Retail analytics: store segmentation using Rule-Based Purchasing behavior analysis
29 Apr 2021-The International Review of Retail, Distribution and Consumer Research (Routledge)-Vol. 31, Iss: 4, pp 457-480
TL;DR: In this article, the authors present challenges in making sense of the significant amount of data available for a better understanding of their customers, while retail analytics plays an increasingly important rol...
Abstract: Retailers are facing challenges in making sense of the significant amount of data available for a better understanding of their customers. While retail analytics plays an increasingly important rol...
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05 May 2009
TL;DR: The retail landscape of the 1990s is not for the fainthearted as discussed by the authors, due to demographic changes, economic developments, increased competition, accelerated consolidation, increased polarization of the players, and the importance of technology.
Abstract: The retailing landscape of the 1990s is not for the fainthearted. A few firms will prosper, but many will disappear. The reasons for this fact include demographic changes, economic developments, increased competition, accelerated consolidation, increased polarization of the players, and the importance of technology.This presentation comes from The Retail Industry—General Merchandisers and Discounters, Specialty Merchandisers, Apparel Specialty, and Food/Drug Retailers conference held in Chicago, Illinois, on March 3-4, 1992.
123 citations
TL;DR: In this article, the authors proposed a latent space approach that parsimoniously captures the dynamics of multi-category shopping behavior due to the interplay between purchase timing and shopping basket composition, and account for interdependence among multiple categories, temporal dependence across category choices, and latent customer attrition.
Abstract: Customer base analysis is an essential tool to measure and develop relationships with customers. While various models have been proposed in a noncontractual setting, they focus primarily on analyzing transactional patterns associated with a single product category or a firm-level activity, such as the times at which purchases are made at a particular retailer. This research proposes a modeling framework for customer base analysis in a multi-category context. Specifically, we model the time between a customer's purchases at the firm and the product categories that comprise her shopping basket arising from multi-category choice decisions. The proposed model uses a latent space approach that parsimoniously captures the dynamics of multi-category shopping behavior due to the interplay between purchase timing and shopping basket composition. We also account for interdependence among multiple categories, temporal dependence across category choices, and latent customer attrition. Using category-level transaction data, we show that the proposed model offers excellent fit and performance in predicting customer purchase patterns across multiple categories. The forecasts and inferences afforded by our model can assist managers in tailoring marketing efforts across categories.
14 citations
13 Apr 2023
TL;DR: In this article , the authors developed a quantitative assessment of service quality for grocery stores operators to translate the customer's expectations and perceptions into measurement framework specifications, taking the emerging market context as their reference.
Abstract: Abstract The purpose of this study is to develop a quantitative assessment of service quality for grocery stores operators to translate the customer’s expectations and perceptions into measurement framework specifications- taking the emerging market context as our reference. The service quality is computed using human assessment. The newly developed framework with interval-valued Pythagorean fuzzy to access the service quality have an added advantage of handling vague human assessments, which is lacked by conventional service quality assessment techniques. Therefore, this study proposed a two-phase service quality analysis using an extended interval-valued Pythagorean fuzzy approach. Firstly, the number of service quality dimensions are identified with a systematic literature review, and secondly, the rank of factors and proposed measurement framework by the interval-valued Pythagorean fuzzy approach. Although, this study results confirmed that tangibility and reliability are the major service quality dimensions from the customer’s expectations. The originality of the present study aids grocery store operators to take group decision-making on high-priority areas so that resources can be properly deployed to meet people's mobility needs.
References
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TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Abstract: Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team.
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TL;DR: The cophenetic correlations which will be developed below provide an extremely simple and effective method for comparing dendrograms of various sorts.
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01 Jun 2014
TL;DR: A data mining approach to predict the success of telemarketing calls for selling bank long-term deposits in Portuguese retail bank was addressed, with data collected from 2008 to 2013, thus including the effects of the recent financial crisis.
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673 citations
TL;DR: In this paper, the authors focus on the future of retail by highlighting five key areas that are moving the field forward: (1) technology and tools to facilitate decision making, (2) visual display and merchandise offer decisions, (3) consumption and engagement, big data collection and usage, and (4) analytics and profitability.
632 citations
01 Apr 2013
TL;DR: A conceptual framework for DSS in cloud is proposed, a unique contribution of this paper is its perspective on how to servitize the product oriented DSS environment, and the opportunities and challenges of engineering service oriented D SS in cloud are demonstrated.
Abstract: Using service-oriented decision support systems (DSS in cloud) is one of the major trends for many organizations in hopes of becoming more agile. In this paper, after defining a list of requirements for service-oriented DSS, we propose a conceptual framework for DSS in cloud, and discus about research directions. A unique contribution of this paper is its perspective on how to servitize the product oriented DSS environment, and demonstrate the opportunities and challenges of engineering service oriented DSS in cloud. When we define data, information and analytics as services, we see that traditional measurement mechanisms, which are mainly time and cost driven, do not work well. Organizations need to consider value of service level and quality in addition to the cost and duration of delivered services. DSS in CLOUD enables scale, scope and speed economies. This article contributes new knowledge in service science by tying the information technology strategy perspectives to the database and design science perspectives for a broader audience.
521 citations
"Retail analytics: store segmentatio..." refers background in this paper
...In the era of big data, companies have huge amount of data (big data) to be used for improving business operations and management including decision-making processes which contribute to business success (Demirkan and Delen 2013)....
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