Loyalty programs have existed for decades, yet few have produced discernible impacts--and many have, instead, destroyed value for retailers. An analysis of more than 50 U.S. retailers over the past 10 years reveals that store sales growth for retailers with loyalty programs has averaged about 2.3 percent, while sales growth for retailers without loyalty programs has averaged 4.3 percent. Many loyalty programs fail to provide the desired sales or profit lift and cost retailers millions of dollars in annual spend.
A key contributor to program failure is retailers that provide unnecessary rewards at the point of purchase. Many create programs that encourage short-term customer behavior, and this focus on maximizing transactions leads retailers to blindly provide incentives to customers. These retailers are unable to capture the right customer information and are unable to build sustainable, profitable customer relationships.
Incentives that typically accompany loyalty programs aren't always required to produce desired behaviors (e.g., increasing customer share of wallet). What separates retailers that operate successful loyalty programs is the realization that a lion's share of the value lies in acting on the rich customer data collected to differentiate offers and rewards--not in the carrot-and-stick rewards system that supposedly drives loyalty. Savvy retailers effectively mine this data and develop deep customer insights. The result? Loyal customers and a profit-creating versus a profit-destroying loyalty program.
To develop rich customer insights and targeted information-based marketing programs, retailers do not necessarily need to develop a loyalty program that directly links purchases to a customer's loyalty card. Rather, they can leverage the data already resident in their transaction systems data warehouses. The key is to find a unique identifier in each transaction that can be linked to a specific customer. For example: Paying by credit card: Link transactions using the credit card number as a key to identify a customer.
Paying by check: Scan checks and link transactions using the customer's bank account number.
Paying with cash: If appropriate, ask customers for a telephone number at the point-of-sale and link transactions using this information.
By linking transactions to customers using these methods, retailers can develop a rich view of customer behaviors. It can be further enhanced by integrating demographic, attitudinal, and other types of data acquired through primary customer research or third-party marketing services companies. There are a few limitations to this approach, namely that customers will interact with sellers in different ways (e.g., channels, payment types), resulting in fragmented views of customers. But retailers can quickly and cost-effectively develop information-based marketing capabilities by following a seven-step approach:
1. Obtain a data set of sample transactions and link them to specific customers using the techniques described above.
2. Use statistical techniques to understand the drivers of customer behavior and value and develop a value-based segmentation.
3. Size and prioritize value-creation opportunities within the customer base.
4. Create predictive models for priority subsegments.
5. Develop and test information-based marketing pilot programs.
6. Refine models based on pilot results and develop information-based marketing program road maps.
7. Design and implement ongoing information-based marketing capabilities, including organization, process, and IT initiatives.
Information-based marketing is a high-value capability. Most important, it can yield huge dividends without giving away the store.
Michael Evans is a consultant, Jeffrey Schumacher is a partner, and Marc Singer is a director at McKinsey & Company's global marketing and sales practice.