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Customer relationship analysis (CRA), sometimes termed customer relationship analytics, is the processing of data about customers and their relationship with the enterprise in order to improve the enterprise's future sales and service and lower cost. This term is generally a synonym for CRM analytics.
Customer relationship analysis can be considered a form of online analytical processing (OLAP) and may employ data mining. As Web sites have added a new and often faster way to interact with customers, the opportunity and the need to turn data collected about customers into useful information has become generally apparent. As a result, a number of software companies have developed products that do customer data analysis.
According to an article in InfoWorld, customer relationship analysis can provide customer segmentation groupings (for example, at its simplest, dividing customers into those most and least likely to repurchase a product); profitability analysis (which customers lead to the most profit over time); personalization (the ability to market to individual customers based on the data collected about them); event monitoring (for example, when a customer reaches a certain dollar volume of purchases); what-if scenarios (how likely is a customer or customer category that bought one product to buy a similar one); and predictive modeling (for example, comparing various product development plans in terms of likely future success given the customer knowledge base). Data collection and analysis are viewed as a continuing and iterative process and ideally over time business decisions are refined based on feedback from earlier analysis and consequent decisions.
Benefits of customer relationship analysis are said to lead not only to better and more productive customer relations in terms of sales and service but also to improvement in supply chain management (lower inventory and speedier delivery) and thus lower costs and more competitive pricing.
One of the major challenges implicit in customer relationship analysis is how to integrate the analytical software with existing legacy systems as well as with other new systems.
A new area of application and data collection has to do with Web site customer usage.
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