로열티 프로그램에 있어서 소비자의 포인트 적립 노력수준이 소진 행동에 미치는 영향 (The Effects of Point Accumulation Effort Level on Redemption Behavior in Loyalty Program)

서지정보

· 발행기관 : 한국마케팅학회
· 수록지 정보 : 마케팅연구 / 27권 / 1호 / 85 ~ 106페이지
· 저자명 : 김지윤, 이장혁, 김상용, 이방형

초록

기존의 로열티 프로그램의 소진행동에 관한 실증 연구들은 주로 쿠폰 사용률(Smith and Sparks 2009; Reibstein and Traver 1982)에만 초점을 맞추었고, 실제 소비자들의 포인트 소진행동에 대한 연구들은 매우 미흡한 상황 (Taylor and Neslin 2005; Liu 2009)이다. 이러한 한계점에 대해서 Benavent et al. (2000)은 대부분 로열티 프로그램 연구는 실험이나 설문조사를 통해 실제 소비자 행동이 아닌 가입 의향과 같은 행동의도 변수들 측정에만 그치고 있어서, 실제로 소비자들이 어떻게 행동을 했는지에 대한 데이터 분석을 통한 행동연구의 필요성을 주장하였다.
본 연구는 로열티 프로그램 가입자들의 거래 행동 데이터를 이용하여, 소비자의 실제 행동을 분석한 최초의 연구라는 점에서 그 의의가 있다고 볼 수 있다. 특히 기존에 연구된 노력수준을 구매빈도로만 국한하여 본 것이 아닌 좀 더 실질적이고 구체적인 적립방법 측면에서의 노력수준을 알아보았으며, 소비자들의 포인트 적립과 소진하는 날짜를 계산하여 속도개념을 도입하였다는데 그 의의가 크다고 볼 수 있다.
로그 선형 회귀분석 결과 소비자의 노력과 보상물에 대한 할인의 정도가 노력과 보상물 간에 다르게 영향을 미치게 되어, 오히려 노력을 더 들일수록 소진속도를 늦추어 천천히 포인트를 소진하게 됨을 검증하였고, 평균 소진 금액은 더욱 커짐을 확인할 수 있었다. 또한, 본 연구는 데이터가 특정 지역에 몰려있는 현상으로 인한 문제점을 보완하기 위해 국소가중회귀분석(Locally Weighted Regression)(Cleveland 1979)을 도입하여 가설의 방향성은 유지되면서도 적합도를 향상 시키는 등 방법론적으로도 의미 있는 분석방법을 제시하였다.
한편 마케팅 실무자에게 다음과 같은 시사점을 제공할 수 있다. 로열티 프로그램 설계에 있어서 소비자들이 어떻게 포인트를 적립하는지가 소비자의 포인트 사용 행동에 영향을 미칠 수 있음을 알아본 연구로, 향후 로열티 프로그램 설계 시 실무자들이 어떻게 효율적으로 프로그램을 디자인할 지에 대한 방향성을 제시한 연구라고 할 수 있다.

영어초록

This paper investigates the effects of customer‘s effort level on reward redemption behavior such as redemption speed and average redemption unit size. Our research extends the understanding of loyalty program where the majority of previous research focuses on coupon redemption rates(Smith and Sparks 2009; Reibstein and Traver 1982)and findings on point redemption behavior are quite limited (Talor and Neslin 2005;Liu 2009)to research methodology applied for loyalty program. Benavent et al.(2000)note that most of the research on loyalty program tends not to use actual customer data but focuses on customer intention to join the program measured by the survey or experimental design. Therefore, they insist that empirical data analysis is necessary for researchers to address the issue on customer's actual redemption behavior based on transaction data.
Liu(2007) notes that Loyalty programs provide some value to consumers in two stages. The first stage is points accumulation, wherein the points have no tangible value until they redeemed. However, recent studies prove that they have important psychological meaning to consumers (Hsee et al. 2003; Van Osselaer, Alba, and Manchanda 2004). This transaction between customers and the firm gives a psychological benefit to the customers by providing a transaction utility of a purchase (Thaler 1985) which leads to the increase of the overall value perception with the firm. The second stage is points redemption wherein consumers get both psychological and economic value from a loyalty program. This free reward means a positive reinforcement to the consumers which leads to a continued transaction with that firm (Sheth and Parvatiyar 1995). For this reason, it is very important to investigate the relationship between these two stages and how the behavior of first stage will affect that of the next stage.
This Loyalty programs are often regarded value-sharing instruments and can enhance consumers’ perceptions of what a firm must provide (Bolton, Kannan, and Bramlett 2000; Yi and Jeon 2003). The value enhancement function is of importance because the ability to provide superior value is essential to customer relationship start and retention(Sirdeshmukh, Singh, and Sabol 2002; Woodruff 1997). Indeed, strengthened value perception is considered a necessary condition for a firm to achieve a successive loyalty program(O’Brien and Jones 1995).
By using transaction data from a multi-brand loyalty program, we address a question on whether the way to accrue points of loyalty program may affect the behavior of redeeming these points. We profoundly investigate the actual membership's redemption behavior by measuring the point accrual effort level and point redemption behavior in suggesting a value proposition to maximize customers' value during the point accumulation and redemption stage.
Accordingly, we propose the two following hypotheses.
Temporal discounting refers to the decrease in the subjective value of an outcome due to delay. Soman (1998) shows that when the mixed outcome is in the distant future, it appears to be more attractive than when the same outcome is immediate, suggesting different discounting rates for effort and money. Thus, the degree of discounting would be the highest for the effort, and lower for the reward in temporal proximity. If a person exerts much effort toward a point accumulation, these mixed outcomes that have both gain and loss components (effort and reward) will moderate temporal discounting and it will delay the redemption of his cumulated points. Therefore, the first hypothesis is that the more consumers exert effort to cumulate reward points, the slower they redeem points.
Kahneman and Tversky (1979, p.286) recognize that "there are situations in which gains and losses are coded relative to an expectation or aspiration level that differs from the status quo". According to Kivetz(2003), effort requirements raise reward expectations that make a shift in the reference from the neutral status quo. This reference point is moved to the right side which makes consumers expect more than the status quo even though the same level of effort is exerted. This would make a consumer spend a larger amount of redemption point than the usual. Therefore, we propose the following hypothesis that the more consumers exert an effort to cumulate reward points, the larger the amount to they spend to redeem.
We measure the effort level by the proportion of points cumulated by using a coupon and the redemption speed by using the FIFO (First In First Out) method(Odgen and Odgen 2005) which is commonly used in the stock management and accounting techniques. It means that what comes in first is handled first and what comes in next waits until the first is finished. This way we measure the difference between the date of accrual and the date of redemption. We also operationalize effort level with the proportion of points cumulated by using a coupon cumulation.
Log Linear regression analysis confirms our hypothesis with empirical data that tests whether the level of effort increases the degree of discounting with accrued reward points in terms of point redemption speed. The result is that the more consumers exert effort to cumulate reward points, the larger they redeem. Moreover, methodologically we first introduce a Locally Weighted Regression Analysis to increase the robustness of fitting of our model in the research. It is used for the fitting of nonparametric models wherein the data points are gathered in some areas. Because our data points gathered near zero, it is appropriate to use this method to fit our model to solve the data problem. Moreover, we improve our model fit by maintaining the result of direction of the hypothesis.
This research is the first one to analyze each membership's real redemption behavior in detail by using loyalty member's transaction data. More importantly, previous research on effort level is mainly measured by the number of purchase a customer has made(Kivetz and Simonson 2002). But, we use other realistic method to measure the effort level by using how to accumulate points. In addition, we calculate each customer's redemption speed by using the FIFO method.
Our findings recommend the company running its loyalty program to develop marketing activities to make its customers cumulate reward points easily. And it also suggests that loyalty program operators would consider the fact that the way of point accrual affects its point redemption behavior.
It is worthwhile to test how the speed of point redemption and average redemption unit size affect customer loyalty in future research. In addition, it is also interesting to examine the customer's other redemption behavior such that the characteristic of redemption outlet(hedonic or utilitarian outlet) would be affected by the effort level.

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