一种商业银行客户分割的多维方法——基于客户期望收益和态度的分割模型

客户分割与资源分配是企业一直在努力解决的问题,但目前,空前巨大的客户数据量使得准确进行市场细分和寻找目标市场变得复杂和难以有效实施。通过数据挖掘技术从大型数据库中抽取隐藏的预测信息,利用层次聚类分析建立了一个根据客户的多个态度维度进行客户分割的多维方法。结果表明,以这一方式产生的聚类在同质性较好并且通过参考人口学特征的差别能够获得客户细分市场的轮廓。此外,识别了四个有特色的、表明对信息服务和技术有特殊偏好的客户群。     

Customer segmentation in retailing based on retail brand patronage patterns

In this study, we propose an alternative method for customer segmentation based on households’ retail brand portfolios. We suggest blockmodeling, a method that is rooted in social network analysis, to identify homogeneous groups of customers being characterized by similar patronage patterns. In a second step, we combine this method with psychometric analyses to examine group differences based on sociodemographic and purchasing behavior variables. To illustrate our approach, we use a sample of 500 households out of a panel data set of 36,502 German households in the fast-moving consumer goods sector. The findings of our analyses yield support for our assumption that our methodology, taking into account the relationship between households and the different retail brands they patronize, provides a broader understanding of the antecedents of households’ multiple store patronage strategies, leading eventually to a new form of customer segmentation.     

A structural equation model of latent segmentation and product choice for cross-sectional revealed preference choice data

We consider the problem of simultaneously performing market segmentation and predicting product choice for a given population of consumers. This behaviour-based segmentation model uses several types of information characterizing individual consumers and their market context: sociodemographic, psychographic and product choice data. These data are combined in a normative conceptual framework that posits the formation of latent segments, each of which displays differing degrees of sensitivity to relevant product attributes. This permits results obtained by the proposed model structure to differ significantly from those of traditional segmentation techniques, which usually produce a set of groups characterized by smaller within-group than between-group variation in sociodemographic and/or psychographic variables. By making the segments behaviour-based, it is argued that the segments produced by the model will be more actionable and more directly relevant to management decision-making. The proposed model is applied to a data set involving choice of a beauty product offered by five national brands. The results show that the explanatory power of the latent segmentation and choice model is far greater than that of the MNL model, which is nested within our more general specification. The types of results available from the model are illustrated through the application.     

Segmentation and market structure when both consumer and situational characteristics are explanatory

This article addresses the problem of exploring data for useful segments (and subsequently, market structure) in markets in which demand is a function of both consumer and situational characteristics. Current exploratory segmentation methods use either persons or situations as the unit of analysis, but not both. Yet choice and needs are frequently an unknown function of both personal characteristics and situational characteristics. Under these conditions of unknown strength of sources of influence, it may be advantageous to explore data. To allow the fruitful use of data exploration, we propose the use of a unit of analysis we call the person-in-situation, sampling of these units from their population, segmentation of these units with respect to choices, and the post-hoc exploration of such segments for regularities in individual and situational characteristics.     

Using segment level stability to select target segments in data-driven market segmentation studies

Market segmentation is widely used by industry to select the most promising target segment. Most organisations are interested in finding one or a small number of target segments to focus on. Yet, traditional criteria used to select a segmentation solution assess the global quality of the segmentation solution. This approach comes at the risk of selecting a segmentation solution with good overall quality criteria which, however, does not contain groups of consumers representing particularly attractive target segments. The approach we propose helps managers to identify segmentation solutions containing attractive individual segments (e.g., more profitable), irrespective of the quality of the global segmentation solution. We demonstrate the functioning of the newly proposed criteria using two empirical data sets. The new criteria prove to be able to identify segmentation solutions containing individual attractive segments which are not detected using traditional quality criteria for the overall segmentation solution.     

Segmentation of both reviewers and businesses on social media

Employing online consumer reviews, this research develops a market segmentation procedure that is feasible to businesses present on social media. Because online reviews typically encompass large numbers of both reviewers and businesses, this data structure allows for both reviewer segmentation and business segmentation. This two-side segmentation approach segments not only reviewers in the preferences expressed in their reviews, but also businesses in their business practices specified in the reviews. Whereas common existing segmentation approaches predominantly use survey and transaction data, the proposed procedure uses publicly available and detailed consumption information in such reviews. A large number of product features elicited from such reviews lead to rich and detailed profiling of both reviewer segments and business segments. Using restaurant reviews on Yelp, this research demonstrates how the proposed procedure can help businesses develop segmentation strategies on social media.     

When and how consumers are willing to exchange data with retailers: An exploratory segmentation

Consumer data is a crucial resource for retailers. Yet accessing this data increasingly requires consumers to willingly participate in data exchange. This paper draws on social exchange theory and privacy calculus to investigate differences in consumer willingness to exchange data with retailers. Consumers are also profiled on their perceptions of retailer's use and abuse of data, along with the antecedents and outcomes of these perceptions. We employ a cross-sectional quantitative survey and collect data from a sample of 463 US consumers. For statistical analysis, we employ a latent class segmentation and identify six consumer segments which differ in their perceptions of the consumer-retailer data exchange. The key drivers of these segment differences include privacy concerns, technology readiness, and general trust of, and engagement with, retail brands. The segments also differ in their subsequent views towards the use and abuse of their data by retailers, including willingness to exchange data. Hence, when accessing and utilizing consumer data, it is important that brands identify different segments, and adapt their approach accordingly.     

Struggles in optimal labelling: how different consumers react to various labels for genetically modified foods

The labelling of genetically modified (GM) foods is an important policy issue, as consumers' attitudes towards these foods appear to be quite sensitive to information about their potential benefits and risks. Because it is difficult for labels to differ across consumers, differences in reactions to label information could lead to conflicts across consumer groups or to different market outcomes. Using factor and cluster analysis, we uncover three consumer segments with different attitudes to the risks and benefits of GM foods. Our segmentation‐based analysis on consumer reactions to information points out important differences across consumers. Not only did we find differences across segments in how they view the credibility of GM‐related information, we also find differences in how information influences segments' perceptions of the product, and in their likelihood to buy.     

Response style corrected market segmentation for ordinal data

Survey data collected for market segmentation studies is typically ordinal in nature. As such, it is susceptible to response styles. Ignoring response styles can lead to market segments which do not differ in beliefs, but merely in how segment members use survey answer options and which possibly occur in addition to the belief segments. We propose a finite mixture model which simultaneously segments and corrects for response styles, permits heterogeneity in both beliefs and response styles, accommodates a range of different response styles, does not impose a certain relationship between the response style and belief segments, and is suitable for ordinal data. The performance of the model is tested using both artificial and empirical survey data.     

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.     

Status consumption and ethnicity in Bolivia: evidence from durables ownership

The ‘compensatory consumption’ hypothesis advanced by Caplovitz in 1967 predicts that households facing racial or ethnic discrimination tend to spend heavily on socially visible consumption goods to make up for their low‐status position in society. This paper provides an empirical test of this prediction in Bolivia, where people of indigenous origin face social exclusion. Using recent household survey data, we examine whether low‐income households of indigenous origin overspend on socially visible durable goods relative to equally poor, non‐indigenous households. We find a marked difference in the propensity for compensatory consumption between the two largest indigenous groups in Bolivia.     

Identifying multi-channel value co-creator groups in the banking industry

The purpose of this paper is providing a value co-creation management framework in the banking industry using the data analysis. Moreover, a multi-channel segmentation approach will be developed in order to identify customer segments based on the use of each channel. Managing value co-creation can be defined as determining the channel that may be used by the customer and the kinds of encounters that lie in these channels to have different impacts on the customer for various types of encounters. The model is built on the basis of the related literature and the collaboration of a Customer Relationship Manager in a large bank in Iran. Then, a multi-channel segmentation model is developed based on the RFM variables of the five banking channels for each customer. Next, about 11,000 customers of the bank is segmented by comparing the k-means and DBSCAN algorithms. Finally, by adapting customer segments on the value co-creation framework, three general groups are identified based on the type of encounter that lies in each channel. Moreover, twenty-seven small groups are recognized based on the desirability of the customer use of the channels.     

A segmentation study of Israeli mall customers

The study presents a segmentation of Israeli mall customers. The study sets three goals: developing a typology of Israeli mall customers based on their behaviors; examining the socio-demographic profile of each segment; and comparing Israeli customers to customers from other countries. The behaviors in this study are divided into three categories: visiting patterns; motivations for trips to the mall; and activities engaged in during the visit. Data were obtained from 636 Israeli customers. The main findings suggest four groups of customers: Disloyal, Family Bonders, Minimalists and Mall Enthusiasts. The segments were found to differ in socio-demographic characteristics. The study results can serve as a marketing tool for retailers.     

Searching for latent class segments in technological services

The focus in this article is on uncovering segments that describe mobile phone users and on investigating the nature of these segments to get some relevant information. We use a phased approach to reach this objective. First, two segmentation bases have been compared in order to select the best variables for the identification of groups. This is done using a latent class modelling approach. Second, two different segmentation techniques are examined looking for the best model fit. Finally, the model that achieves the best results is applied to the most significant segmentation variables with the purpose of uncovering segments that describe mobile phone users.     

shopper taxonomy for retail strategy development

Segmentation of shoppers has been explored by many academic researchers and business practitioners seeking to understand shopping behaviour or to develop marketing strategies for particular customer groups. Market segmentation holds the key to successful marketing strategy as it encourages understanding of the key variables that differentiate specific segments.

The shopper taxonomy determined through this study is based on a set of variables that is relevant and appropriate for shopper segmentation and reflects the key aspects important to shoppers in motivating shopping behaviour towards a specific retail location. This taxonomy extends the proposed motivational taxonomy of Westbrook and Black (1985), derived from Tauber's (1972) earlier research. Westbrook and Black defined this taxonomy through shopping motives, and identified categories of product-oriented, experiential and a combination of product and experiential shoppers. Their research findings, however, pointed to a six-cluster typology, defining department stone shopping around seven motivations aligned with evaluating options and acquiring the products, engaging in the sales process and gaining stimulation and affiliation through the retail environment.

The “apathetic”, “shopping-processed involved” and “choice optimisation” shopper segments described by Westbrook and Black align with the “have to” “experiential” and “practical” “segments found in this study in terms of their focus on the shopping activity itself and the affiliation and stimulation motives associated with the shopping activity. Other associations between shopper segments across the two studies are less clear, and may be explained through the differing purposes for which the studies were undertaken and resulting variation in the measures used to define the motivational constructs.     

The Relationship between Retirement Wealth and Householders' Lifetime Personal Financial and Investing Behaviors

While previous research indicates wide wealth dispersion at retirement within households with similar lifetime incomes, there have been few attempts to identify personal financial behaviors associated with retirement wealth in households matched for lifetime income. Householders with similar demographics and lifetime income but differing markedly in net worth near retirement were surveyed in terms of personal financial behaviors undertaken during their lifetime. Results revealed key differences between householders with low and high retirement wealth in their financial behaviors and how these were acquired.     

Who will adopt electric vehicles? Segmenting and exemplifying potential buyer heterogeneity and forthcoming research

Market segmentation becomes a crucial tool for evolving transportation technology such as electric vehicles (EVs) in emerging markets to explore and implement for extensive adoption. EVs adoption is expected to grow phenomenally in near future as low emission and low operating cost vehicle, and thus, it drives a considerable amount of forthcoming academic research curiosity. The main aim of this study is to explore and identify distinct sets of potential buyer segments for EVs based on psychographic, behavioral, and socio-economic characterization by employing an integrated research framework of ‘perceived benefits-attitude-intention’, The study applied robust analytical procedures including cluster analysis, multiple discriminant analysis and Chi-square test to operationalize and validate segments from the data collected of 563 respondents using a cross-sectional online survey. The findings posit that the three distinct sets of young consumer groups have been identified and labelled as ‘Conservatives’, ‘Indifferents’, and ‘Enthusiasts’ which are deemed to be buddying EV buyers The implications are recommended, which may offer some pertinent guidance for scholars and policymakers to encourage EVs adoption in the backdrop of emerging sustainable transport market.     

Sparen in Zeiten niedriger Zinsen — wirtschaftspolitische Unterstützung nötig?

Critics of the low interest rate environment claim that German households have had difficult times generating positive returns from their savings since interest rates reached levels around zero. Therefore, direct public support is increasingly being called for. This article shows that, from a macroeconomic perspective, households have in fact generated positive real returns to date. However, portfolio returns may vary among households due to differences in portfolio structure and size. In addition, aggregate portfolio returns might decrease in the years to come if nominal interest rates remain low. Regarding policy responses, it is therefore proposed to undertake measures which increase total factor productivity and improve the financial literacy of households. Both approaches promise to be more effective than direct public support of savings.     

An Examination of the Relationship Between a Firm's Offerings and Different Customer Loyalty Segments

Purpose: Loyalty reflects the highest state in the buyer–seller relationship and occurs when repeat patronage and commitment are both high. One generally accepted model of segmenting the customers by degree of loyalty includes 4 categories of loyalty: no loyalty, latent loyalty, spurious loyalty, and loyalty. This study examines the relationship between these 4 customer segments and their evaluation of the firm's offerings.

Methodology/approach: This study uses self-reported purchase behaviors and attitude toward the seller for segmentation. Buyers report the importance of and satisfaction with 15 different offerings or processes. The mean scores for the 4 different groups are compared and tested for statistical significance.

Findings: The loyalty segments differed in the importance placed on customized products. The loyalty and spurious loyalty groups placed a higher importance on receiving customized products from the seller. The loyalty segments also differed in their levels of satisfaction, but these differences did not fully explain repeat patronage behavior. The latent loyalty group, despite their higher levels of satisfaction with standardized offerings, purchased less than the spurious loyalty group.

Originality/value/contribution: The implication for managers is that, if properly identified and managed, understanding these differences could lead to a sustainable competitive advantage. Managers can build loyalty by applying specific tactics tailored to the customer segment.