International Market Segmentation across Consumption and Communication Categories: Identity, Demographics, and Consumer Decisions and Online Habits

Villiers, Rouxelle de; Tipgomut, Pornchanoke; Franklin, A

doi:10.5772/intechopen.89988

Cited by 6 publications

(4 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Oeconomia 20 �2�, 13-20, doi: 10.22630�ASPE.2021.20.2.11 doi: 10.22630�ASPE.2021 This cluster analysis confirms the importance of demographic variables and behavioural characteristics as important tools in the touristic market segmentation for visitors to Gjirokastra. These variables are considered to be important as noted by previous researchers examining market segmentation [Dolnicar 2002, Perdue 2004, Kazeminia et al 2013, Camilleri 2017, De Villiers et al 2019.…”

Section: Resultsmentioning

confidence: 99%

“…Marketers further differentiate between buyers and divide them into smaller segments that are fairly homogeneous in terms of need, resources, location, buying attitudes, or buying practices. The main purpose of segmentation activities is to ensure that potential and current customers can be reached more effectively and that communication, product, and service offerings can be matched to the unique needs of different consumers [De Villiers et al 2019].…”

Section: Main Debatesmentioning

confidence: 99%

See 1 more Smart Citation

Exploring Tourist Expenditures of the Gjirokastra District in Albania: A Cluster Analysis

Boboli

Muça

2022

aspe

View full text Add to dashboard Cite

Tourism expenditures are an important indicator for measuring the impact of tourism on a destination. Information taken from the micro data of tourism expenditures, together with other socio-demographic characteristics of visitors, provides important data on the tourist demand for a destination. Visitor costs in combination with other variables can be used to profile the demand for tourist goods and services in the destination area. In this paper, the daily expenses of visitors in the Gjirokastra district of Albania are analysed. The Gjirokastra district is one of the more preferred regions and attracts a considerable number of domestic and foreign visitors, because it offers a diversity tourist attractions and services. For the purposes of this study, a survey of 200 visitors was conducted. The survey results were analysed with descriptive statistics via a cluster analysis. The survey provides detailed data on the daily expenses of visitors, divided into six main categories of a typical travel budget. Through the use of data mining cluster analysis, we identified and analysed the tourists’ daily expenses based on the purpose of their visit to the area of Gjirokaster.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Main Debatesmentioning

confidence: 99%

Exploring Tourist Expenditures of the Gjirokastra District in Albania: A Cluster Analysis

Boboli

Muça

2022

aspe

View full text Add to dashboard Cite

show abstract

“…Integrated marketing communications may also become more valuable with localized automated applications (IMC). When past are examined, it is concluded that the probability of IMC being successful is higher when it contains cultural, communication activities, language, and socio-demographic differences (De Villiers et al, 2020).…”

Section: The Role Of Automated Analysis At the Enterprise Level: Gloc...mentioning

confidence: 99%

Untitled

2023

SJBMM

View full text Add to dashboard Cite

This study aims to investigate the role of human-machine interaction and automatic analysis concepts, which are a product of digitalization, on glocalization. In recent years, great attention has been paid to artificial intelligence applications in the field of marketing, as in every field of companies. With the application of artificial intelligence in the field of marketing, marketing strategies have also changed. The concept of glocalization, which is one of the current marketing strategies, is formed from the combination of the words global and local. Glocalization means the implementation of marketing strategies compatible with the cultural characteristics of the target market while presenting global products to local markets. It has created a new marketing behavior through digital products such as glocalization, human-machine interaction, and automatic analysis.

show abstract

“…The model has divided customers into groups groupings characterized by three index values: relevance (once customers can directly make most latest acquisition), recurrence (how often the consumer makes transactions), and financial value (how much the purchaser gets to spend on each purchase), and then gives e-commerce businesses the operational measures they need to keep potential customers and enhance profitability. Way of categorizing, but on the other side, has a significant wait than some other types of client information, especially data on browsing habits [5], [6]. Furthermore, various clients' repurchase cycles are different.…”

Section: Introductionmentioning

confidence: 99%

Classification of customer churn prediction model for telecommunication industry using analysis of variance

Babatunde

Abdulsalam

et al. 2023

IJ-AI

View full text Add to dashboard Cite

Customer predictive analytics has shown great potential for effective churn models. Thriving in today's telecommunications industry, discerning between consumers who are likely to migrate to a competitor is enormous. Having reliable predictive client behavior in the future is required. Machine learning algorithms are essential to predict customer turnovers, and researchers have proposed various techniques. Churn prediction is a problem due to the unequal dispersal of classes. Most traditional machine learning algorithms are ineffective in classifying data. Client cluster with a higher risk has been discovered. A support vector machine is employed as the foundational learner, and a churn prediction model is constructed based on each analysis of variance. The separation of churn data revealed by experimental assessment is recommended for churn prediction analysis. Customer attrition is high, but an instantaneous support can ensure that customer needs are addressed and assess an employee's capacity to achieve customer satisfaction. This study uses an analysis of variance (ANOVA) with a support vector machine (SVM), classification in analyzing risks in telecom systems It may be determined that SVM provides the most accurate forecast of customer turnover (95%). The projected outcomes will allow other organizations to assess possible client turnover and collect customer feedback.

show abstract

International Market Segmentation across Consumption and Communication Categories: Identity, Demographics, and Consumer Decisions and Online Habits

Cited by 6 publications

References 25 publications

Exploring Tourist Expenditures of the Gjirokastra District in Albania: A Cluster Analysis

Exploring Tourist Expenditures of the Gjirokastra District in Albania: A Cluster Analysis

Untitled

Classification of customer churn prediction model for telecommunication industry using analysis of variance

Contact Info

Product

Resources

About