Predict Customer Behavior and Engage High Potential Customers

Many organizations have figured out how to use data to better serve their customers. They’ve used data to optimally stock grocery aisles, price hotel rooms, select the right colors for their catalog sweaters or study regional buying patterns. What many organizations haven’t gotten a handle on is customer loyalty and engaging high potential customers.

Customer loyalty is a term that gets tossed about quite a bit, but what does it really mean to a company’s bottom line? In his book, The Ultimate Question, Frederick Reicheld of Bain & Co. says every 5% increase in retention equals a 25% to 100% increase in profitability. What many organizations fail to understand is that to increase retention levels of the customers that matter most, they must shift from a product focus to a customer focus.

Focusing on product profitability is still necessary. It’s important to understand what products earn the most and how to maximize that knowledge. Consider the example of a beverage that costs more per ounce when purchased in a larger size. It takes advantage of consumers’ tendency to assume the bigger the box the better the unit price – and it works, or organizations wouldn’t do it. It is, however, a product-centric way of looking at increasing profit because it doesn’t factor in what the customer feels like when they realize their trust has been violated.

When an organization is customer focused the question changes. It’s not so much “How can I get the most profit out of this product?” It’s “What percent of my best customers buy my product every week and what can we do to maintain and even grow that number?” And, “How can I assure that my products are delivering value to the customers that matter most?”

Take the example of a retailer that struggled to understand why it was losing market share. The company had a tremendous tradition of strong, data-driven operational procedures. What it seemed to lack was customer loyalty. It realized it had plenty of data on their customers, but it just wasn’t using the information to segment its customers and their marketing messages. By leveraging customer data to target messages more effectively, the company significantly improved customer loyalty, which translated to a 20% increase in profitability.

Trying for a more interactive approach to retention – whether it involves text messages or efforts to bring customers to a Web site – can also pay dividends. Consumers, as the Association of National Advertisers has pointed out, want to be spoken with and not spoken to. It’s not enough to send a “Your subscription is about to expire” letter; rather, publishers should want to engage the subscriber throughout the subscription period.

An international publisher was losing 50% of its customers after the first renewal. The publisher switched to a more proactive retention campaign that opened up a dialog with subscribers from their first issue onward. As readers responded to different messages, the company gained insight that helped it tailor messages further. Within a few months, the retention rate improved by 10%.

Market segmentation is critical, but to really bring in a high number of potential customers, marketers need to get the offer to the person just in time. It needs to feel less like a “pitch” and more like the organization understands the customers’ desires.

A terrific example of this is a casino that tried to understand what created loyal customers. By building predictive models, management determined that a customer’s experience within the first hour of setting foot in the casino determined how long they were likely to stay, how profitable their visit would be, and whether they were likely to come back. So they began to monitor the first hour experience of high-value customers and, when appropriate, started offering incentives.

For example, if a high-value customer came into the casino and began to experience a string of bad luck, a casino employee would immediately engage the customer and offer a special treat such as free tickets to a show. This sent the message to high-value customers that the casino values their relationship and is willing to invest to assure that they have a positive visit. The company is now the most profitable in the industry.

Real-time behavior-triggers can dramatically increase marketing effectiveness. It’s conservatively estimated to be 20 to 30 times more effective than traditional direct-marketing. Responding to aberrant changes in customer behavior not only achieves a higher response rate, but it also increases customer affinity because the offer is more relevant.

Consider the example of a telecommunications company that began real-time analysis of data to make offers to clients calling in with service requests or changes. As soon as the person called in, the decisioning engine was answering key questions about the client ranging from the likelihood that they will cancel to whether they are a credit risk. The engine then provided the customer service rep with an offer (if appropriate) and other guidance to assure the best outcome for the customer and the company. The new approach created a 40% conversion rate on offers, with an additional 20% of customers willing to consider the offer.

For marketers to succeed they need to know their customer. And to do that in 2009 they need to use predictive analytics, provide offers in real time and use more interactive forms of marketing.

Jeff Gilleland is the global customer intelligence strategist at SAS. Karen Heath is a managing practice principal in HP’s BI Solutions group.