Four Eras of CRM Selling

2015 ◽  
pp. 83-100
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.

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.

scholarly journals TOWARDS EFFECTIVE CUSTOMER RELATIONSHIP MANAGEMENT IN OMAN: ROLE OF BIG DATA

2017 ◽  
Vol 5 (10) ◽  
pp. 92-100
Author(s):  
Tarek Khalil ◽  
Al-Refai Mohammad ◽  
Amer Nizar Fayez ◽  
SharafQudah Mohammed
Keyword(s):  
Big Data ◽  
Customer Relationship Management ◽  
Predictive Analytics ◽  
Big Data Analytics ◽  
Relationship Management ◽  
Qualitative Evaluation ◽  
Customer Relationship ◽  
Customer Engagement ◽  
Time Data ◽  
Analytical Tools

We established a framework to explore the feasibility of enabling big data within the customer relationship management (CRM) strategies in Oman for creating sustainable business profit nationwide. A qualitative evaluation was made based on predictive analytics convergence and big data facilitated CRM. It was found that the big data analytics can meticulously alter the competitive industrial setting, and thereby proffered notable benefits to the business organization in terms of operation, strategies, and competitiveness. Results revealed that companies must introduce analytical tools, real-time data, and hire talented as well as skilled employees to improve the productivity in consistent with the new business model. Furthermore, depending on the customer engagement, an assemblage and analysis of enormous data volume together with analytical tools was discerned to assist companies towards efficient resource allocation and capital spending. The implications of using big data for CRM in Oman and way forward were emphasized.

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
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