The Business Analytics Knowledge Exchange will publish a series of articles on high-performance analytics – the enabler to getting faster, better answers – and how it applies to various industries. These use-case scenarios address various ways to take advantage of “big data” and identify examples of the business value high-performance analytics provide for virtually every organization.
To begin, consider the banking and financial management sector. Here is an excerpt from a recently released white paper on the topic, focusing on customer relationship dynamic pricing.
Many banks today are hoping to grow consumer and small business revenues through cross-sell and up-sell techniques that increase the number of products per customer and also create “sticky” relationships that reduce attrition. The challenge in selling additional products to each customer is there may be no way to modify the price of new products under consideration based on the current value of the relationship and how this could change with the addition of other new products. With high-performance analytics, the bank representative could assess the customer’s current use of existing bank products and services along with associated profitability and combine that information with in-house propensity, credit scores and external data (such as outstanding loans and other financial relationships) to gain a view of the customer’s potential lifetime value. The overall value to the bank through the addition of high-performance analytics is that every customer interaction can be based on optimizing the price of new products for each customer in a way that increases retention, grows revenue and improves the bank’s profits while providing the optimal customer experience for each individual consumer or business client.
Follow this series for more industry examples.