Experience Is the Best Teacher

Most people will agree with the adage experience is the best teacher. Although I tend to agree, I also keep in mind one of my favorite Will Rogers' quotes: "The trouble with using experience as your guide is that sometimes the final exam comes first, then the lesson." In business, have you ever experienced the final exam and then the lesson? In other words, did your customer defect (the ultimate final-exam failure) without you seeing it coming or without you having determined why (the lesson learned too late)? It's not supposed to happen that way: Satisfied customers are supposed to be loyal and profitable. In fact, you invested in an operational CRM system to automate and manage the transactions with your customers during marketing, sales, and services processes. In addition, you capture historical information and receive reports based on predefined questions. Your CRM system was supposed to help you walk in step with your customers' desires, building customer loyalty and profitability along the way. Well, along the way customer loyalty shifted to customer royalty. Yes, the customer really is king. And if you relied on simple reporting of historical data, you missed the opportunity to predict your royal customers' behavior. What if you had a special pencil that could predict the answers to the final exam before you viewed the questions? Do you think your odds of passing the exam would improve? What if your CRM system created customer intelligence that allowed you to predict which customers were likely to defect, giving you the opportunity to persuade them to stay? Do you think your odds of reducing customer churn would improve? Do I need to remind you what reducing customer churn would do to your bottom line? Analytical CRM is that special pencil and is a source of tremendous power. Analytical CRM provides usable customer intelligence from the data collected by your operational CRM system. You can use analytical CRM to:

Segment your customers for more profitable, targeted cross- and upsell opportunities.

Assess and predict the current and potential profitability of your customers.

Determine each customer's affinity to a channel, message, product, or service, and then provide personalization. Predict the probability that a specific customer will churn. A key to analytic CRM is the ability to provide predictive analysis. Predictive analysis is what makes your special analytical CRM pencil so powerful. Reporting and online analytical processing (OLAP) slice and dice data and provide ways to search for relationships between customers, products, or time. However, with OLAP you must know what you are looking for and supply the questions to the answers you are seeking. In other words, you are using experience as your guide. This is not stated to discount experience. If given a choice, most of us would rather make business decisions based on experience as opposed to a shot in the dark. But how do you leverage experience when the final exam comes first? How can you position your company to be forward looking, to be proactive rather than reactive? Predictive analysis through data mining is different from reporting or OLAP. Data mining is a process that provides statistical analyses that can identify trends and patterns in vast amounts of data. Data mining is forward looking and may very well provide the answers to questions you wouldn't think to ask. With data mining, you can predict a customer's future behavior. This is important in predicting customers' probability to churn and determining the underlying reasons for their loyalty. Perhaps I can paraphrase Will Rogers: The trouble with using reports as your guide is that sometimes the customer churns, and then the revenue and profits decrease. To provide leadership and achieve a competitive advantage around customer intelligence, your CRM solution must be forward thinking and include predictive analytic capabilities. About the Author Alan See serves as an adjunct faculty member for the University of Phoenix's College of Business and Management and is a member of SAS's Alliance Development Division. Contact him at Alan.See@sas.com.