Do loyalty programs really enhance behavioral loyalty? An empirical analysis accounting for self-selecting members
Introduction
The effect of loyalty programs on loyalty is a topic of debate. Most loyalty programs do not turn all disloyal customers into loyals or make customers exclusively loyal. This does not mean that a loyalty program cannot be a useful tool. As expressed by Koslowsky (1999): “While none of these programs result in a perfect world, each can generate that little extra that can provide the retail marketer with potential tactical weapons”. A supermarket manager describes the added value of its loyalty program as follows: “You don't have 100% of a share of a customer's wallet. Customers shop about five times a month. Maybe you'll get three of those trips and the competition gets two. The loyalty program eliminates at least one shopping trip you weren't getting and creates an additional shopping trip to your store” (Cioletti, 2001). Hence, it is important to correctly quantify that ‘little extra’ that a loyalty program can offer to a retailer.
Recently, many retail companies have introduced loyalty programs to enhance customer loyalty (Kumar & Reinartz, 2005). Loyalty programs are currently available in many industries, such as supermarkets, gasoline stations, and clothing stores (Leenheer and Bijmolt, 2003, Lewis, 1997). Loyalty programs provide members with benefits such as discounts and saving rewards, which make these programs popular among consumers (Liebermann, 1999). In the United States, almost 80% of all households have at least one supermarket loyalty card, and in Canada this is even 90% (ACNielsen, Consumer Insight, 2002).
Extant empirical research provides mixed evidence of loyalty program effectiveness. Some studies found positive effects of retail loyalty programs on purchase behavior (Bell and Lal, 2003, Lewis, 2004, Taylor and Neslin, 2005), whereas others provide evidence of loyalty programs that do not generate any effects (Mägi, 2003, DeWulf et al., 2001, Sharp and Sharp, 1997). This ambiguity may relate at least partly to the fact that methodological limitations hinder proper assessment of loyalty programs effects. A potential problem is that customers who are already loyal may have a higher likelihood to enroll into the program, leading to an overestimation of the loyalty program effect. In other words, expenditure differences between members and non-members (Van Heerde & Bijmolt, 2005) may be partly driven by self-selection of the most loyal customers into the loyalty program. To illustrate our point, we show in Table 1 descriptive statistics for our empirical study on grocery loyalty programs. There are substantial differences in share-of-wallet (SOW) between members and non-members: the average share-of-wallet of members is 36%, which is 29 percentage points higher than the average share-of wallet of non-members (7%). The central question of this study is to what extent this gap is due to self-selection and to what extent loyalty programs really enhance behavioral loyalty. Existing research has ignored this self-selection or endogeneity problem, as argued by Bolton, Lemon, and Verhoef (2004). They propose that a thorough solution for this problem is needed before any conclusion can be made on loyalty program effectiveness.
This paper aims to measure the impact of loyalty programs on customer loyalty while controlling for endogeneity due to self-selecting members by using a model with instrumental variables. We apply our model to data from a representative Dutch sample of 1909 households who report their loyalty program memberships for all seven loyalty programs in Dutch grocery retailing as well as their expenditures at each of the 20 major supermarket chains. The wide and empirical scope of the study allows us to conclude that loyalty programs really enhance behavioral loyalty, albeit seven times less than what we would conclude if we did not control for self-selecting members. This paper also aims to deepen the substantive knowledge about what determines the effectiveness of loyalty programs, as called for by Jain and Singh (2002). Though experimental research indicates that the effectiveness of loyalty programs depends on the program's design (Kivetz and Simonson, 2002a, Roehm et al., 2002, Van Osselaer et al., 2003, Yi and Jeon, 2003), there is no evidence from empirical field data to date. In this paper we study two loyalty program design elements: the discount percentage and the percentage of a household's expenditures that is redeemed as a saving program reward. Our findings suggest that these design elements do affect the decision to enroll in a program, but they do not impact the effectiveness of loyalty programs once consumers are enrolled.
The remainder of the paper is structured as follows. Section 2 develops a conceptual framework on the relation between loyalty programs and purchase behavior. Section 3 discusses the data of our empirical study, and Section 4 describes the model. A presentation of the results follows, and we conclude with a discussion.
Section snippets
Customer loyalty
The marketing literature provides a wide range of loyalty measures (Odin, Odin, & Valette-Florence, 2001), and their usefulness depends on the specific market and study objective. The main distinction in loyalty measures is between attitudinal loyalty and behavioral loyalty (Dick & Basu, 1994). Since we are interested in the effects of loyalty programs on actual purchase behavior, our key dependent variable captures behavioral loyalty. In grocery retailing, purchase behavior is characterized by
Data description
To assess the effects of loyalty programs on behavioral loyalty, we conduct an empirical study of the Dutch supermarket industry. This industry is an interesting market for a study of loyalty programs, because consumers make transactions in supermarkets frequently, and can easily visit several supermarkets within a relative short time-interval. We have panel data on purchase behavior of 1909 Dutch households in supermarkets during 2 years. The panel members provide purchase information by
Model
A model for share-of-wallet yields specific challenges. To be logically consistent, the model must produce estimates between 0 and 1 (range constraint), and the sum of estimates over all stores must equal 1 (sum constraint) (Hanssens, Parsons, & Schultz 2001, p.121). Attraction models meet these constraints, and have been widely used for modeling market shares (Leeflang, Wittink, Wedel, & Naert, 2000, p.171). An attraction model can also be applied to household-level shares-of-wallet: the basic
Results
As a first step, we estimate the choice model over all observations, and obtain the inverse Mill's ratio λis needed in the succeeding steps. The complete model reveals that none of the moderating effects between household characteristics and store variables is significant. Therefore we continue with a choice model without these moderators. This model is significant (p < .01) with LL = − 7285.0 and pseudo-R2 = .248. Since the store choice equation is merely included to obtain unbiased estimates for the
Discussion
We studied the effects of seven loyalty programs on share-of-wallet using market-wide panel data on supermarket purchases. Our study is the first to account for the endogenous nature of loyalty program membership by specifying a model for the loyalty program decision and using instrumental variables such as the attitude towards loyalty programs in general. We find a significant positive yet small effect (4.1 percentage points) of loyalty program membership on share-of-wallet. This effect is
Limitations and further research
We undertook a market-wide study of all loyalty programs in the Dutch supermarket industry and found overall positive effects of programs on share-of-wallet. Given that the relationship proneness and product category involvement of consumers is low in this industry, we could expect these effects to be even larger in other industries, such as clothing retailing (DeWulf et al., 2001). Furthermore, in the empirical application several competitors use loyalty programs, and households hold several
Acknowledgements
The paper is part of the first author's dissertation. A major part of the research has been conducted at Tilburg University and the Vrije Universiteit Amsterdam. The authors thank GfK Panel Services for providing the data. They also thank Els Gijsbrechts, Marnik Dekimpe, and Richard Paap for their useful comments on a previous version.
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