Heavy Buyers Research Articles

The Effectiveness of Membership-Based Free Shipping: An Empirical Investigation of Consumers’ Purchase Behaviors and Revenue Contribution

Membership-based free shipping (MFS) has been increasingly adopted by online retailers. However, its effectiveness is understudied. This study leverages a consumer transaction data set provided by an online retailer and uses a stacked difference-in-differences approach to quantify the enrollment effect of MFS on consumers’ purchase behaviors and their net revenue contribution to the retailer. Interestingly, MFS enrollment does not lift average consumers’ spending at the beginning of the enrollment, as they break large orders into smaller ones. Retailers do not gain incremental net revenue due to the increased shipping costs during this period. However, the free shipping benefit may build a switching barrier that motivates consumers to purchase more often with larger order sizes over time. It eventually leads to increased spending and revenue contribution. MFS also increases members’ purchase variety and impulse purchases. In addition, the authors find that there is a greater increase in net revenue contribution after enrollment for light buyers, variety seekers, and those who are willing to pay shipping fees before enrollment. Surprisingly, MFS has a negative impact on the revenue contribution of heavy buyers, the conventional best-value consumers. Moreover, MFS can effectively strengthen consumer–retailer relationships by reducing customer churn.

Examining Pareto Law across department store shoppers

Department stores invest in loyalty strategies that largely focus on retaining current high value customers in response to increasing competition in retail shopping. In this study, we examine the contribution of the top 20% customers for transaction frequency and value (“heavy buyers”) to the total sales, and the consistency of this contribution across departments within a store. We also investigate the heavy buyer stability over time across 3 years, from over 550 million transactions from a department store chain in East Asia. The results show that the Pareto ratio of the top 20% spenders account for 71% of revenue (and 52% of the total transactions), and the top 20% transactors represent 58% of revenue (and 62% of total transactions), which may signal the role of such heavy buyers to overall stores sales. At each department level, the heavy buyers (by value) contribute from 65% to 86% of the department revenue. Despite this, the stability of the top 20% segment over time varies greatly by department from 11% to 74%. Finally, whether high value customers in one department store also translate across departments, depends mainly on the department size in terms of its shopper penetration. The research furthers our knowledge on Pareto Law, with important implications for customer retention strategies and loyalty programs especially for retailers.

Sustaining shopping momentum in retail malls using real-time messaging

Retail malls thrive not only on foot traffic they attract but also on buyers spending at multiple retailers in the mall. While the importance of shopping momentum, i.e., buyers continuing to shop, is known, few studies have examined how mobile promotions can incentivize buyers to sustain their shopping momentum in a mall. This study examines how a mall operator targets buyers in its loyalty program with a real-time message (RTM) to encourage them to sustain their shopping momentum and spend more at the next retailer. We use a quasi-experimental design and show that the RTM has a stronger effect on heavy than light buyers. Specifically, moderate and heavy buyers are more likely to respond favorably to RTMs by sustaining shopping momentum and increasing spending at the next retailer. In contrast, the RTM has no effect on shopping momentum of light buyers, and if they continue to shop, they lower their subsequent spending. The study has important implications for retailers using mobile applications to target buyers with relevant real-time promotions to achieve desired outcomes.

How Instagram usage time and spending on fashion products affects product attitude and purchase intention according to influencer type

This study examined the effect of Instagram usage time (short, long) and spending on fashion products (light, heavy) on product attitude and purchase intention of products promoted by an influencer. The moderating effect of influencer type (mega, macro, micro) was also investigated. A total of 515 males and females in their 20s participated in an online survey. Descriptive statistics were analyzed and exploratory factor analysis and two-way ANOVA were conducted. Research findings were as follows. First, the usage time, both short and long, had a positive effect on product attitude. Also, the interactive effects of usage time and influencer type on product attitude were found. Consumers with short Instagram usage time displayed the highest attitude toward products promoted by a macro-influencer whereas consumers with long Instagram usage time displayed the highest attitude toward products promoted by a micro-influencer. Second, usage time and influencer type did not show interactive effects on purchase intention. Third, both categoriacl variables of users’ spending on fashion products had a positive effect on product attitude. Fourth, the interaction effects of spending on fashion products and influencer types on purchase intention were found. The group of light buyers showed the highest purchase intention on products promoted by the macro-influencer while the group of heavy buyers showed the highest purchase intention of products promoted by the micro-influencer. Based on the results, implications were suggested.

Marketing’s 60/20 Pareto Law

We confirm our 2007 conclusions concerning the Pareto Law. Our conclusions are now supported by many other data sets, and independent analyses. It’s wrong to talk about an 80/20 law in marketing. A brand’s heaviest 20% of buyers generally contribute not much more than half of a brand’s sales, and these same buyers will contribute less in the following time period. Indeed, even for stable brands half of last year’s heavy buyers will then not even qualify to be in the top 20%, while the people who were light or non-brand buyers last year will contribute more to sales this year than they did last year. The exact sales contribution of the top 20% (a brand’s Pareto share metric) depends on the time period and some other technical decisions made by the person calculating the metric, and brand size and some category characteristics. But it’s reasonable to expect that almost half of your brand’s sales will always come from your very lightest 80% of buyers. It is also apparent that growth comes largely from these light, very light/non-brand buyers and so it would be foolhardy to ignore them.

The fallacy of the heavy buyer: Exploring purchasing frequencies of fresh fruit and vegetable categories

‘Avocado lover,’ ‘banana lover,’ or ‘berry lover’ – these words are starting to dominate the contemporary marketing campaigns for fresh fruit and vegetable categories. Such campaigns assume that there are sizable buyer segments who purchase a particular fresh category more frequently, who are contributing a larger portion of sales, and who will continue to do so into the future. Yet, an established body of empirical evidence from consumer packaged goods (CPG) categories suggests that these assumptions could be false. The current study empirically examines fresh category purchasing behavior (through a large Nielsen US panel data) by applying three known models: the Negative Binomial Distribution, the Pareto share, and the stability over time analysis (buyers and sales contribution). This study compares the results and finds that despite many differences between fresh and CPG categories, buyers' purchasing behavior follows the same established benchmarks patterns as those observed in CPG contexts. There are many more infrequent or light buyers than heavy ‘lovers’; the heavy buyers contribute roughly 60% of sales; they are purchasing less frequently, and contributing fewer sales as time goes by. These findings carry important implications for marketers, retailers, and farmers of fresh categories. Specifically, the results show which marketing campaigns (i.e., those highly targeted at ‘lovers’ or those with a mass marketing appeal) are better grounded in the empirical evidence about buyer behavior which has the highest probability of increasing consumption.

Are Heavy Pirates also Heavy Buyers?: A Case of the Video Game Industry in Japan

Abstract Purpose This study aims to examine how piracy via peer-to-peer (P2P) network affects sales of original version in the video game industry. Design/methodology/approach This study conducted an online questionnaire survey in 2009 with a focus on 9970 users of portable video game platforms, and collected information of how familiar respondents were with techniques for downloading pirated video games via P2P network and how this knowledge affected their purchase behavior of original video games. Findings First, 38% of the respondents know how to download pirated video games via P2P network. Younger male respondents with greater enthusiasm for video games are exposed to greater opportunities to learn to pirate. Second, different respondents employ different channels to learn about piracy. Third, 95% of the respondents who knew how to pirate did not download any pirated video game. Once involved in piracy, jobless respondents with less enthusiasm for video games who were informed about piracy by their friends tend to download pirated video games more intensively. Fourth, there is no significantly negative relationship between the number of pirated video games respondents downloaded and the number of original video games they purchased. Fifth, respondents who downloaded pirated video games also purchased original video games of which pirated version they have downloaded. Originality/value This study clarified that heavy pirates are also heavy buyers not only at the aggregate level, but also at the individual level, and interpreted the results from the viewpoint of peculiarities of video games as a cultural product, making piracy harmless to sales of original version.

Investigating the Natural Monopoly Effect in Brand Purchasing: Do Big Brands Really Appeal More to Lighter Category Buyers?

The Natural Monopoly [NM] effect is that big brands appeal to somewhat ‘lighter’ or less frequent buyers of the product category, whereas small brands appeal to heavier category buyers. The NM effect has an important managerial implication. It implies that for a brand to grow from small to big, it must heighten its appeal particularly to lighter buyers of the product category. NM is potentially informative as to customer base analysis, providing empirical norms for a brand’s light and heavy category buyers. Moreover, NM could help managers understand loyalty metrics, because it pertains to systematic variation in the category purchase rate, which is an input into common loyalty measures such as SCR (share of category requirements). However, little is known as to the extent to which NM occurs and the extent to which it covaries with variables such as brand size, price and type (store brand, manufacturer brand). This study examines the NM effect in packaged goods markets using data on 24 FMCG categories in Holland. The analysis compares observed category purchase rates among buyers of each brand with theoretical ‘norms’ derived from the well-known NBD-Dirichlet model. It also examines the simple correlation between brand size and category purchase rate as a direct test of the NM effect. Analysis confirms the NM effect is quite pervasive, being present in most categories. The average correlation between brand size (i.e., penetration) and category purchase frequency is -0.36. This figure shows that buyers of large brands do buy the category less often on average. Second, the analysis finds the NBD-Dirichlet model produces accurate predictions of the average rate at which buyers of each brand buy the product category. However, there is nearly twice as much variation in the category purchase rates than predicted by the NBD-Dirichlet. As well as finding that bigger brands tend to have lighter category buyers, the study also finds lower-priced brands and store brands appeal more to heavy category buyers. The study also explains how bigger brands manage to be bought more frequently by their buyers, whilst simultaneously appealing to lighter category buyers. The answer is they obtain a higher share of requirements among light, medium and heavy category buyers: particularly heavy buyers. These findings are useful general knowledge for brand marketers and retailers. The NM effect will be subject to further research to test the extent that it is an empirical generalization.

Can the negative binomial distribution predict industrial purchases?

Purpose This paper aims to extend the known boundary conditions of the negative binomial distribution (NBD) model, and to test the applicability of conditional trend analysis (CTA) – a key method to identify whether changes in overall sales are accounted for by previous non-buyers, light buyers or heavy buyers – in industrial purchasing situations. Design/methodology/approach The study tested the NBD model and CTA in an industrial marketing context using a 12-month data set of purchases from an Australian supplier of a range of industrial plastic resins. Findings The purchase data displayed a good NBD fit; the study therefore extends the known boundary conditions of the model. The application of CTA provided second-period purchasing frequency estimates showing no significant difference from actual data, indicating the applicability of this method to industrial purchasing. Research limitations/implications Data relate to just one supplier. Further research across several industries is required to confirm the generalizability and robustness of NBD and CTA to industrial markets. Practical implications Marketing decisions can be improved through appropriate analysis of customer purchasing data. However, without access to equivalent competitor data, industrial marketers are constrained in benchmarking the purchasing patterns of their own customers. The results indicate that use of the NBD model enables valid benchmarking for industrial products, while CTA would enable appropriate analysis of purchases by different classes of customer. Originality/value This paper extends the known boundary conditions of the NBD model and provides the first published results, indicating the appropriateness of CTA to predict purchasing frequencies of different industrial customer classes.

Understanding brand loyalty of the store brand’s customer base

Purpose The purpose of this paper is to attempt to understand the extent to which price consciousness and quality consciousness influence attitudinal loyalty to store brands (SBs) in different segments of consumers: heavy, medium and light buyers of SBs. SBs are currently consolidated among price-conscious consumers, but less established among the quality-conscious consumers. Design/methodology/approach After reviewing the literature and constructing a theoretical model, the authors performed a study on Spanish food products, a sector in which SBs have achieved a significant market share. They collected data through a personal survey and analyzed it using structural equations modeling, and they performed a multigroup analysis of heavy buyers, medium buyers and light buyers of SBs. Findings The results obtained alert retailers to the tremendous importance of price vs quality in the formation of SB value and loyalty to SBs among heavy buyers of these brands, show the balance between price and quality as components of SB value and generators of loyalty among medium buyers and recognize the need to strengthen the image of SB quality to reinforce SBs’ value and smart shopping associations to increase light buyers’ loyalty to SBs. Originality/value The study contributes new evidence and knowledge on SB loyalty among consumers who show different usage of these brands (heavy, medium and light buyers). It then assesses the short- and long-term value of each segment of customers for the retailer and recommends retail strategies adapted to each segment.

Who Are Store Brands Buyers? Demographic Profile of Store Brand Buyers in Bosnia and Herzegovina

Store brands, also known as private labels, own brands or retail brands, are experiencing a remarkable growth in various product categories and their acceptance by consumers seems to be unquestionable. The key drivers of the store brands’ success are the increased concentration in retailing, consumers’ much more positive attitudes towards the quality of store brands and critically, in the current economic downturn, their price, which is significantly lower than that of manufacturer brands. Sales of store brands in the Southeast European markets have not picked up yet, making these markets a compelling space to study, analyze and predict the future of store brand growth and success. Thus, this study focuses on consumer’s attitudes towards store brands in the Federation of Bosnia and Herzegovina – an emerging market, which is highly attractive for international retailers. The main objective of this study is to analyze and validate the profile of a consumer of store brands in the Federation of Bosnia and Herzegovina in the context of personal care products. For the purposes of this study, the mall-intercept survey was carried out at selected hypermarket locations. Based on the extent to which consumers perceive themselves to be consumers of store brands, three consumer segments have been identified: heavy buyers, sometimes buyers and seldom buyers. These segments were then described in terms of perceived quality and price of store brands as well as demographic characteristics of respondents. The findings allow drawing some useful reflection about who are the buyers of store brands in the Federation of Bosnia and Herzegovina and what drives their preferences towards store brands. Thus, this study provides valuable information for both retailers and manufacturers.

The stability and sales contribution of heavy‐buying households

AbstractCreating long‐term heavy buyers underpins many theories of consumer behaviour and marketing plans. This makes heavy‐buying households an attractive target for research and marketing activities. However, analysis across over 150 brands in 15 categories reveals that only around 50 per cent of the heavy‐buying households of a brand in 1 year to remain heavy brand buyers in the next year. This provides a benchmark for marketers implementing strategies to reduce leakage from heavy‐buyer segmentations. This result, however, casts doubt on the reliability of heavy buying as a household/buyer targeting characteristic and calls into question the idea that long‐term heavy brand buyers can be cultivated. There is evidence that category heavy buying is consistently more stable behaviour, averaging 67 per cent year‐on‐year buyer stability. Therefore, if heavy buying behaviour is a targeting characteristic, the results support the use of category buying, rather than brand buying weight. Copyright © 2014 John Wiley & Sons, Ltd.

Generalizations regarding the growth and decline of manufacturer and store brands

Stimulating growth or staving off decline in market share are core objectives for brand managers, including retailers who now offer store brands (SBs). This study identifies how changes in brand penetration and repeat-purchase loyalty accompany changes in brand share. We examine 1093 changes in brand share over 63 packaged goods categories in the UK from 2003 to 2007, covering both growth and decline. Two measures of repeat purchase loyalty are used—annual purchase frequency (PF) and share of category requirements (SCR). Our results show that brand share growth is accompanied by greater change in penetration than in loyalty, at a ratio of approximately 3:1. This finding generalizes across brand type, loyalty measure, retailer SB or manufacturer brand (MB), category purchase frequency, category type, and initial brand share. However, while brand share growth is accompanied by stronger changes in SCR than PF for MBs; the reverse is the case for SBs. For MB decline, both penetration and SCR change are significant correlates. However for SBs, the decline in brand share happens predominantly in loyalty—more strongly in SCR, followed by PF. Therefore, both brand types need to focus on building penetration to grow. While MBs also need to prevent light buyers from lapsing, SBs need to pay more attention to retaining heavy buyers to avoid repertoire demotion.

Value and store brand identification in food products

Purpose – Store brands have become consolidated in the food market and are currently considered real brands. The purpose of this paper is to determine the factors that contribute to consumers’ identification with store brands, as well as the possible effect of consumers’ identification with store brands on their loyalty to the retail establishment. Design/methodology/approach – The paper achieves its goal by reviewing the academic literature on the topic and proposing and validating a theoretical model for consumer-store brand identification. The theoretical model is validated through an empirical study of the Spanish market for food products using data gathered from individuals responsible for shopping for their homes who claim to have purchased store brand food products at least once. Structural equations modeling is then used to estimate and perform a multigroup analysis for heavy and light buyers of store brands. Findings – The results obtained reveal, first, that consumers’ store brand identification mediates the relationship between their value consciousness and their loyalty to the retail establishment that manages a broad, competitive portfolio of store brands. Second, the study demonstrates the effect of other variables, such as perceived risk associated with the purchase of store brands, their perceived value and consumer satisfaction. Finally, the results show important differences between heavy and light buyers of store brands. Research limitations/implications – The main limitations of this research derive from the factors conditioning the information. Store brand value was analyzed on an aggregate level, for the Spanish food products market. Future research should include other store brands (e.g. premium store brands), control for store brands with different labels and expand the area of application to new product categories and new countries. Practical implications – The results obtained have interesting implications for food retailers. These implications concern the management of value store brands in the product portfolio to achieve loyalty to the retail establishment among value-conscious consumers (who constitute the main target of value store brands). Originality/value – This paper analyzes consumer brand identification in an area that has not been studied to date: store brands. It contributes interesting and very useful findings for retailers who commercialize these brands in their establishments. The line of research on brand identification is quite new in academic research and has arisen due to the importance for companies of constructing close, lasting connections with the consumer.

Perceived value of retail service and loyalty to the commercial chain: the role of propensity to buy store brands

Previous studies in the area of marketing indicate that the service provided by retail firms affects the purchasing behaviour of their customers and thus the sales and profitability that these firms achieve. In this sector, we observe that store brands are closely linked to the service provided by these commercial labels and play a very significant role in the configuration of the distributors' assortment and price positioning. This paper first identifies the determining aspects of the functional value of service, measured formatively by components of quality of service, convenience of the assortment, and price level. Second, it proposes a theoretical model of the effect of the functional value of the retail service on customers' loyalty to the commercial chain and their evaluation of the relationship that they maintain with the distributor. Finally, it examines the moderating role of propensity to buy store brands. Our investigation shows the importance of the functional value of service to the dependent variables studied, which are relevant to entrepreneurial management. Further, we confirm that there are significant differences between heavy and light buyers of store brands. Specifically, as the propensity to buy store brands increases, the value of service is explained to a greater degree by perceived price level and to a lesser degree by perceived convenience of the assortment.

Predicting future purchases with the Poisson log-normal model

The negative binomial distribution (NBD) has been widely used in marketing for modeling purchase frequency counts, particularly in packaged goods contexts. A key managerially relevant use of this model is Conditional Trend Analysis (CTA)—a method of benchmarking future sales utilizing the NBD conditional expectation. CTA allows brand managers to identify whether the sales change in a second period is accounted for by previous non-, light, or heavy buyers of the brand. Although a useful tool, the conditional prediction of the NBD suffers from a bias: it under predicts what the period-one non-buyer class will do in period two and over predicts the sales contribution of existing buyers. In addition, the NBD's assumption of a gamma-distributed mean purchase rate lacks theoretical support—it is not possible to explain why a gamma distribution should hold. This paper therefore proposes an alternative model using a log-normal distribution in place of the gamma distribution, hence creating a Poisson log-normal (PLN) distribution. The PLN distribution has a stronger theoretical grounding than the NBD as it has a natural interpretation relying on the central limit theorem. Empirical analysis of brands in multiple categories shows that the PLN distribution gives better predictions than the NBD.

소비자의 포인트 적립 및 소진행동에 대한 재조명 : 사용수준(Usage Level)의 조절 효과를 중심으로

This study investigates customers' different behavior in accumulating and redeeming points and focuses on the moderating effect of usage level. We measure the hedonic accumulation and redemption ratio and usage level using loyalty program transaction data and link them to the survey data of loyalty and satisfaction. By doing so, we examine the effects of hedonic accumulation and redemption ratio on a consumer's loyalty intention and his or her satisfaction and the moderating effect of usage level. The result shows that there is a significant positive effect of hedonic accumulation and redemption ratio on customer loyalty and the mediating role of satisfaction on customer loyalty in both stages. And accumulation and redemption most importantly, we find an interaction effect of usage level on outlet type in point redemption stage while no effect in accumulation stage. That is if customers accumulate and redeem points at a hedonic outlets in both stages, it will give him a feeling of satisfaction and finally it will enhance the loyalty toward the focal loyalty program. And light buyers' loyalty increase more than those of heavy buyers when they redeem points in hedonic outlet. Our findings will help marketing managers of loyalty program to apply the effective segmentation strategy to the reward program which affects the customer's satisfaction and loyalty.

The Power of Before and After

<h3>ABSTRACT</h3> The Dirichlet is a well-established theoretical model that describes and predicts patterns of purchasing behavior in stationary markets. This paper uses data from a highly nonstationary market to demonstrate that the Dirichlet norms also provide a baseline to interpret change in purchasing behavior—in particular, change wrought by sustained promotional activity. The empirical analysis of industrial purchasing data describes how one supplier more than doubled its share of the market. This share increase was achieved by, first, securing a higher share of the category purchases made by heavy buyers (increasing purchase frequency) before adopting a more typical growth strategy of attracting more buyers (increasing penetration).

New Perspectives on Customer “Death” Using a Generalization of the Pareto/NBD Model

Several researchers have proposed models of buyer behavior in noncontractual settings that assume that customers are “alive” for some period of time and then become permanently inactive. The best-known such model is the Pareto/NBD, which assumes that customer attrition (dropout or “death”) can occur at any point in calendar time. A recent alternative model, the BG/NBD, assumes that customer attrition follows a Bernoulli “coin-flipping” process that occurs in “transaction time” (i.e., after every purchase occasion). Although the modification results in a model that is much easier to implement, it means that heavy buyers have more opportunities to “die.” In this paper, we develop a model with a discrete-time dropout process tied to calendar time. Specifically, we assume that every customer periodically “flips a coin” to determine whether she “drops out” or continues as a customer. For the component of purchasing while alive, we maintain the assumptions of the Pareto/NBD and BG/NBD models. This periodic death opportunity (PDO) model allows us to take a closer look at how assumptions about customer death influence model fit and various metrics typically used by managers to characterize a cohort of customers. When the time period after which each customer makes her dropout decision (which we call period length) is very small, we show analytically that the PDO model reduces to the Pareto/NBD. When the period length is longer than the calibration period, the dropout process is “shut off,” and the PDO model collapses to the negative binomial distribution (NBD) model. By systematically varying the period length between these limits, we can explore the full spectrum of models between the “continuous-time-death” Pareto/NBD and the naïve “no-death” NBD. In covering this spectrum, the PDO model performs at least as well as either of these models; our empirical analysis demonstrates the superior performance of the PDO model on two data sets. We also show that the different models provide significantly different estimates of both purchasing-related and death-related metrics for both data sets, and these differences can be quite dramatic for the death-related metrics. As more researchers and managers make managerial judgments that directly relate to the death process, we assert that the model employed to generate these metrics should be chosen carefully.

패션 명품의 추구혜택과 온라인 구매위험지각에 따른 쇼핑채널 선택

This study investigates the factors influencing consumer`s channel selection for luxury fashion items, specifically the effect of (i) perceived luxury benefits, (ii) perceived online shopping risks, (iii) demographics, and (iv) purchasing behavior. A survey questionnaire was developed and implemented to measure the perceived luxury benefits, perceived online shopping risks, purchasing behaviors, and consumer demographics. A total of 396 responses were analyzed by one-way ANOVA, cross-tab, and multinomial logit analysis with SPSS18.0. The results are as follows. First, those who shop in offline shopping channels tend to be heavy buyers that look for product quality and conspicuousness. They perceive low risks from online shopping and purchase few bag items offline. Second, those who shop online tend to be men and perceive the high benefits of economic value. Third, those who shop in multi channels tend to be men, search for information via the Internet, and purchase few accessory items. Implications for multichannel strategies are suggested.