Which customers are more likely to cross-sell or up-sell?
3. Which customers are more likely to churn (customer termination)?
By focusing on promising customer groups you can effectively target the customer base for acquisition, customer development and retention. If you know what characteristics typify promising customers, you can also make efficiency improvements by targeting less customers and get the same or even more results.