Market Segmentation Analysis and Visualization using K-Mode Clustering Algorithm for E-Commerce Business

Kamthania, Deepali; Pawa, Ashish; Madhavan, Srijit S.

doi:10.20532/cit.2018.1003863

Cited by 45 publications

(22 citation statements)

References 19 publications

(29 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The highest number of publications was in 2012 (14 bibliographic units); in the years to 2018, the number of published bibliographic units covered by Scopus ranges around 10 per year. The latest publications in 2018 show, how the integrated approach of GIS and BI may be beneficial for different aspects of quality of life of different social groups (Szewrański et al 2018a), for detecting and predicting the flood risks for improving the water management infrastructure modelling (Szewrański et al 2018b), for market segmentation and visualization, based on user behavior geographical distributions (Kamthania et al 2018) etc.…”

Section: Research Publishing On Business Intelligence (Bi) and Geogramentioning

confidence: 99%

Business Informatics Principles

2019

View full text Add to dashboard Cite

Business informatics consists of two major areas which are developing separately but are closely related and also to some extent integrated within information systems architecture in organisations. The first area is business solutions as core information systems for support of business operationsthey consist of Enterprise resources planning solutions (ERP), Customer relationship management solutions (CRM) and other specialised solutions. The second area is Business Intelligence (BI). After describing the basic concepts of these information solutions/business information systems and their functionality, the chapter explains the emerging integration of business informatics and geo-informatics. Developments provided by solution providers are analysed and discussed. The chapter concludes with a bibliometric analysis of research which shows areas and dynamics of business informatics and GIS integration.

show abstract

Section: Research Publishing On Business Intelligence (Bi) and Geogramentioning

confidence: 99%

Business Informatics Principles

2019

View full text Add to dashboard Cite

show abstract

“…Ou, 2021) the application of analysis and visuals is also very useful in e-commerce business. for market segmentation based on geographic distribution of user behavior (D. Kamthania, 2018).…”

Section: Introductionmentioning

confidence: 99%

Clustering Algorithm For Determining Marketing Targets Based Customer Purchase Patterns And Behaviors

Husein

waruwu

Bara

et al. 2021

SinkrOn

View full text Add to dashboard Cite

Customer segmentation is one of the most important applications in the business world, specifically for marketing analysis, but since the Corona Virus (Covid-19) spread in Indonesia it has had a significant impact on the level of digital shopping activities because people prefer to buy their needs online, so It is very important to predict customer behavior in marketing strategy. In this study, the K-Means Clustering technique is proposed on the RFM (Recency, Frequency, Monetary) model for segmenting potential customers. The proposed model starts from the data cleaning stage, exploratory analysis to understand the data and finally applies K-Means Clustering to the RFM Model which produces three clusters based on the Elbow model. In cluster 0 there are 2,436 customers, in cluster1 1,880 and finally in cluster2 there are 18 customers. RFM analysis can segment customers into homogeneous groups quickly with a minimum set of variables. Good analysis can increase the effectiveness and efficiency of marketing plans, thereby increasing profitability with minimum costs.

show abstract

“…A good farsightedness from the perspective of future status and circumstances has the ability of assisting a business in taking effective and corrective measures in advance [19]. AI (Artificial Intelligence) and Machine Learning are being adopted in almost all business organisations to achieve growth and profitability [11]. Likewise, these technologies have become an inevitable wing in the movie industry.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, the author presents a 2 layered back-propagation neural network model with 23 numeric inputs (BPNN-N23) developed for prediction of the success status among 3 success classes. Data on the movies released during the years 2014 through 2017 had been collected from relevant websites [10][11][12][13][14]. The present paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

Classification and Forecasting of Bollywood Movies by Commercial Success using Back-Propagation Neural Network model

Nayak*

2019

IJITEE

View full text Add to dashboard Cite

Forecasting commercial success of motion pictures remained challenging for producers, critics and other industry leaders in this changing world of web and online media. In this study, the author has explored a back-propagation neural network model with 23 numeric input (BPNN-N23) for classification of Bollywood movies released during the years 2014 through 2017. The proposed model classifies movies in three classes namely “HIT”, “AVERAGE” and “FLOP”. Common procedures like data filtering, data cleaning and data normalization have been followed prior to feeding those data to the neural network. After comparing the performance of the proposed model with the benchmark models and works, the results show that the said model shows performance that is comparable to the published ones with respect to the assumed Indian empirical settings. This research reveals the extent of the effects and roles of the considered factors as well as the proposed model in predicting the fate of a Bollywood movie in India.

show abstract

Market Segmentation Analysis and Visualization using K-Mode Clustering Algorithm for E-Commerce Business

Cited by 45 publications

References 19 publications

Business Informatics Principles

Business Informatics Principles

Clustering Algorithm For Determining Marketing Targets Based Customer Purchase Patterns And Behaviors

Classification and Forecasting of Bollywood Movies by Commercial Success using Back-Propagation Neural Network model

Contact Info

Product

Resources

About