Profitable Customers Are Your Business' Best Friends

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If I asked you to name your best friends, you likely could answer me in seconds. But if I asked you to identify your business' best customers, how quickly could you answer? What is the basis for your response?


If yours is like most companies, you would not have a definitive answer. And like most people, you would admit that you should know who your best, most profitable customers are because they are the lifeblood of your business.


Over a lifetime, loyal customers purchase more, cost less to sell to and, studies show, will refer five other people to your company. What's more, keeping current customers costs five to seven times less than finding new ones. Clearly, ensuring their satisfaction is vital to long-term business survival and profitability.


So how do you keep customers loyal? It's easy, right? Give them what they want. But how do you find out what they want? Today, vast amounts of data are available about your customers. Do you use the data from purchases and transactions, Web activity, call center and service activities, marketing campaigns and third-party sources? You can combine transaction data with third-party data and add survey data to the mix. Together, this information provides a complete profile of your customers and leads you to a deeper understanding of them.


In order to truly understand customers, you have to mine the data you have accumulated. Data mining enables you to uncover their unique characteristics and behaviors so you can take actions to better serve them. Understanding what customers do and how they act helps you develop loyalty, retention and awards programs -- up-sell and cross-sell programs -- and targeted marketing programs. But where should you begin? The first step is identifying your best customers.


It is easy to say that the best customers are those who are most profitable. But what makes a profitable customer? Is it simply someone who spends a certain amount of money? Maybe it is someone who always buys new products as soon as they are released. Or perhaps it is someone who purchases with regular frequency. Data mining will help you sort out who is most profitable to your organization and which factors are most important in determining profitability over a projected customer lifetime.


Begin the data mining process with lifetime value modeling, a powerful data mining method that identifies ideal customers, or those with the greatest long-term profit potential. Various software packages are available to help you do this. In lifetime value modeling, you classify customers by how recently and how often they have used services or purchased products and by how much they have spent. Lifetime value modeling goes beyond the RFM of customers to identify the unique demographic or behavioral characteristics that drive profitability. The method forecasts how long you can expect someone to be a customer and predicts lifetime value to the organization based on past behaviors. Armed with this information about individual customers, you can allocate resources more appropriately.


This brings us to step two of the data mining process: propensity modeling. While lifetime value modeling provides a picture of who is likely to be a good customer over time, propensity modeling predicts how people are likely to behave in specific situations. Propensity modeling explores a specific question, such as "Who is likely to respond to this offer?" or "Who is likely to buy this product?" By measuring profiles of your best customers -- developed in lifetime value modeling -- against a propensity model, you can improve response rates to marketing and sales programs.


Equipped with these two methods, lifetime value modeling and propensity modeling, you can assign predictive values or scores for lifetime value and an individual's likelihood to do any number of specific things. Employing both methods will provide the most complete picture of your customer base and will enable you to make the most informed decisions about how to keep the most profitable customers. Additionally, the reduction in costs and higher response rates resulting from more targeted programs can add up to an increased return on investment.


Using these methods requires a few important things. Data is a prerequisite. For the most part, you can use data already available in the organization. As the process develops, it is important to collect data that meet your specific data mining goals. Secondly, you need a data mining tool that offers predictive modeling techniques, such as decision trees, clustering and neural networks. Finally, the results of data mining are useful only when they are applied to specific business issues. To do this, you will need a process for integrating results with specific programs. It is useful to have a person or people to serve as a bridge between the analysts creating the models and the people who understand the related business issues. Someone who understands the technology and is connected with the business applications of the data mining can do this function in house. Many times, this is handled as a consultancy function and outsourced.


Where do you go from here? Exactly where customers want you to be. You now have the power to develop in-depth customer profiles and predict customer behavior in a way that can affect your relationships with customers in day-to-day interactions. You can even put models to work to predict customer behavior in real time.


With this scoring system in place, when a valued customer dials up your company, a service representative will immediately look at their scores on the computer screen and give specific treatment to customers based on their preferences and long-term value to the organization. Perhaps the representative will make a special offer to an individual who has been profitable in the past. Maybe the representative will suggest new products that complement the customer's past purchases. The result: a happy, loyal customer who keeps coming back.


Remember that data mining is an ongoing process. As you refine your analytical models, the results will prove more and more valuable in helping you keep your customers and ensure their satisfaction. And just as you want to make the journey through life with your best friend, you'll want to make your business journey with your best customers.

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