Private companies and public institutions increasingly want research programs that focus on ethnic and religious minorities. Companies want to tailor their offer to specific target groups and institutions aim to combat discrimination although some politicians do not rule out so-called positive discrimination for minorities. Identifying people within a specific ethnic or religious group is not easy. We normally have three classifications: immigrants, ethnic minorities and religious minorities. These terms may be defined and interpreted differently depending on the language and country involved, which is why it is crucial for the research industry to agree on unambiguous and globally valid definitions. The work of the EU Agency for Fundamental Rights (FRA) could be helpful in this respect.
While regional classification systems have been developed for both Latin America and Europe, it is increasingly evident that a harmonized social economic classification system that spanned all countries - retaining accuracy and relevance - is necessary. This paper addresses the need for such a system and discusses the approach taken, as well as the applications of the system to meet the needs of advertisers, advertising agencies and media owners.
This paper aims to inform marketers and researchers interested in Mexico's market about how the Mexican Association of Research and Public Opinion Agencies (AMAI) has dealt with the problem of defining a common ground where all parties involved (research, advertising and media agencies, along with advertisers) talk the same language in terms of socio-economic levels. Additionally the paper aims to make a brief comparison among the SEL classifying systems used in the three main economies of the Latin American world in order to provide a first approach to what could in the near future become a simple rule of 'comparability' among the three systems. This idea does not mean, at this moment, to create a unique classifying system for the three countries. On the contrary its aim is to look for ways in which the outcomes of the already developed statistical models for classifying households could be more comparable. Nevertheless, in the future a common system should be jointly created by the professional research associations involved.
Customers are increasingly demanding, and successful companies need to design and introduce new ways to offer customer value. However, the process is not complete until they design control systems, provide a support decision tool able to identify and distinguish customer behaviour profiles according to their loyalty, and help marketers to readapt relationship marketing strategies in order to increase efficiency. LAMDA (Learning Algorithm Machine for Data Analysis), an artificial intelligence technique software tool enabling forecasting and identification of customer behaviour, is based on a self-learning classifying technique that relies on the generalizing power of Fuzzy Logic and the interpolation capability of logical hybrid connectives. This paper specifically examines the efficiency of the LAMDA classifier in identifying and distinguishing between the various degrees of customer loyalty. The study carried out in this project is based on data gathered from the customer loyalty cards of a Spanish grocer, Supermercats Pujol, S.A.
ESOMAR has sought ways to help standardise some of the procedures used in market research surveys. This does not in any way imply that we are seeking to treat Europe or any other part of the world as single homogeneous markets. On the contrary, our aim is to look for ways in which the tools we use in research can be made more comparable from one country to another so that the true diversity of the marketplace can be more readily identified. This chapter reports work carried out over a number of years. It represents an attempt to develop a common system for assessing the social and economic standing of the populations in the various countries of Europe. The system is designed for Europe, but we believe that it may also have applications in other parts of the world, either as it stands or in a modified form.
This chapter describes how in a heterogeneous market, such as India, a single socio-economic classification system is not sufficient to discriminate across various product categories. It demonstrates a new basis of segmenting households on life style related parameters which, unlike the existing system, work very well for premium products and services. The results are based on experiments carried out during the last four years.
Brazil may well be the country with the largest experience of using a uniform socio-economic classification system in the world. It adopted one such system in 1970, as a result of the recommendation proposed by a panel nominated by the National Association of Advertisers (ABA). It has been revised and updated five times since then. The history of the Brazilian experience does not matter as much as the lessons we derive from it, which may be relevant for the future. We summarise here what we think those lessons are, and also explain how a common, uniform criterion was or can be achieved. We also mention the difficulties found in twenty-seven years of experience, from the purely technical to the fieldwork limitations that have an impact on the results of any classification system.
This paper is intended to provide a much needed social grading for rural India. The problems in defining a rural socio-economic classification in India are presented and the previous efforts in this direction are discussed. The drawbacks of these attempts are highlighted and a novel approach is adopted to identify the powerful discriminators. Based on this approach a socio-economic classification is recommended. Using two large databases of rural India the discriminating power stability and other desirable features of our proposed classification are assessed. Rural SEC as defined by us emerges as a clear winner when compared with other potent and promising candidates. It is believed that this classification will fulfill the requirements of both research users and practitioners for years to come.
The objective of this guideline is to aid researchers and research users in the field of international research. It endeavours to provide a pragmatic guide and advice to those wishing to apply the ESOMAR Social Grade in everyday research and forms a common source of reference for researchers not only in Europe but throughout the world.
This paper describes how in a heterogeneous market, such as India, a single socio-economic classification system is not sufficient to discriminate across various product categories. It demonstrates a new basis of segmenting households on lifestyle related parameters which, unlike the existing system, work very well for premium products and services. The results are based on experiments carried out during the last four years to develop the same.
This paper seeks to demonstrate that we can improve our use of research as a creative tool by using and classifying more effectively the range of mindsets and abilities that exist amongst our raw material - people.
This paper demonstrates the applicability of the L-O-V (List of Values) in Venezuela as a means of consumer classification, as well as the steps taken for its adaptation to the local context. To test initial applicability within the marketing context, it was applied to help describe possible purchase and/or usage motivations for some key state-of the-art consumer durables among middle and upscale urban respondents.