What does it take to build and sustain ‘true’ customer loyalty? The answer may seem straightforward given the fact that today customer loyalty is one of the key strategic initiatives of many retailers. However, surprisingly, a good majority of customer loyalty initiatives in existence today suffer from some shortcomings. For instance, customer loyalty is managed by most retailers at an aggregate customer level. That is, all customers are treated equal. Individual customer level differences (such as those based on psychographic, demographic, attitudinal, and behavioral) are ignored. Next, it has been empirically proven that there is generally a weak correlation between customer loyalty (as measured by most companies) and profitability. This is because, most loyalty programs in existence today reward behavioral loyalty (the more you spend (or use) the more rewards you get). Very few loyalty programs tend to focus on cultivating attitudinal loyalty, an important perquisite to ensure ‘true’ loyalty from the customer in the long run. Finally, most loyalty programs in existence today are linked to customer spend or frequency of usage and not customer profitability. This runs the risk of hurting the company’s bottom-line with the increase in membership base of the loyalty program, thus rendering the loyalty program counter-productive.

We explore issues like these and draw upon past research to emphasize the need to manage behavioral loyalty, attitudinal loyalty and profitability concurrently. Is it even possible to manage all these three simultaneously? We propose a two-tiered conceptual framework to achieve the same. According to this framework, customer loyalty may be managed at two levels. At the first level (Tier 1), all customers are treated equal and rewarded in proportion to their total spend. Hence, the primary objective of Tier 1 reward would be to encourage more spending or build behavioral loyalty. Next, the data collected for executing Tier 1 reward could be extensively mined to discern customer-level differences and determine whether a particular customer may qualify for a Tier 2 reward. Tier 2 reward (unlike Tier 1) could be administered at individual customer level and hence the objective fulfilled by Tier 2 reward would vary from customer to customer. Through careful and creative selection of the right Tier 2 reward for the right customer, companies may selectively build attitudinal loyalty or enhance behavioral loyalty for its most valuable customers. However, it has been empirically observed that customer loyalty need not translate into long term customer profitability. This is where we introduce the customer lifetime value metric. Customer lifetime value metric helps set a ceiling on the maximum dollar value that may be spent on rewarding a particular customer. By doing so, marketers can ensure that loyalty is not compromised for profitability. Also, by employing the customer lifetime value metric, companies can measure the expected future profitability of a customer and accordingly be proactive in rewarding the customer, thereby gaining a strategic edge over competition. By managing customer loyalty at both Tier 1 and Tier 2 in tandem, companies can build and sustain behavioral loyalty, attitudinal loyalty and profitability simultaneously.

The two-tiered framework poses several strategic implications for the retailing industry. For instance, it provides a mechanism through which companies can selectively and prudently manage their valuable marketing resources for each customer as opposed to indiscriminate deployment of resources across the overall customer base. This offers the flexibility to companies to vary their marketing budget from time to time as per the financial health of the company without risking any backlash from the customers. In addition, the two-tiered framework can be easily integrated with other marketing initiatives such as cross-sell, up-sell, and relationship management. Other implications (as described in the article) include protecting a company from cannibalizing its own business through excessive rewards based on pure customer spending or usage.

Finally, in this article, we position our proposed conceptual framework as a basis to understand the emerging dominant logic of twenty first century customer loyalty programs. Advances in IT, especially database management software has opened up a new era in loyalty marketing that is distinguished by sophisticated customer-level tracking and personalization. In such a scenario, this article identifies nine emerging trends in loyalty programs that seem to converge toward a discernible dominant logic. For instance, loyalty programs are moving away from rewarding customers based on usage or spend and instead focusing on customer profitability. Case in point is the airlines industry, where already some airlines have announced plans to realign their frequent flyer program to a mechanism where passengers paying the full fare for a ticket are rewarded more miles as compared to a passenger paying a discounted fare. Similarly, this article illustrates several real company examples to strengthen our conviction of the evolving dominant logic and the relevance of our proposed framework.