scholarly journals The New Trend and Application of Customer Relationship Management under Big Data Background

2016 ◽  
Vol 07 (08) ◽  
pp. 841-848 ◽  
Author(s):  
Lan Wang
Keyword(s):  
Big Data ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship

A structured literature review on Big Data for customer relationship management (CRM): toward a future agenda in international marketing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pasquale Del Vecchio ◽  
Gioconda Mele ◽  
Evangelia Siachou ◽  
Gloria Schito
Keyword(s):  
Big Data ◽  
Customer Relationship Management ◽  
Research Agenda ◽  
International Marketing ◽  
Relationship Management ◽  
Customer Relationship ◽  
Future Research ◽  
Content Type ◽  
Future Research Agenda ◽  
Structured Literature Review

PurposeThis paper aims to advance the international marketing debate by presenting the results of a structured literature review (SLR) focusing on Big Data implementation in customer relationship management (CRM) strategizing. It outlines past and present literature and frames a future research agenda.Design/methodology/approachThe research analyzes papers published in journals from 2013 to 2020, deriving significant insights about Big Data applications in CRM. A sample of 48 articles indexed at Scopus was preliminarily submitted for bibliometric analysis. Finally, 46 papers were analyzed with content and a bibliometric analysis to identify areas of thematic specializations.FindingsThe paper presents a conceptual multilevel framework demonstrating areas of specialization emerging from the literature. The framework is built around four coordinated sequences of actions relevant to “why,” “what,” “who” and “how” Big Data is implemented in CRM strategies, thus supporting the conception and implementation of an internationalization marketing strategy.Research limitations/implicationsImplications for the development of the future research agenda on international marketing arise from the comprehension of Big Data in CRM strategy.Originality/valueThe paper provides a comprehensive SLR of the articles dealing with models and processes of Big Data for CRM from an international marketing perspective. Despite these issues' relevance and the increasing literature focused on them, research in this area is still fragmented and underexplored, requiring more systematic and holistic studies.

Big Data and Service Science

2016 ◽  
pp. 180-196
Author(s):  
Tu-Bao Ho ◽  
Siriwon Taewijit ◽  
Quang-Bach Ho ◽  
Hieu-Chi Dam
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Service Science ◽  
Customer Relationship ◽  
Service Value ◽  
Mining Methods ◽  
The Relationship

Big data is about handling huge and/or complex datasets that conventional technologies cannot handle or handle well. Big data is currently receiving tremendous attention from both industry and academia as there is much more data around us than ever before. This chapter addresses the relationship between big data and service science, especially how big data can contribute to the process of co-creation of service value. In particular, the value co-creation in terms of customer relationship management is mentioned. The chapter starts with brief descriptions of big data, machine learning and data mining methods, service science and its model of value co-creation, and then addresses the key idea of how big data can contribute to co-create service value.

scholarly journals Customer relationship management and big data enabled: Personalization & customization of services

2019 ◽  
Vol 15 (2) ◽  
pp. 94-101 ◽  
Author(s):  
Muhammad Anshari ◽  
Mohammad Nabil Almunawar ◽  
Syamimi Ariff Lim ◽  
Abdullah Al-Mudimigh
Keyword(s):  
Big Data ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship

Big Data-enabled Customer Relationship Management: A holistic approach

2018 ◽  
Vol 54 (5) ◽  
pp. 818-846 ◽  
Author(s):  
Pierluigi Zerbino ◽  
Davide Aloini ◽  
Riccardo Dulmin ◽  
Valeria Mininno
Keyword(s):  
Big Data ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Holistic Approach ◽  
Customer Relationship

Detecting customers knowledge from social media big data: toward an integrated methodological framework based on netnography and business analytics

2020 ◽  
Vol 24 (4) ◽  
pp. 799-821 ◽  
Author(s):  
Pasquale Del Vecchio ◽  
Gioconda Mele ◽  
Giuseppina Passiante ◽  
Demetris Vrontis ◽  
Cosimo Fanuli
Keyword(s):  
Social Media ◽  
Big Data ◽  
Customer Relationship Management ◽  
Value Creation ◽  
Relationship Management ◽  
Customer Relationship ◽  
Business Analytics ◽  
Content Type ◽  
Social Big Data ◽  
Practical Implications

Purpose This paper aims to demonstrate how the integration of netnography and business analytics can support companies in the process of value creation from social big data by leveraging on customer relationship management and customer knowledge management (CKM). Design/methodology/approach This paper adopts the methodology of a single case study by using desk analysis, netnography and business analytics. The context of analysis has been identified into the case of Aurora Company, a well-known producer of fountain pens. Findings The case demonstrates how the integration of big data analytics and netnography is relevant for the development of a customer relationship management strategy. The results obtained have been categorized according to the three main categories of customer knowledge, such as knowledge for, from and about customer. Research limitations/implications This paper presents implications for the advancement of the theory on CKM by demonstrating, as the acquisition, storage and management of data generated by customers on social media require the adoption of a cross-disciplinary approach resulting from the integration of qualitative and quantitative approaches. The framework is structured as methodological tool to detect knowledge in virtual community. Practical implications Practical implications arise for managers and entrepreneurs in terms of value creation from knowledge assets generated on social big data through the management of the customers’ relationship and data-driven innovation patterns. Originality/value This paper offers an original contribution of integration of well-established research streams. The focus on the knowledge under the perspectives of information assets for, from and about customers in the debate on value creation and management of big data is an element of value offered by this study in addition to the comprehension of strategies of social customer relationship management as actual initiative embraced by a company in the leveraging of innovation and tradition.

Four Eras of CRM Selling

2017 ◽  
pp. 939-957 ◽  
Author(s):  
Cindy Marie Gordon
Keyword(s):  
Big Data ◽  
Customer Relationship Management ◽  
Productivity Growth ◽  
Predictive Analytics ◽  
Relationship Management ◽  
Customer Relationship ◽  
Sales Professionals ◽  
Sales Organizations ◽  
And Mathematics ◽  
Sales Quotas

This chapter examines the evolution of selling, as well as the software solutions that sales professionals have used to support Customer Relationship Management (CRM) practices. Tracing over four eras of selling, spanning 30 years, including product to solution selling, customer centric selling, social selling, and big data: predictive analytics selling. This chapter examines the stark reality that after three generations of CRM: less than 50% of sales organizations do not achieve their sales quotas. It is time to seriously challenge the current approaches to Customer Relationship Management (CRM), as quota attainment is seriously underperforming, despite what sales software leaders espouse. Research from CSO Insights, Accenture (2013), and Sales Choice (2014) is compelling to pause to Think Big and Smarter! The next era's growth resides in Big Data and Predictive Analytics as advanced sciences and mathematics will pave the way to unlock productivity growth challenges that have plagued the first three eras.

Big Data and Service Science

2014 ◽  
pp. 128-144 ◽  
Author(s):  
Tu-Bao Ho ◽  
Siriwon Taewijit ◽  
Quang-Bach Ho ◽  
Hieu-Chi Dam
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Service Science ◽  
Customer Relationship ◽  
Service Value ◽  
Mining Methods ◽  
The Relationship

Big data is about handling huge and/or complex datasets that conventional technologies cannot handle or handle well. Big data is currently receiving tremendous attention from both industry and academia as there is much more data around us than ever before. This chapter addresses the relationship between big data and service science, especially how big data can contribute to the process of co-creation of service value. In particular, the value co-creation in terms of customer relationship management is mentioned. The chapter starts with brief descriptions of big data, machine learning and data mining methods, service science and its model of value co-creation, and then addresses the key idea of how big data can contribute to co-create service value.

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