Benefit Segmentation in Seaside Destination: A Domestic Tourism Perspective

The primary purpose of this study is to examine the benefits sought by domestic tourists and activities they’re involved in while in Kuala Terengganu. A self-administered survey was obtained from a sample of 382 domestic tourists that visited the state. Cluster analysis, the Kruskal-Wallis Test, and Mann-Whitney Test were employed to examine the benefit segment variables. Results from the cluster analysis show that there are significant differences among the clusters based on visitors’ demographics in the activities that they join in Kuala Terengganu. In the meantime, Kruskal-Wallis Test and Mann-Whitney Test also show significant differences between six pairs of clusters regarding activities in the visitors’ demographics. The results can be used to assist state planners and tourism entrepreneurs determine suitable marketing mix strategies that enhance the Kuala Terengganu attractions and ensure their sustainability for receiving new and repeat tourists. The understanding of benefit segmentation will be able to help the state or marketers in identifying the character of an undecided group of domestic tourists who are not into the main tourism products.

Toward an understanding of segmentation strategies in international tourism marketing: the moderating effects of advertising media typesand nationality

Purpose The purpose of this paper is to contribute to international tourism market segmentation research by proposing a comprehensive framework that examines behavioral, benefits and lifestyle segmentations. The moderating roles of geographic segmentation (nationality) and advertising media types are also discussed. Design/methodology/approach Tourists volunteered to participate in a self-administered survey at random during peak seasons. Total number of collected questionnaires was 966. The authors used WarpPLS 6.0 software to analyze data. Findings Results from a sample of 919 tourists show that tourists in the benefit segmentation cluster had intentions to revisit the destination but they were unlikely to recommend it to others. Another finding indicates that marketing campaigns on different advertising media types might have different results when targeting different activities. Originality/value Leaning on the foundations of the marketing literature and the market segmentation theory, this research attempts to create a theoretical contribution that can be used to segment international tourists based on their travel motivations. Additionally, this study highlights the power of conditional probability approach, as it could be of more value than the predominant path coefficient approach.

Benefit segmentation in the tourist accommodation market based on eWOM attribute ratings

Given the increasing importance of electronic word-of-mouth (eWOM) in the global tourism market, the purpose of the study was to estimate weights customers assign to main attributes of tourist accommodations embodied in easily observed eWOM numerical ratings and subsequently to determine segments of customers with homogenous preferences. To this goal, the preferences tourists attach to price and seven other accommodation attributes rated by Internet users on Booking.com were revealed with the analytical hierarchy process (AHP). Next, a two-stage clustering procedure based on these preferences was undertaken followed by profiling of the clusters in terms of their socio-demographics and travel characteristics. The results show that even if the ranking of the attributes is roughly the same for all the segments (with cleanliness, value for money, and location always in top four), all eight attributes effectively segment tourists into three clusters: “quality-seekers” (45% of the market), “bargain-seekers” (35%), and “cleanliness-seekers” (20%). The segments differ in terms of tourists’ income and expenditures, type of accommodation, actual payer for accommodation, and trip purpose. In contrast, socio-demographics, and most tourists stay variables are alike across the segments. The proposed method of benefit segmentation provides a new perspective for an exploitation of eWOM data by accommodation providers in their marketing strategy.

To Speak to Me, Address Us: Insights From LGBT Young Adults to Inform Public Education Campaigns

Draft advertising concepts were tested in a series of focus groups among 140 lesbian, gay, bisexual, and transgender (LGBT) young adults aged 18 to 24 in seven U.S. cities in 2015. In this secondary analysis of focus group transcripts, young adult responses to tested concepts belie deeper lessons that have broader application for public education campaigns among LGBT young adult audiences. Respondents valued seeing both individuals who were like them and also unlike them, preferring a diverse portrayal of the fuller spectrum of LGBT communities, a finding which has implications for campaign segmentation of LGBT audiences. More broadly tailored communications for LGBT audiences can be appropriate as long as portrayals are diverse. These young adults expressed the desire to see nuanced, humanizing content that avoids playing into existing stereotypes. These findings also show how qualitative research can benefit segmentation and how research and communications can address the needs of subgroups within diverse segments.

A benefit segmentation framework for a nature-based tourism destination: the case of Kruger, Panorama and Lowveld areas in Mpumalanga Province

Purpose The purpose of this study is to investigate benefits tourist seek when visiting a nature-based tourism destination to develop a benefit segmentation framework. Design/methodology/approach The study used quantitative research methods, with 400 self-administered survey administered to a sample of 400 tourists visiting the Kruger, Panorama, and Lowveld areas in Mpumalanga. Findings Cluster analysis produced two benefit segments. Binary logistic regression benefits that emerged from the cluster analysis were statistically significant predictors of the attractions tourists visited and the activities in which they participated during their stays in Mpumalanga. Factor-cluster analysis and binary logistic regression results were used to develop a benefit segmentation framework as a marketing planning tool. Research limitations/implications The study was only based on Mpumalanga Province and therefore, the results cannot be generalised. The study was conducted over one season, the Easter period Practical implications The proposed benefit segmentation framework provides a tool that destination management organisations can use to plan effectively for marketing. Social implications Effective marketing may lead to increased tourism growth which can have a multiplier effect on the destination. Originality/value This article is based on a master’s study conducted in Mpumalanga and results are presented on this paper.

Benefit segmentation of a summer destination in Uruguay: a clustering and classification approach

Purpose This study aims to perform a benefit segmentation and then a classification of visitors that travel to the Rocha Department in Uruguay from the capital city of Montevideo during the summer months. Design/methodology/approach A convenience sample was obtained with an online survey. A total of 290 cases were usable for subsequent data analysis. The following statistical techniques were used: hierarchical cluster analysis, K-means cluster analysis, machine learning, support vector machines, random forest and logistic regression. Findings Visitors that travel to the Rocha Department from Montevideo can be classified into four distinct clusters. Clusters are labelled as “entertainment seekers”, “Rocha followers”, “relax and activities seekers” and “active tourists”. The support vector machine model achieved the best classification results. Research limitations/implications Implications for destination marketers who cater to young visitors are discussed. Destination marketers should determine an optimal level of resource allocation and destination management activities that compare both present costs and discounted potential future income of the different target markets. Surveying non-residents was not possible. Future work should sample tourists from abroad. Originality/value The combination of market segmentation of Rocha Department’s visitors from the city of Montevideo and classification of sampled individuals training various machine learning classifiers would allow Rocha’s destination marketers determine the belonging of an unsampled individual into one of the already obtained four clusters, enhancing marketing promotion for targeted offers.

The U.S. Toothpaste Market: A Competitive Profile

This paper follows the path of seven studies (see below). However, it is different in one important respect: it also offers a benefit segmentation profile of the U.S. Toothpaste Market.Porter associates high market share with cost leadership strategy which is based on the idea of competing on a price that is lower than that of the competition. However, customer-perceived quality—not low cost—should be the foundation of competitive strategy, because it is far more vital to long-term competitive position and profitability than any other factor. So, a superior alternative is to offer better quality vs. the competition.In most consumer markets a business seeking market share leadership should try to serve the middle class by competing in the mid-price segment; and offering quality better than that of the competition: at a price somewhat higher, to signify an image of quality, and to ensure that the strategy is both profitable and sustainable in the long run. Quality, however, is a complex concept that consumers generally find difficult to understand. So, they often use relative price, and a brand’s reputation as a symbol of quality.In 2008 retail sales in the U.S. were $1.27 Billion for the Toothpaste Market. The market leader Crest had a market share of 34.7%, closely followed by Colgate with a share of 33.5%. We focused on the most popular pack-size—5.8-6.5oz—which had a 45.3% share. Employing Hierarchical Cluster Analysis, we tested two hypotheses: (1) That a market leader is likely to compete in the mid-price segment, and (2) That the unit price of the market leader is likely to be somewhat higher than that of the nearest competition. Employing U.S. retail sales data for 2008 and 2007, we found that, for both 2008 and 2007, the market leader in the U.S. Toothpaste market—Crest—was a member of the mid-price segment. Furthermore, the unit price of Crest was somewhat higher than that of Colgate, the runner-up, which was also a member of the mid-price segment.Thus, the results fully supported both Hypothesis I and II—for 2008 and 2007.We also found strong support for the idea, that relative price is a strategic variable, as we have hypothesized.We discovered five benefit segments. The most fundamental result of this analysis is that it revealed an avalanche of various brands of toothpaste that not only whitened teeth, but were also helpful in preventing tooth decay, as before.Finally, we discovered four strategic groups in the industry.