Benefit Segmentation – Definition

Cite this article as:"Benefit Segmentation – Definition," in The Business Professor, updated March 4, 2019, last accessed August 13, 2020, https://thebusinessprofessor.com/lesson/benefit-segmentation-definition/.

Back to: MARKETING, SALES, ADVERTISING, & PR

Benefit Segmentation Definition

Benefit segmentation is the clustering that is done based on the perceived value or benefits to the end customer. That is, most products offer one or more value proposition to intended customers. Customers may value the various value propositions of the product differently. As such, companies segment these customers based upon their preferred value offering. The company will then seek to more effectively market the product’s value proposition to those specific customers.

A Little More on What is Benefit segmentation

Market segmentation is a significant process in all marketing strategy. To illustrate market segmentation, imagine a market with ten various shoes without branding or description. The decision to purchase the shoes will be based on one or more customer values.

For example, the customer may desire comfort, fit, style, utility, etc. The customer market could be segmented into these various attributes for purposes of marketing.

The segmentation is beneficial to the managers of footwear companies in dividing their markets

References for Benefit Segmentation

http://www.businessdictionary.com/definition/benefit-segmentation.html

https://www.marketing91.com/benefit-segmentation/

https://product2market.walkme.com/benefit-segmentation-examples/

Academic Research on Benefit Segmentation

  • Benefit segmentation: A decision-oriented research tool, Haley, R. I. (1968). The Journal of Marketing, 30-35. The author indicates that even though the Descriptive factors relating to purchase are the sole base upon which the market segregation is based, it fails in the potential buyer behavior’s forecast. The paper market segmentation approach to demarcating based factors related to future behavior. The approach emphasizes the availability of true market segments as a result of the benefits people are looking from using some of the products.
  • Step Two in Benefit Segmentation: Learning the Benefits Realized by Major Travel Markets, Woodside, A. G., & Jacobs, L. W. (1985). Journal of Travel Research, 24(1), 7-13. There may be a wide variation of the benefits derived from product usage in different segments. Benefits of traveling to the same holiday destination by three different national’s shoes that rest are the significant benefits for Canadians compared to cultural experiences for Americans and family unity among Japanese. The paper concludes that each national market has a different market strategy that provides maximum benefits.
  • A clusterwise regression method for simultaneous fuzzy market structuring and benefit segmentation, Wedel, M., & Steenkamp, J. B. E. (1991). Journal of Marketing Research, 385-396. The proposed Generalized Algorithm for Fuzzy Clusterwise Regression (GFCR) that involves both benefit segmentation and market structuring in the preference analysis framework. There is the simultaneous estimation of the experimental parameters related to dimensions of the product in all cluster numbers, brand degree membership, and subject into the cluster. Monte carols examination on which generalized algorithm for fuzzy clusterwise regression is based involves brand preference data application of margarine and data is showed, the evaluation of the GFCR’s performance was done.
  • Seasonal segmentation of the tourism market using a benefit segmentation framework, Calantone, R. J., & Johar, J. S. (1984). Journal of Travel Research, 23(2), 14-24.  In the examination of the travel market segmentation initiative, options were found to be varying in different seasons and were affected by different factors. Each annual benefit varied and the number of people with bundled preference may vary from one season to another.
  • A benefit segmentation of tourists in rural areas: a Scottish perspective, Frochot, I. (2005). Tourism Management, 26(3), 335-346. As a result of the value addition of rural tourism in rural communities’ sustainability, rural tourism has been subjected to examination for years. There has been little inclusion of rural tourists even though their impacts and features have been subject for discussion. The paper deals with the examination of two Scottish tourists, and it shows the possibilities of the sample clustering based on the benefits required. The outcome of the examination provided evidence of different segment profiles regarding their roles and their behavior and the socio-economic characteristics.
  • A benefit segmentation of the major donor market, Cermak, D. S., File, K. M., & Prince, R. A. (1994). Journal of Business Research, 29(2), 121-130.  The author talks of the wealthy individual’s significant influence by the largely charitable trust created in the $230 billion nonprofit sectors. The segmentation of the wealthy population based on deeper of their giving’s motivation and their established relationships with nonprofit beneficiaries. There have been impacts of the four generous market profiles on nonprofit entity’s marketing activities in addition to motivational philanthropic motivational advancement
  • Benefit segmentation in industrial markets, Mariorty, R. T., & Reibstein, D. J. (1986). Journal of Business Research, 14(6), 463-486. The paper examines whether or not historical bases of segmenting industries, for instance, SIC codes and company size develops segments that are similar internally and different externally in regards to benefits being searched. The study is on the acquisition of nonintelligent information intelligence. The finding was that the historical factors do not result in segments with major varied dimensions. Additionally, the traditional approach produced segments with major differences from the benefit segmentation.
  • Benefit segmentation: a potentially useful technique of segmenting and targeting older consumers, Ahmad, R. (2003). International Journal of Market Research, 45(3), 373-390. The paper outlines the UK population growth to around 20 million people aged 50 years and above. These people provide new market opportunities and any company that decides to ignore them should be ready for the consequences. Marketers utilize the individual features relating to socioeconomic, demographic and psychographic data as a factor for older people segmentation. The paper outlines the application benefit segmentation for older consumers’ segmentation and targeting.
  • Benefit segmentation for fundraisers, Harvey, J. W. (1990). Journal of the Academy of Marketing Science, 18(1), 77-86. The paper deals with the establishment of the applicability of benefit segmentation to generous American’s gift-giving behavior. Fundraising and restaurant benefit segments were developed from a representative population within the continental United States. Face and predictive validity and strategic practicality were demonstrated by the five donors that were presented. The findings of the donor and community-based factors are useful indicators for donor segment differences.
  • Benefit segmentation–20 years later, Haley, R. I. (1984). Journal of Consumer Marketing, 1(2), 5-13. Benefit segmentation technique has been a common method of market examination to expose segment opportunities. There have been many attempts to utilize this segmentation technique by nearly all major consumer goods and services’ marketers with different success degrees. In this paper, the originator undertakes the examination of justification for the variations, offering proper use guidelines and suggests directions for more method improvements.
  • Consumer benefit segmentation using clusters linear regression, Wedel, M., & Kistemaker, C. (1989). International Journal of Research in Marketing, 6(1), 45-59. The Cluster Wise Linear Regression method generalization is suggested for benefits segmentation. A consumer with the same preference to perceived product dimension was found within segments. This method is very useful mostly when there are small and collinear sets that evoke consumers, and this affects the estimation of an individual’s level preference model. With the FORTRAN computer clustering software, data preference regression is described and the investigation of algorithm performance on synthetic data. Aged people meat’s preference application was given and unique considerations granted to Monte Carlo testing methods and centralization to internal optima.
  • Market segmentation: a review, Beane, T. P., & Ennis, D. M. (1987). European journal of marketing, 21(5), 20-42. The paper states the importance of creativity in the performance of segmentation examination as there is the existence of many ways of market segmentation. The five major ones include: geographic, demographic, psychographic, and behavioristic in addition to the image. The summary of the major techniques for the establishment and verification of segments including the interaction detectors, conjoint analysts, multidimensional and canonical examination follow.

Was this article helpful?