A Benefit-Based Approach To Market Segmentation: A Case Study of an American Specialty Coffeehouse Chain in Hong Kong

Abstract

Specialty coffeehouses have become an increasingly important segment of the foodservice industry in Hong Kong. The exponential growth of this segment has generated keen competition. Without a good understanding of their customers, these coffeehouses may end up losing market share to competitors. The purpose of this study is to identify the market segments in Hong Kong specialty coffeehouses based on the benefits sought by customers when they visit specialty coffeehouses. A survey of 1,000 customers was conducted. The results of this study support the effectiveness of segmenting the specialty coffeehouse customers in Hong Kong using the benefits variable. Four distinct segments of customers were identified: service seekers, atmosphere seekers, quality coffee seekers, and marketing-oriented customers. Based on the differences in coffeehouse selection factors, sociodemographic variables, and coffee consumption behaviors among the four segments, managers of specialty coffeehouses in Hong Kong can customize their strategies to meet the needs of these four market segments.

Importance‐performance analysis with benefit segmentation of spa goers

“…He suggested that benefit segmentation allows a clear understanding of consumer behavior and a better focus on the products and services required in the different market segments. Similarly, Tan and Lo (2008) supported the effectiveness of using benefit variables to segment the customers of specialty coffeehouses. The authors argued that the benefit variables identified in their study could be useful to managers of specialty coffeehouses when customizing marketing strategies to meet the needs of different market segments.…”

Hospitality marketing research: Recent trends and future directions

“…Three studies each were conducted in the foodservice and hotel industries. In the foodservice industry, Tan and Lo (2008) pursued a benefit-based approach, identifying four distinct segments of patrons for a specialty coffeehouse chain. The other two restaurant-focused articles studied issues relating to the creation of wine lists Gil et al, 2009).…”

A contrast analysis of online hotel web service purchasers and browsers

“…(Chung et al, 2004;Fü ller and Matzler, 2008;Tan and Lo, 2008). From a methodological point of view, clustering algorithms learn to group data patterns by inspecting the similarities between different input records, and the clustering result is that the degree of similarity among users within the same group is maximized, whereas that between different groups is minimized.…”