A Cloud-Based System for Improving Retention Marketing Loyalty Programs in Industry 4.0: A Study on Big Data Storage Implications
A Cloud-Based System for Improving Retention Marketing Loyalty Programs in Industry 4.0: A Study on Big Data Storage Implications
复制标题
用于改善工业 4.0 中保留营销忠诚度计划的基于云的系统：大数据存储影响的研究
DOI：
10.1109/access.2017.2776400
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发表时间：
2018
期刊：
影响因子：
3.9
通讯作者：
M. Villari
中科院分区：
文献类型：
--
作者：
A. Galletta;Lorenzo Carnevale;A. Celesti;M. Fazio;M. Villari
如今，日益增长的全球经济和对定制产品的需求正在将制造业从卖方市场带入买方市场。在此背景下，工业4.0带来的智能制造正在改变着专注于不同种类产品的公司的整个生产周期。一方面，云计算和社交媒体的出现使客户的体验越来越包容，另一方面，网络物理系统技术帮助行业根据客户的需求实时改变生产周期。在这种情况下，“留存”营销战略不仅旨在获得新客户，而且还旨在提高现有客户的盈利能力，从而使各行业能够采用特定的生产战略，以使其收入最大化。这可以通过分析来自客户、产品、购买等的各种信息来实现。在本文中，我们关注的是客户忠诚度计划。特别是，我们提出了基于云的软件作为服务架构，存储和分析与购买和产品排名相关的大数据，以便为客户提供推荐产品列表。实验的重点是针对在私有云和混合云场景中部署的客户进行预选的人机工作流原型。
Nowadays, the growing global economy and demand for customized products are bringing the manufacturing industry from a sellers’ market toward a buyers’ market. In this context, the smart manufacturing enabled by Industry 4.0 is changing the whole production cycle of companies specialized 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 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 cloud-based software as a service 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 workflow for the pre-selection of customers deployed on both private and hybrid cloud scenarios.