Interaction Mining

2012 ◽  
pp. 688-709
Author(s):  
Vincenzo Pallotta ◽  
Lammert Vrieling ◽  
Rodolfo Delmonte
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Future Development ◽  
Business Intelligence ◽  
Relationship Management ◽  
Marketing Research ◽  
Customer Relationship ◽  
Unstructured Data ◽  
Social Media Analytics ◽  
Business Analytics

In this chapter we present the major challenges of a new trend in business analytics, namely Interaction Mining. With the proliferation of unstructured data as the result of people interacting with each other using digital networked devices, classical methods in text business analytics are no longer effective. We identified the causes of their failure as being related to the inadequacy of dealing with conversational data. We propose then to move from Text Mining towards Interaction Mining, and we make several cases for this transition in areas such as marketing research, social media analytics, and customer relationship management. We also propose a roadmap for the future development of Interaction Mining by challenging the current practices in business intelligence and information visualization.

Interaction Mining

2011 ◽  
pp. 122-146 ◽  
Author(s):  
Vincenzo Pallotta ◽  
Lammert Vrieling ◽  
Rodolfo Delmonte
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Future Development ◽  
Business Intelligence ◽  
Relationship Management ◽  
Marketing Research ◽  
Customer Relationship ◽  
Unstructured Data ◽  
Social Media Analytics ◽  
Business Analytics

In this chapter we present the major challenges of a new trend in business analytics, namely Interaction Mining. With the proliferation of unstructured data as the result of people interacting with each other using digital networked devices, classical methods in text business analytics are no longer effective. We identified the causes of their failure as being related to the inadequacy of dealing with conversational data. We propose then to move from Text Mining towards Interaction Mining, and we make several cases for this transition in areas such as marketing research, social media analytics, and customer relationship management. We also propose a roadmap for the future development of Interaction Mining by challenging the current practices in business intelligence and information visualization.

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.

Introduction of Social Media Platforms and Social Media Analytics for Social CRM

2019 ◽  
pp. 107-123
Author(s):  
In Lee
Keyword(s):  
Social Media ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Social Media Analytics ◽  
Social Media Data ◽  
Social Crm ◽  
Social Media Platforms ◽  
Media Data

This chapter reviews customer relationship management, social media platforms, and social media analytics, and discusses how social media platforms and social media analytics are used to support social CRM. Social CRM emerged by integrating social media with customer relationship management. Social media offers companies an array of innovative ways to interact with their employees, customers, partners, and other stakeholders. As the user base of social media is growing rapidly, it is crucial for companies to understand their social media platforms, develop a plan to continually integrate social media with CRM, analyze social media data with social media analytics, and quickly respond to the needs of customers. To help CRM managers utilize social media analytics systematically, this chapter discusses various analytics methods and presents analytics processes for social media data.

Introduction of Social Media Platforms and Social Media Analytics for Social CRM

2018 ◽  
pp. 92-108
Author(s):  
In Lee
Keyword(s):  
Social Media ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Social Media Analytics ◽  
Social Media Data ◽  
Social Crm ◽  
Social Media Platforms ◽  
Media Data

This chapter reviews customer relationship management, social media platforms, and social media analytics, and discusses how social media platforms and social media analytics are used to support social CRM. Social CRM emerged by integrating social media with customer relationship management. Social media offers companies an array of innovative ways to interact with their employees, customers, partners, and other stakeholders. As the user base of social media is growing rapidly, it is crucial for companies to understand their social media platforms, develop a plan to continually integrate social media with CRM, analyze social media data with social media analytics, and quickly respond to the needs of customers. To help CRM managers utilize social media analytics systematically, this chapter discusses various analytics methods and presents analytics processes for social media data.

Customer Relationship Management- The Indian Perspective

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Pankaj K. Trivedi
Keyword(s):  
Social Media ◽  
Product Quality ◽  
Customer Relationship Management ◽  
Paradigm Shift ◽  
Relationship Management ◽  
Modern Technology ◽  
Customer Relationship ◽  
Brand Name ◽  
Service Support ◽  
Indian Perspective

Market is a kingdom and customer is the king. This is a renowned maxim pursued by the Indian companies in true spirit. With the advancement in modern technology, customers are becoming more and more informed about their need and want. Nowadays social media is educating them and they scout around for best product, brand name, product quality, operation, and service support. Marketing has thus, undergone a paradigm shift and has come up to the point of establishing relationship with customer. Not just retaining the existing customers but even attracting new customers has become a big challenge. This is the main reason why companies have shifted their focus from being product-centric to customer-centric.

scholarly journals Implementing Social Customer Relationship Management in Turbulent Environments: A Dynamic Capabilities Perspective

Webology ◽  
2021 ◽  
Vol 18 (SI03) ◽  
pp. 49-70
Author(s):  
Vu Minh Ngo ◽  
Quyen Phu Thi Phan ◽  
Hieu Minh Vu
Keyword(s):  
Social Media ◽  
Customer Relationship Management ◽  
Technology Use ◽  
Customer Value ◽  
Dynamic Capabilities ◽  
Relationship Management ◽  
Customer Relationship ◽  
Superior Performance ◽  
Turbulent Environments ◽  
Social Crm

Purpose: Despite the crucial contribution of social media on customer relationship management (CRM) strategies, how social CRM can be transformed into customer value, and economics returns for firms remain unexplored in the hospitality industry, especially in turbulent environments. As a new approach for dealing with both gradual and disruptive changes in the market, this study develops and tests the mediating role of dynamic capabilities in the social CRM - performance relationship. Methodology: Drawing on resource-based view and capabilities perspectives, a mixed methodology was applied. First, a survey was conducted to quantitatively test the proposed hypotheses using Structural Equation Modelling with PLS approach (PLS-SEM) on a sample consisting of 111 SEMs. Then, a qualitative fuzzy-set Comparative Analysis (fsQCA) was employed to look for the unique combinations of capabilities to achieve firms‟ superior performance. Findings: The outcomes indicated a mixture of expected and unexpected findings, including: (i) the direct effect of social CRM on firm‟s performance; (ii) Dynamic capabilities as the missing link between social CRM capabilities and firms‟ performance; (iii) the unique roles of social media technology use in the combinations with other capabilities for generating the best firms‟ performance. Originality: This study is among the few to consider the dynamic nature of the market when investigating how to implement Social CRM successfully. The insights and practical implications in this study can be useful for managers in SMEs whose desire is to build a dynamic system for improving customer value and firms‟ performance.

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