Nowadays, the growing global economy and demand for customized products are bringing the manufacturing industry from a sellers’ market towards a buyers’ market. In this context, the smart manufacturing enabled by Industry 4.0 is changing the whole production cycle of companies specialised on different kinds of products. On one hand, the advent of Cloud computing and social media makes the customers’ experience more and more inclusive, whereas on the other hand Cyber-Physical System (CPS) technologies help industries to change in real time the cycle of production according to customers’ needs. In this context, “retention” marketing strategies aimed not only at the acquisition of new customers but also at the profitability of existing ones allow industries to apply specific production strategies so as to maximize their revenues. This is possible by means of the analysis of various kinds of information coming from customers, products, purchases and so on. In this paper, we focus on customer loyalty programs. In particular, we propose a Cloud-based Software as a Service (SaaS) architecture that store and analyses big data related to purchases and products’ ranks in order to provide customers a list of recommended products. Experiments focus on a prototype of Human to Machine (H2M) workflow for the pre-selection of customers deployed on both private and hybrid Cloud scenarios.

A Cloud-Based System for Improving Retention Marketing Loyalty Programs in Industry 4.0: a Study on Big Data Storage Implications

Galletta, Antonino
Primo
;
Carnevale, Lorenzo
Secondo
;
Celesti, Antonio
;
Fazio, Maria
Penultimo
;
Villari, Massimo
Ultimo
2018-01-01

Abstract

Nowadays, the growing global economy and demand for customized products are bringing the manufacturing industry from a sellers’ market towards a buyers’ market. In this context, the smart manufacturing enabled by Industry 4.0 is changing the whole production cycle of companies specialised on different kinds of products. On one hand, the advent of Cloud computing and social media makes the customers’ experience more and more inclusive, whereas on the other hand Cyber-Physical System (CPS) technologies help industries to change in real time the cycle of production according to customers’ needs. In this context, “retention” marketing strategies aimed not only at the acquisition of new customers but also at the profitability of existing ones allow industries to apply specific production strategies so as to maximize their revenues. This is possible by means of the analysis of various kinds of information coming from customers, products, purchases and so on. In this paper, we focus on customer loyalty programs. In particular, we propose a Cloud-based Software as a Service (SaaS) architecture that store and analyses big data related to purchases and products’ ranks in order to provide customers a list of recommended products. Experiments focus on a prototype of Human to Machine (H2M) workflow for the pre-selection of customers deployed on both private and hybrid Cloud scenarios.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3116920
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