A WNS DecisionPoint™ survey of over 1,500 retail shoppers identified six shopper archetypes, each having different expectations from their loyalty rewards programs
Driven by customer expectations of rewards that go beyond the basic and transactional, retailers are looking at innovative alliances to offer experience-based and personalized redemption options
Existing customer data can offer rich insights into lifestyle, behavior and communication preferences that can guide retailers in redesigning their loyalty programs
Just ahead of the 2016 holiday season, prominent U.S. department store chain Sears announced an unlikely partnership with ride sharing company Uber, taking the entire industry by surprise. The alliance was formed in an attempt to revive the struggling retailer’s loyalty program, ‘Shop Your Way’. Under the new program, Sears’ customers using Uber, as well as drivers and riders with Uber accounts linked to ‘Shop Your Way’, could get more reward points and gain access to benefits such as holiday price guarantees. A couple of months later, Sears announced a similar partnership with Activehours, a mobile payroll app provider.
As more such stories of retailers modernizing their loyalty programs hit the press, one can safely assume that traditional loyalty programs are perhaps not enough. The monetary rewards usually associated with the latter are now viewed as mere table stakes. Customers today demand highly personalized services and a wide range of accrual and redemption options in exchange for their loyalty, as seen in a recent WNS DecisionPointTM survey.
Whether it is intense personalization of rewards, faster point accruals or redemption through alliance programs as in the case of Sears, loyalty programs need to undergo a radical change if retailers want to boost customer engagement.
Fortunately, retailers with a long-standing loyalty program already have a treasure trove of customer data, right from basic profiles to detailed transaction histories. This data can be used to segment customers into multiple categories to create personalized rewards and redemptions. The data can also be used to gain a deeper understanding of customer needs and preferences to personalize their experience with the brand.
For instance, in the WNS DecisionPoint™ survey of over 1,500 retail shoppers, six different archetypes of customers were identified based on their demographics, personal characteristics and behavioral traits. These six personalities — In-store Point Miners, Redemption-centric Card Members, Experience Seekers, Channel-agnostic Point-seekers, Consummate Demanders and Casual Subscribers— were found to have varying expectations of loyalty rewards and personalization. Respondents also assigned varying degrees of importance to monetary and non-monetary rewards and redemptions.
This difference in preferences makes it clear that a loyalty program that treats these six unique customer types as one will never make a comeback. This also makes a strong case for retailers with far larger customer bases to stop investing in a one-size-fits-all loyalty programs. So, how should retailers go about re-designing their loyalty programs to be more relevant? How can they revitalize them beyond their transactional nature to deliver experiential value?
The answer lies in using data analytics to achieve a 360-degree approach towards building higher customer engagement and satisfaction. By analyzing the data, unique insights into every customer’s behavior, lifestyle and preferences can be obtained to identify non-monetary drivers of satisfaction. These insights can then be used to re-define loyalty programs and offer exactly what each customer wants, ensuring loyalty programs deliver what they were originally intended for – to foster a sustainable customer relationship.
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