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Knowing your customer, i.e. your target market, is critical for the success of a company and its’ products. The current socio-demographic changes in the United States issue new challenges to marketers and practitioners. Actual fashion consumer seg-mentation approaches within the United States have received little attention in media and scholarly literature. Therefore, the aim of this paper is to present the existing academic literature addressing fashion consumer style preferences, particularly highlighting the most promising consumer groups within the United States: Hispanics and African-Americans. For this, a literature review was chosen with a subsequent critical discussion and comparison of both segments including findings of academic researches as well as market research agencies and actual lifestyle clustering approaches regarding these consumer groups. The findings show, whilst the published literature on consumer segmentation in the apparel industry provides only a surficial understanding of the fashion buying behaviors of Hispanics and Black Americans, it could be found that both ethnic groups are highly interested in fashion, price sensitive, and they are over indexed in apparel spending habits. Especially within the Hispanic population factors such as age and level of acculturation play a vital role in the purchasing choice of apparel, footwear and accessories and require further research.
The following paper is dealing with the issue on which actual consumer lifestyle segmentation methods there are for particular European countries and accordingly for Europe as a whole. This is important for corporations to be able to place their products accurately by a consumer orientated marketing concerning the constant change of values and minds. Researching current literature, internet sources and documents, the state of the science is presented by a detailed description of the most popular lifestyle segmentation methods used in European countries. In addition to that, these instruments are discussed individually and then compared to each other. All instruments, the Sinus-Milieus, Euro-Socio-Styles, Roper-Consumer-Styles, RISC and Mosaic, are serving the same purpose even so they differ pretty much from each other. Each market research company has its own method to generate their model just as different segments and definitions for them. Furthermore every segmentation method is illustrated in a different way. This paper demonstrates all these instruments in detail and shows its advantages and disadvantages. Summing up literature research concerning the main research question, there are several models segmenting consumers in different lifestyle groups for e.g. in Germany, France or Great Britain, but still less models referring to the entire European market.
In a globalized world the importance of a proper segmentation method for identifying target consumers has been increasing. Vast majority of the research in this area focuses on the usage or development of different techniques. Lifestyle is a good criterion for dividing people into groups which then can be better targeted. This article addresses the research question, which classical methods exist to segment markets with the aid of lifestyle. The purpose of this paper is to illustrate several instruments, such as A.I.O., Roper Consumer Styles, VALS-Method, the Sinus-Milieus, Sigma-Milieus, RISC-Method and Semiometrie but also Discriminant and Conjoint Analysis which proved of value in the past. Furthermore it deals with the benefits of this methods but weaknesses are also considered. Therefore several existing literature is examined, and information is collected by institutes providing the typologies. Obvious is, that new methods e.g. predictive analytics already play a major role in marketing, because it can be found much literature about it. In the literature research also appear research implications, because besides the provided information from institutes and journals, there is hardly no data to find if and how companies use the instruments. Furthermore, some important databases cannot be scanned because they are not accessible without paying.
Purpose of this research paper is to assess the state of the art concerning the relevance of consumer segmentation models in the fashion industry with regards to current changes in technology, market structure and consumer behavior.
The paper is composed of a qualitative literature review and an empirical study in form of a survey. They are contrasted in order to identify both similarities and differences.
Findings reveal that consumer segmentation is still relevant. Notwithstanding, an adaptation of classification models is necessary according to occurring changes. External models, segmenting consumers by means of lifestyle or fashion typologies, are used. However, it is striking that most companies of the empirical study already apply internal segmentation models with tendency to rise. Moreover, research has shown that consumer classification models in the USA make use of different criteria than in Europe.
Language barriers within the literature review and a low sample size in the empirical study give research limitations. Future management implications can be directed to the identification of procedures for the efficient application of internal segmentation models.
This case study of Breuninger aims to analyze how Breuninger adapts to the emerging omnichannel environment in fashion business. From a consumer’s perspective Breuninger and the general omnichannel strategy of Breuninger is explained, before the loyalty program of Breuninger is analyzed in detail. Key factors as the mobile app and the mobile Breuninger card, social media, direct mail and in-store capabilities are described. A discussion chapter finalizes the case.
Loyalty programs become more important in an omnichannel environment of fashion retail business. After the definition of customer loyalty and loyalty programs the main characteristics of omnichannel loyalty programs are described. As touchpoints of omnichannel loyalty programs mobile, social media, direct mail and in-store capabilities are detailed. A discussion chapter closes with recommendations for fashion retailers.
This case study describes the emerging customized omnichannel loyalty solution of Marc O’Polo from a customer’s perspective. After the introduction of Marc O’Polo and their general omnichannel strategy, the loyalty program is described in detail, like Marc O’Polo for members and the mobile app, social media, direct mail and in-store capabilities. A discussion chapter closes the case study with research implications and open questions for Marc O’Polo.
Like many others, fashion companies have to deal with a global and very competitive environment. Thus companies rely on accurate sales forecasts - as key success factor of an efficient supply chain management. However, forecasters have to take into account some specificities of the fashion industry. To respond to these constraints, a variety of different forecasting methods exists, including new, computer-based predictive analytics. After the evaluation of different methods, their application to the fashion industry is investigated through semi structured expert interviews. Despite several benefits predictive analytics is not yet frequently used in practice. This research does not only reflect an industry profile, but also gives important insights about the future potential and obstacles of predictive analytics.
In times of e-commerce and digitalization, new markets are opening, young companies have the possibility to grow and new perspectives arise in terms of customer relationship. Customers require more possibilities of personalization. In the same time, companies have access to new and especially more information about the customer. Seems like it was a correlation that could evolve greatly if there weren't privacy issues. Vast amount of data about consumers are collected in Big Data warehouses. These shall be analyzed via predictive analytics and customers shall be classified by algorithms like clustering models, propensity models or collaborative filtering. All these subjects are growing in importance, as they are shaping the global marketing landscape. Marketers develop together with IT scientists new ways of analyzing customer databases and benefit from more accurate segmentation methods as that have been used until now. The following paper shall provide a literature review on new methods of consumer segmentation regarding the high inflow of new information via e-commerce. It will introduce readers in the subject of predictive analytics and will discuss several predictive models. The writing of the paper is not based on own empirical researches, but shall serve as a reference text for further researches. A conclusion will complete the paper.