Segmentation of Retail Mobile Market Using HMS Algorithm

In the modern world of marketing, analyzing the trends in market is a key point towards to scope of improvement of any company. Considering the analysis of a retail market where market trends change very frequently based on customer needs and interest is highly challenging. Market segmentation is one of the approaches included in analysis of market trends which gives a diverse view of the market.  The research here concentrates, especially on a case study based on fast moving consumable goods market and identifying market change patterns by applying a novel data mining approach. Data mining includes a wide variety of techniques and algorithm which can be effectively used in the process of market analysis. The research work carried out coins a new algorithm which combines various association rules and techniques, the HMS (Hybrid market segmentation) algorithm with some specialized criteria is used to support the market segmentation. The primary data needed for the analysis and operation are collected through a questionnaire based survey conducted on people from various demographic regions as well as various age groups. Used a quota based sampling approach for the research, The data mining approach here helps to study the large dataset collected and also to extract the useful information required to model the system. The system here is a learning system which improves the market segmentation functionality as data set improves, The paper implements a hybrid data mining approach which effectively segments the retail mobile market in to various customer and product groups and also provides a prediction and suggestion system for company as well as customer.

Customer Visit Segmentation Using Market Basket Data

Basket analytics is a powerful tool in the retail context for acquiring knowledge about consumer shopping habits and preferences. In this paper, we propose a clustering-based artifact that mines customer visit segments from basket sales data. We characterize a customer visit by the purchased product categories in the basket and identify the shopping intention or mission behind the visit e.g. ‘breakfast’ visit to purchase cereal, milk, bread, cheese etc. We demonstrate the utility of the artifact by applying it to a real case of a major fast-moving consumer goods (FMCG) retailer. Apart from its theoretical contribution, the proposed approach extracts knowledge that may support several decisions ranging from marketing campaigns per customer segment, redesign of a store’s layout to product recommendations

A hybrid model for migrating customer segmentation with missing attributes

Due to missing attributes in an enterprise's database, migrating customer segmentation results from external dataset to enterprise database in difficult. In this paper, a hybrid model, called HMCS model, is presented. This model artificially generates values of missing attributes based on external dataset and populates them to enterprise database. Based on this model, an application in a telecom application is reported. Application indicates the presented model can produce acceptable segmentation results on the enterprise dataset which is with missing attributes. © 2013 IEEE

Finding new opportunities in the Lisbon market through Whitaker consumer lifestyle segmentation

A sample of 445 consumers resident in distinct Lisbon areas was analyzed through direct observations in order to discover each lifestyle’s current proportion, applying the Whitaker Lifestyle™ Method. The findings of the conducted hypothesis tests on the population proportion unveil that Neo-Traditional and Modern Whitaker lifestyles have the significantly highest proportion, while the overall presence of different lifestyles varies across neighborhoods. The research further demonstrates the validity of Whitaker observation techniques, media consumption differences among lifestyles and the importance of style and aesthetics while segmenting consumers by lifestyles. Finally, market opportunities are provided for firms operating in Lisbon

STRATEGI PENJUALAN PEDAGANG PASAR MODERN BERBASIS CUSTOME DATA MINING

Abstract. Business competition between merchant in the modern market which is is getting tighter needs effective marketing strategies. An effective sales strategy can be arranged based on the knowledge of consumers. The increasingly competitive business environment that causes businesses must continue to provide the best service to customers for the development and success of trading businesses in the present and who will date. This problem can be addressed properly if you have accurate information about customers. Accurate information about these consumers can be obtained through customer data collection methods that is called customer data mining. Customer data mining is a method of finding consumer data which includes various kinds of aspects ranging from characteristics to the way consumers purchase. Using the instrument questionnaire, this research is a consumer survey. This paper is a brief report on the results of consumer data excavation, analysis of the results of statistical data based on the results of consumer data processing, and formulation of recommendations regarding promotion and sales strategies for merchant in the modern marketAbstrak. Persaingan bisnis antar pedagang yang semakin ketat menuntut pedagang manciptakan strategi penjualan yang efektif. Strategi penjualan yang efektif dapat disusun berdasarkan pengetahuan tetang perilaku konsumen. Lingkungan bisnis yang semakin kompetitif menyebabkan pelaku usaha harus terus berupaya memberikan pelayanan terbaik kepada konsumen demi perkembangan dan kelangsungan usaha dagang di masa sekarang dan yang akan dating. Masalah ini dapat diatasi dengan baik jika pedagang mempunyai informasi akurat mengenai perilaku konsumen. Informasi akurat mengenai perilaku konsumen tersebut dapat diperoleh melalui metode pengalian data konsumen (customer data mining). Customer data mining merupakan metode mencari data konsumen yang mencakup berbagai macam aspek mulai dari karakteristik sampai dengan perilaku pembelian yang dilakukan konsumen. Menggunakan instrumen kuesioner, penelitian ini merupakan seuatu survei konsumen. Tulisan ini merupakan merupakan laporan singkat mengenai hasil penggalian data konsumen, analisis hasil data statistik berdasarkan hasil pengolahan data konsumen, dan rumusan rekomendasi mengenai strategi promosi dan penjualan bagi pedagang pasar modern.

Lifetime-value creation through a customized offer adressed to diferent lifestyles

This paper purposes a method for marketing segmentation based on customers‟ lifestyle. A quantitative and qualitative segmentation established by the Whitaker Lifestyle™ Method was created in order to define a concrete and clear identification of the customer, by understanding the behavior, style and preferences of each segment. After conducting 18 in-depth interviews, it was concluded that four main personas characterize the customer base of the company. These four personas will be the support for the creation of „quick-wins‟ that address to the expectations of each lifestyle, projecting a significant impact on the lifetime-value of the company‟s customer bas

Aplicação de marketing analítico na farmácia Gaia Jardim

O projecto apresentado surgiu no âmbito de uma proposta de investigação da Católica Porto Business School. Cada vez mais, os sistemas de informação fazem parte do desenvolvimento das empresas e a Farmácia Gaia Jardim procurou evoluir nesse sentido e utilizar a sua base de dados para desenvolver a sua relação com os clientes. Assim, neste trabalho pretendeu-se estabelecer estratégias de cross-selling através do uso de ferramentas de marketing analítico, nomeadamente data mining. De um modo geral, esta análise aos dados da farmácia permitiu um maior conhecimento sobre os seus clientes. Mais concretamente, este trabalho permitiu a identificação dos segmentos de clientes com base na frequência de visitas à fármacia e o valor médio gasto e a criação de regras de associação entre produtos para estabelecer as estratégias de cross-selling mais adequadas para cada segemento de clientes da farmácia.The presented project is developed in the scope of a research proposal from Católica Porto Business School. Information systems are becoming of increased importance to the development of companies. Gaia Jardim Pharmacy is taking this fact into consideration and using its data base to develop their relationship with their customers. Therefore, in this paper we aimed at creating cross-selling strategies through of the use of analytic marketing tools, as data mining. In general, this analysis enabled to obtain a more detailed knowledge about the customers of the pharmacy. uMore specifically, this study enabled the identification of segments of customers and finally on the identification of association rules between the products which allows the pharmacy to definethe most adequate cross-selling strategies for the segments of customers identified