Customer segmentation in a large database of an online customized fashion business

Brito, Pedro Quelhas; Soares, Carlos; Almeida, Sheylla Susan Moreira da Silva de; Monte, Ana; Byvoet, Michel

doi:10.1016/j.rcim.2014.12.014

Cited by 84 publications

(41 citation statements)

References 37 publications

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“…A range of other previously described techniques have been adapted for modern datasets. Brito et al (2015) segment a fashion database of 7000 consumers using k-medoids clustering (a variant of k-means with an L 1 city-block distance) and subset mining, which is designed to find interesting relations for items/customers who have an specific distribution of a target variable. In this case, it was used to elicit fashion preferences for overweight consumers.…”

Section: Modern Large Scale Segmentation Approachesmentioning

confidence: 99%

Marketing analytics: Methods, practice, implementation, and links to other fields

Ghose

2019

Expert Systems with Applications

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Marketing analytics is a diverse field, with both academic researchers and practitioners coming from a range of backgrounds including marketing, expert systems, statistics, and operations research. This paper provides an integrative review at the boundary of these areas. The aim is to give researchers in the intelligent and expert systems community the opportunity to gain a broad view of the marketing analytics area and provide a starting point for future interdisciplinary collaboration. The topics of visualization, segmentation, and class prediction are featured. Links between the disciplines are emphasized. For each of these topics, a historical overview is given, starting with initial work in the 1960s and carrying through to the present day. Recent innovations for modern, large, and complex "big data" sets are described. Practical implementation advice is given, along with a directory of open source R routines for implementing marketing analytics techniques.

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Section: Modern Large Scale Segmentation Approachesmentioning

confidence: 99%

Marketing analytics: Methods, practice, implementation, and links to other fields

Ghose

2019

Expert Systems with Applications

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“…These approaches were expected to be particularly important for highly customized industries because the diversity of products sold makes it harder to find clear patterns of customer preferences. The models obtained produced six market segments and 49 rules that allowed a better understanding of customer preferences in a highly customized fashion manufacturer/e-tailor [11].…”

Section: Literature Reivewmentioning

confidence: 99%

“…Because fashion is a very dynamic business, new collections should be issued at least twice a year. The variety of products offered, together with the speed of response to changes in demand, can be crucial for the success of this business [11].…”

Section: Introductionmentioning

confidence: 99%

Dijital Tüketicilerin Giysi Satın Alma Davranışlarının İncelenmesi

Taydaş¹,

Çoruh²

2017

Tekstil ve Mühendis

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The aim of the research was to investigate of clothing purchase behaviours of digital consumers. The survey method was employed in the research. A questionnaire was developed to gather the data. The questionnaire was designed in two parts. In the first part of the questionnaire it consisted of defining the personal details. In the second part, the advantages and disadvantages of purchasing clothes via the Internet were itemised with five-point Likert scale. The sample group was selected with "random sample method" as 512 digital consumers. In the research, the clothing purchase behaviours of the digital consumers were compared in terms of the advantages and disadvantages with the personal details. As a result, women thought the clothes purchasing from the Internet favourable and men thought that it was unfavourable. It was also seen that the users of the Internet for shopping older than 4-5 years and the users of the daily 4-5 hours shopping websites found the Internet favourable for the clothing purchase. For other comparisons, there wasn't any meaningful relationship.

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“…Xiao and Dong (2015) further conducted a case study based on a real O2O e-commerce platform to demonstrate the application of HSMM-RMS. Data mining (DM) techniques have been used to solve marketing and manufacturing problems in the fashion industry (Brito et al 2015) and can be extended for exploring O2O business models when the transactions and consumer data can be collected and utilized. These approaches are expected to be particularly important for highly customized industries because the high diversity of products sold makes it difficult to find clear patterns of customer preferences.…”

Section: O2o-based Fashion Logistics Systemsmentioning

confidence: 99%

“…These approaches are expected to be particularly important for highly customized industries because the high diversity of products sold makes it difficult to find clear patterns of customer preferences. Brito et al (2015) investigated two different data mining approaches for customer segmentation: clustering and subgroup discovery. Their models produced six market segments and 49 rules that allowed a better understanding of customer preferences in a highly customized fashion manufacturer/e-tailor.…”

Section: O2o-based Fashion Logistics Systemsmentioning

confidence: 99%

Distribution, Transshipment, and Sustainable Logistics for Fashion Products

2016

Springer Series in Fashion Business

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This paper reports and studies three fashion logistics optimization-related problems, including fashion distribution, transshipment, and sustainable logistics management. Fashion products are popular in the context of e-commerce and business innovation. The responsiveness of product searching, purchasing, experiencing, and returning or disposal is critically important. In this paper, considering the consumer experience during the distribution service, the try-on service is introduced and examined, where the effects of try-on services on return ratios, loyalty, and logistics cost are analyzed based on experiments. Then, to share fashion products among retailers of a brand, transshipment is critical and this paper presents an analytical model for investigating transshipment. By transshipment, fashion products can be efficiently transported from, e.g., the selling-well "good business" retailers to the "poor business" retailers. Next, considering the short life cycles of fashion products, a sustainable supply chain model is devised by using rental services in the loop. The operations problems and systematic mechanisms are then explored based on the model. Finally, the challenges and opportunities of using advanced technologies (e.g., Internet of Things and big data) are discussed. The proposed models in this paper provide important references for fashion industrialists as well as academics on fashion logistics and supply chain management.

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Customer segmentation in a large database of an online customized fashion business

Cited by 84 publications

References 37 publications

Marketing analytics: Methods, practice, implementation, and links to other fields

Marketing analytics: Methods, practice, implementation, and links to other fields

Dijital Tüketicilerin Giysi Satın Alma Davranışlarının İncelenmesi

Distribution, Transshipment, and Sustainable Logistics for Fashion Products

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