Market segmentation: A comparison of benefits/attributes desired and brand preference

Benefits/attributes desired is commonly considered the most strategically meaningful market segmentation base. However, in practice, problems in product benefit/attribute specification and data collection are frequently observed. This research compares the performance of benefits/attributes desired and brand preference (a competing segmentation base that provides similar information but is more closely related to purchase behavior) on the criteria of segment identification, brand purchase, and responsiveness to marketing mix elements. Results suggest that brand preference segmentation produces more interpretable and managerially useful segmentation results than benefits/attributes desired. © 1995 John Wiley & Sons, Inc.     

Data accuracy's impact on segmentation performance: Benchmarking RFM analysis,logistic regression,and decision trees

Companies greatly benefit from knowing how problems with data quality influence the performance of segmentation techniques and which techniques are more robust to these problems than others. This study investigates the influence of problems with data accuracy – an important dimension of data quality – on three prominent segmentation techniques for direct marketing: RFM (recency, frequency, and monetary value) analysis, logistic regression, and decision trees. For two real-life direct marketing data sets analyzed, the results demonstrate that (1) under optimal data accuracy, decision trees are preferred over RFM analysis and logistic regression; (2) the introduction of data accuracy problems deteriorates the performance of all three segmentation techniques; and (3) as data becomes less accurate, decision trees retain superior to logistic regression and RFM analysis. Overall, this study recommends the use of decision trees in the context of customer segmentation for direct marketing, even under the suspicion of data accuracy problems.     

RFM-based repurchase behavior for customer classification and segmentation

Customer behavior modeling and classification are well-studied areas for applications in retail. Past studies implemented the purchase behavior modeling based on the physical behavior of a subject. In this research, we apply the recency, frequency, and monetary (RFM) model and data modeling techniques to detect behavior patterns for a customer. Each transaction attributed to a customer is part of one's behavior, and an instance of the feature vector, it is modeled on a set of transactions to constitute repurchase behavior. The proposed scheme is validated by simulating a publicly accessible real-world data set with a need-tailored multi-layer perceptron (MLP) and also support vector machine (SVM) and decision tree classification (DTC) methods. The experiments yield a high customer classification rate of more than 97% for the different numbers of the customers. Empirical analysis shows that eight transactions are sufficient to classify a customer with high accuracy.     

The Mediating Role of Customer Relationship on the Social Media Marketing and Purchase Intention Relationship with Special Reference to Luxury Fashion Brands

The reach of internet technology and social media has opened abundance of opportunities for marketers as well as for consumers across the globe. To anticipate future purchase behavior of consumers, marketers are not leaving any stone unturned. The main objective of this study is to investigate the direct and indirect impacts of social media marketing activities (entertainment, customization, interaction, word of mouth, and trend) on consumers' purchase intentions in luxury fashion brands. This study employed higher order Structural Equation Modeling to test the study model with (n = 243) sample data. We found positive significant impacts of social media marketing and customer relationships on consumers' purchase intentions. In addition, our study model confirmed full mediation of customer relationships in the relationship between social media marketing and consumers' purchase intentions. Based on our research findings, we strongly recommend that marketers of luxury fashion brands engage in social media marketing activities to provide value to customers.     

Reward redemption effects in a loyalty program when customers choose how much and when to redeem

The redemption of loyalty program (LP) rewards has an important impact on LP members' behavior, particularly on purchase behavior before and after redeeming a reward. However, little is known about the interplay between members' purchase and redemption behavior when members are not pressured with point expiration and they choose for themselves when and how much to redeem. In this context, the effects of redemption are not straightforward, as little additional effort is required from an LP member to obtain the reward. Analyzing the behavior of 3094 members in such an LP, we find that the mere decision to redeem a reward significantly enhances purchase behavior before and after the redemption event, even when members redeem just a fraction of their accumulated points. Conceptually, we refer to this enhancement as the redemption momentum, which is an alternative and novel explanation of the existence of pre-reward effects that do not depend on points-pressure. In addition to the overall impact of redemption on purchases, prior purchase behavior also enhances redemption decisions. Finally, we find a number of moderating effects on purchase and redemption behavior that derive from the length of LP membership, age, income and direct mailings. Our study's most important managerial implication is that firms should avoid imposing point expiry and/or binding thresholds in order to enhance members' purchase behavior.     

Generation Y vs. Baby Boomers: Shopping behavior,buyer involvement and implications for retailing

This paper presents some significant empirical findings about generational cohorts and their shopping behavior. Marketing has long relied on the use of market segmentation. While birth age has been a useful way to create groups, it describes segments but does not help to understand segment motivations. However, environmental events experienced during one's coming of age create values that remain relatively unchanged throughout one's life. Such values provide a common bond for those in that age group, or generational cohort. Segmenting by ‘coming of age’ age provides a richer segmentation approach than birth age. This study compares two significant cohorts: Baby Boomers and Generation Y, with respect to their shopping behavior and purchase involvement for food, clothing and automobiles. For the three types of products, Baby Boomers value the retail experience and in-store service higher than Generation Y. For Baby Boomers, the purchase process starts with a retailer the consumer trusts, who gives advice for choosing the right product, while for Generation Y, the purchase process starts with choosing a product. This study presents implications for retail strategies that have an appeal to different generational cohorts and considers how retailers should deal with building customer relationships.     

Book Review Index

The authors examine the impact on consumers' purchase likelihood after learning about online covert marketing practices. The findings suggest that while learning of online covert marketing practice lowers purchase likelihood, it is moderated by contextual factors including prior purchase experience, whether the company is well known or a start-up, and whether covert marketing involved information gathering or promotions. Consumer background variables were also found to moderate the negative impact on purchase likelihood resulting from consumers learning about online covert marketing activities. Conjoint scenarios were examined and a segmentation study was conducted based on a national survey of U.S. consumers. Implications for advertisers and regulatory action are discussed.     

Market segmentation

Market segmentation is a crucial marketing strategy. Its aim is to identify and delineate market segments or “sets of buyers” which would then become targets for the company's marketing plans. The advantage to marketing management is that this technique divides total demand into relatively homogeneous segments which are identified by some common characteristics. These characteristics are relevant in explaining and in predicting the response of consumers, in a given segment, to marketing stimuli.

The market can be subdivided by geographic, demographic, psychological, psycho‐graphic or behavioural variables. The advantages and disadvantages of each of these types of segmentation variables are discussed in detail in this paper. Kotier (1984) has identified four requirements that a marketer can use in evaluating the desirability of potential market segments, namely measureability, accessibility, substantiality and actionability. Once a segment has been identified which meets these requirements, it is possible to develop a product or service which meets the unfulfilled needs of this segment. A marketing mix can then be devised to reach the segment identified economically and efficiently. A strategy of market segmentation attempts to regain some of the benefits of the closer association with customers which was the strength of traditional business operations.     

Research on the influencing factors of consumers’ green purchase behavior in the post-pandemic era

The severe impact of the COVID-19 pandemic on the world has caused consumers to think about environmental issues. Although green products are very important to environmental sustainability, the factors that influence consumers' purchase behavior of green products is unclear. This study aims to explore the impact mechanism of social media marketing on consumers' green product purchase behavior in the post-pandemic era. Based on the theory of planned behavior (TPB), this study constructs an extended TPB model to understand the influencing factors of Chinese consumers' green product purchase behavior in the post-pandemic era. The empirical results of 489 questionnaires show that social media marketing, product knowledge and crisis awareness have a direct or indirect positive influence on purchase intentions. Perceived behavioral control and intentions have positive effects on behavior. The attribution of responsibility facilitates the relationship between intentions and behaviors. The results have important implications for enterprises’ sustainability strategies and provide a framework for investigating green buying behaviors in Chinese culture in the post-pandemic era.     

Exploring the effect of Starbucks' green marketing on consumers' purchase decisions from consumers’ perspective

This study contributes to current literature by constructing a model to evaluate how using green marketing to promote brand image affects consumers' purchase intentions. First, the decision-making trial and evaluation laboratory (DEMATEL) method was used to explore the mutual influence on evaluation indicators, and an influential network relation map (INRM) of indicators and sub-indicators was constructed based on the results. The DEMATEL method was then combined with the analytic network process to create a DANP method to calculate weights for each indicator and sub-indicator. A modified Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method was then employed to explore the comprehensive performance of each indicator and sub-indicator using empirical data. Finally, conclusions were summarised and suggestions were proposed. This study's findings can serve as a reference for firms seeking to improve the tangible effects of their green marketing strategies by stimulating consumers' purchase intentions.     

The effect of product touch information and sale proneness on consumers' responses to price discounts

Since price discounts are costly and can negatively affect consumers' perceptions of quality, it is crucial to identify the factors that make them effective in stimulating purchase behavior. Drawing on cue utilization theory, we examine price discount effectiveness in affecting consumers' reliance on the sale cue based on the provided product touch information as an intrinsic cue and individual consumer differences in sale proneness. Two experimental studies indicate that price discount information, product touch information, and sale proneness interact to determine consumers' responses. Perceived quality is the underlying mechanism behind the observed effects. For nonsale-prone consumers, product touch information favorably influences responses to large price discounts by addressing product quality concerns and enhancing purchase confidence, but has no effect for regularly priced or low discounted products. For sale-prone consumers, product touch information is not effective in increasing their responses regardless of the discount size. A qualitative study provides support for these results and highlights the role of perceived quality and purchase confidence. The research contributes to behavioral pricing, cue utilization theory, and sensory marketing and suggests that marketing managers should provide consumers with product touch information when implementing high discounts for products for which prepurchase touch is important.     

Segmentation in direct marketing channels: a transaction-patterns based method

This paper presents a method designed to segment a customer file for direct marketing using behavioral data. The results of this method are tested against the traditional Recency-Frequency-Monetary Amount segmentation model, as well as other parameters of consumer behavior. Strategic applications and future research orientations are suggested.     

A sequence analysis approach to segmenting credit card customers

This research examines the longitudinal relationships between patterns of customer loyalty behavior and firm financial outcomes in the context of credit card use. By examining credit card users' transactions with a focal bank and its competitors, this study creates a typology of loyalty behavior and employs a sequence analysis to segment customers on the basis of their behavioral patterns exhibited over time. The analysis results in six distinct customer segments: Loyalist, Switching Loyalist, Switching Defector, Defector, Dormant Loyalist, and Dormant Defector. We subsequently estimate the revenue, servicing costs, and profitability associated with each segment, and assess differences across segments. We discuss the implications for managing distinct credit card customer segments and optimizing the bank's marketing resource allocation.     

Customer segmentation by web content mining

This article introduces a new dimension, Interpurchase Time (T), into the existing RFM (Recency, Frequency, and Monetary) model to form an expanded RFMT model for parsing consumers' online purchase sequences in a long period to implement customer segmentation. The proposed RFMT model can track and discern changes in customer purchasing behaviors during their whole shopping cycle. Firstly, a web content retrieving system was developed to fetch publicly available customer data on a retailer's website, including demographic information (gender, age, location, etc.) and product information (name, price, date, etc.) of each purchase in a period from 2008 to 2019. The RFMT values of a customer were then computed from the retrieved data and subsequently analyzed by the hierarchical clustering to derive seven homogeneous clusters with specific customer profiles. Subsequently, demographic features and product preferences were identified for each cluster with business insights that can help the retailer to improve customer relationships and to implement targeted recommendation strategies.     

Identifying the critical factors of customer behavior: An integration perspective of marketing strategy and components of attitudes

The purpose of this empirical study is to operationalize the relationship of green marketing's influence on consumer attitudes via the mediating role of marketing mix towards green products to validate the proposed research model in the Taiwanese context of explaining consumers' willingness to be environmentally friendly. The model is based on structural equation modeling (SEM) from data collected from 977 online consumers. The findings revealed that green consumption intention was significantly and indirectly driven by attitude to green products. Additionally, the effect of perceived quality on marketing mix and consumer willingness in environmental concern is both significant and positive. However, when a restaurant has high consumer social responsibility (CnSR) for marketing mix, the consumer attitudes of cognitive, affective, and behavioral model (C-A-B model) is less effective. These findings have contributed to the revival of the theory of planned behavior (TPB) and offer a comprehensive understanding of consumer attitude, consumer social responsibility, marketing mix and perceived quality impact that a restaurant has on the ability to raise consumer willingness to purchase green products or food. We provides valuable suggestions to marketers to design from the perspective of green marketing policies and strategies in order to accommodate Taiwan's indigenous green restaurants.     

Evaluating discounts as a dimension of customer behavior analysis

Today, increased competition between organizations has led them to seek a better understanding of customer behavior through identifying valuable customers. Customers’ expectations about the price and quality of products and services play an important role in their selection process. In online businesses, competition and price differences between suppliers is high, so discounts will attract different customers. As a result, discounts and the frequency and amount of purchases can lead to better understanding of customer behavior. Customer segmentation and analysis is essential for identifying groups of customers. Hence, this study uses a model based on RFM called RdFdMd, in which d is the level of discount used to analyze customer purchase behavior and the importance of discounts on customers’ purchasing behavior and organizational profitability. The CRISP-DM and k-mean algorithm were used for clustering. The results indicate that using the R_dF_dM_d model achieves better customer clustering and valuation, and discounts were identified as an important criterion for customer purchases.     

Antecedents of Taiwan Chinese Consumers’ Purchase Intentions Toward U.S.- and Japanese-Made Household Appliances

ABSTRACT

The purpose of this article is to understand the factors influencing Taiwan's Chinese consumers’ purchase intentions toward U.S. and Japanese household appliances. The authors attempt to develop and test a comprehensive model linking such purchase intentions to several constructs including Taiwan Chinese consumers’ openness to foreign cultures, consumer nationalism, product familiarity, traditional cultural values orientation, and product-country image. The result of analysis using structural equation modeling shows that consumer nationalism has a strong indirect effect on purchase intention via the product-country image construct. Taiwan Chinese consumers’ traditional cultural values orientation and openness to foreign cultures have direct effects on consumer nationalism and, hence, are important antecedents in explaining the purchase intentions toward foreign-made goods by Taiwan Chinese consumers. With the growing importance of the Chinese domestic market, this study provides international marketing managers with practical implications in important areas such as market segmentation, branding strategy, and market research and practices in the Chinese consumer market.     

Cross-channel effects of omnichannel retail marketing strategies: A review of extant data-driven research

The authors review 50 empirical retailing research papers that have appeared over the last 20 years to take stock of what we know, need to know better, and do not know yet about within-retailer cross-channel effects of omnichannel retail marketing strategies on (a) consumer responses over their purchase journeys, i.e., online and/or offline search, purchase intention, frequency, amount, returns, loyalty, and (b) the retail firm's aggregate outcomes (e.g., sales, costs, profits, product returns) by channel and overall. Specifically, the authors focus on five strategies: (1) the addition of online channel by an offline retailer; (2) the addition (or subtraction) of offline channels by an online retailer; (3) addition of mobile shopping channel (website and/or app) by offline and/or online retailer; (4) cross-channel integration strategies; and (5) retail marketing mix strategies. The author/s integrate findings from empirical research on these strategies into a number of ‘insights’ about ‘what we know’. Prominent among these are the following: Adding a transactional online channel to an offline channel improves the retailer's overall sales even though offline channel sales can be cannibalized to some degree. Adding an offline channel by an online retailer, however, boosts online channel sales as well as overall sales of the retailer. Similarly, adding a mobile shopping channel usually increases customer purchase frequency and amount and overall sales of the retailer in the long-term. Strategies for greater cross-channel integration generally have a positive effect on a retailer's overall performance while online advertising has positive effects on offline channel consideration and sales as well as overall sales of a multichannel retailer. Other insights or findings that need further study or open questions are also identified. The paper closes with managerial implications of the derived empirical insights, and suggestions for future research.     

Students' Online Shopping Behavior: A Dual-Country Perspective

ABSTRACT

This study investigates the online purchase behavior of a key segment of the population, the “Net Generation” undergraduate college-aged student, from two of the countries with the greatest potential for e-marketing opportunity, the United States and Ireland. In addition to identifying college students' Internet activities, this research provides useful comparative information concerning how frequently students from each country interactively shop online, how much they spend, what they buy, as well as answer the question whether students from the two countries under study approach the Buyer Decision Process differently in their use of the Internet. The results provide useful guidance to electronic marketers.     

Factors influencing consumers' purchase decision-making in O2O business model: Evidence from consumers' overall evaluation

Online-to-offline (O2O) has become a rapidly growing e-commerce model worldwide, but the factors influencing consumers' purchase decision-making have not been examined well. After exploring the working mechanism of the O2O model, we extract eleven indexes of consumers' overall evaluation in the O2O model with Crawlzilla and R techniques. Social network analysis (SNA) is adopted to build social networks reflecting consumers' overall evaluation in the O2O model. Based on the modified social network and the extracted subgraph, this study (N = 768) reveals consumers' overall evaluation behavior patterns in the O2O model by calculating network density, central potential, edge betweenness. The results show that shoppers overall evaluate the eleven indexes, especially perceived product quality, online product price, promotion intensity, business reputation, and product brand, which reflects the significant associations between the indexes. Among all the eleven evaluation indexes, perceived product quality, online product price, and business reputation dominate consumers’ decision-making behavior. When making purchase decisions, consumers not only overall consider online product price, perceived product quality, and business reputation but also balance perceived product quality, business reputation, and promotion intensity. Finally, we make some suggestions on marketing strategy for e-commerce companies.