The relationship between loyalty program and customer loyalty in retail industry: A case study

Zakaria, Ibhrahim; Rahman, Baharom Abdul; Othman, Abdul Kadir

doi:10.1109/icimtr.2012.6236356

Cited by 7 publications

(1 citation statement)

References 12 publications

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“…Within retail industries, footfall sensors are used to provide intelligence for staff scheduling that ensure customer demands are met without overheads being excessive (Ipsos, 2013). Together with an overall trend in Point-of-Sale (POS) transactions, loyalty cards used by major retailers are being utilised to track customer purchases leading to a greater understanding of shopping habits and enabling businesses to track the success of marketing initiatives (Zakaria, et al, 2012). Despite uncovering a wealth of data about shopper demographics and their purchase history, insight into the customers in store behaviour is often missing.…”

Section: Introductionmentioning

confidence: 99%

Sensing Gestures for Business Intelligence

Bell¹,

Makwana²,

Mgbemena³

2014

Proceedings of the 3rd International Conference on Sensor Networks

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Abstract:The combination of sensor data with analytic techniques is growing in popularity for both practitioners and researchers as an Internet of Things (IoT) offers new opportunities and insights. Organisations are trying to use sensor technologies to derive intelligence and gain a competitive edge in their industries. Obtaining data from sensors might not pose too much of a problem, however subsequent utilisation in meeting an organisation's decision making can be more problematic. Understanding how sensor data analytics can be undertaken is the first step to deriving business intelligence from front line retail environments. This paper explores the use of the Microsoft Kinect sensor to provide intelligence by identifying and sensing gestures to better understand customer behaviour in the retail space.

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Section: Introductionmentioning

confidence: 99%

Sensing Gestures for Business Intelligence

Bell¹,

Makwana²,

Mgbemena³

2014

Proceedings of the 3rd International Conference on Sensor Networks

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New Market Opportunities By Merging Loyalty and Payment

Goeller¹,

Yeap

2015

Xpert.press

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Decision Tree: Customer Churn Analysis for a Loyalty Program Using Data Mining Algorithm

Lee

Claudia

Zainol

et al. 2019

Communications in Computer and Information Science

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In the world of retailer, customers typically patronize multiple shops thus making loyalty programs a favorite among retailer to retain their customers. Loyalty programs are utilized across many different businesses as a marketing strategy to encourage customers to continuously shop or patronize the services provided by a certain organization. However, one of the biggest problem faced by these businesses is customer churn. The purpose of this research was to build a predictive model, which could predict customer churn, where visualization of data was generated to better understand the existing members and see the patterns and behavior demonstrated by members of the loyalty program. Through these, meaningful insights about the businesses' analysis on customers could be gathered and utilized for better actions which could be taken to address the issues which the company faces. At the end, based on the issues found, strategies were proposed to address the issues found. For this research, SAS Enterprise Miner was used to perform predictive analysis while Tableau was used to perform descriptive analysis.

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The relationship between loyalty program and customer loyalty in retail industry: A case study

Cited by 7 publications

References 12 publications

Sensing Gestures for Business Intelligence

Sensing Gestures for Business Intelligence

New Market Opportunities By Merging Loyalty and Payment

Decision Tree: Customer Churn Analysis for a Loyalty Program Using Data Mining Algorithm

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