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Publication date: 4 December 2020

Samir Yerpude

A paradigm shift is observed in the last decade where transactional marketing is taken over by relationship marketing. Customer relationship management (CRM) has been an integral…

Abstract

A paradigm shift is observed in the last decade where transactional marketing is taken over by relationship marketing. Customer relationship management (CRM) has been an integral part of a business strategy in the current era. CRM integrates product sales, product marketing and, most importantly, customer service in a seamless manner to generate value for the organization as well as for its customers in short a win-win situation. Profoundly, CRM needs to be a part of the top management agenda and driven top-down instead of an IT initiative. Industrial revolution 4.0 is characterized by cyber-physical systems. Internet of Things (IoT) is the digital technology for the present and future. IoT primarily aids in gathering real-time data and transmitting the same over the internet to a central repository for consuming the same in business models. Real-time customer data analytics can be performed by customer-centric organizations to enhance CRM.

Article
Publication date: 1 May 2023

Paulo Rita, Maria Teresa Borges-Tiago and Joana Caetano

The hospitality industry values segmentation and loyalty programs (LPs), but there is limited research on new methods for segmenting loyalty program members, so managers often…

Abstract

Purpose

The hospitality industry values segmentation and loyalty programs (LPs), but there is limited research on new methods for segmenting loyalty program members, so managers often rely on conventional techniques. This study aims to use big data-driven segmentation methods to cluster customers and provide a new solution for customer segmentation in hotel LPs.

Design/methodology/approach

Using the k-means algorithm, this study examined 498,655 profiles of guests enrolled in a multinational hotel chain’s loyalty program. The objective was to cluster guests according to their consumption behavior and monetary value and compare data-driven segments based on brand preferences, demographic data and monetary value with loyalty program tiers.

Findings

This study shows that current tier-based LPs lack features to improve customer segmentation, and some high-tier members generate less revenue than low-tier members. Therefore, more attention should be given to truly valuable customers.

Practical implications

Hotels can segment LP members to develop targeted campaigns and uncover new insights. This will help to transform LPs to make them more valuable and profitable and use differentiated rewards and strategies.

Originality/value

As not all guests or hotel brands benefit equally from LPs, additional segmentation is required to suit varying guest behaviors. Hotel managers can use data mining techniques to develop more efficient and valuable LPs with personalized strategies and rewards.

Details

International Journal of Contemporary Hospitality Management, vol. 35 no. 12
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 24 January 2023

Dawn Holmes, Judith Zolkiewski and Jamie Burton

Despite data being a hot topic, little is known about how data can be successfully used in interactions in business-to-business relationships, specifically in the boundary…

Abstract

Purpose

Despite data being a hot topic, little is known about how data can be successfully used in interactions in business-to-business relationships, specifically in the boundary spanning contexts of firms working together to use data and create value. Hence, this study aims to investigate the boundary spanning context of data-driven customer value projects to understand the outcomes of such activities, including the types of value created, how resulting value is shared between the interacting firms, the types of capabilities required for firms to deliver value from data and in what contexts different outcomes are created and different capabilities required.

Design/methodology/approach

Three abductive case studies were undertaken with firms from different business-to-business domains. Data were coded in NVivo and interpreted using template analysis and cross-case comparison. Findings were sense checked with the case study companies and other practitioners for accuracy, relevance and resonance.

Findings

The findings expand our understanding of firm interactions when extracting value from data, and this study presents 15 outcomes of value created by the firms in the study. This study illustrates the complexity and intertwined nature of the process of value creation, which emphasises the need to understand distinct types of outcomes of value creation and how they benefit the firms involved. This study goes beyond this by categorising these outcomes as unilateral (one actor benefits), developmental (one actor benefits from the other) or bilateral (both actors benefit).

Research limitations/implications

This research is exploratory in nature. This study provides a basis for further exploration of how firm interactions surrounding the implementation of data-driven customer value projects can benefit the firms involved and offers some transferable knowledge which is of particular relevance to practitioners.

Practical implications

This research contributes to the understanding of data-driven customer-focused projects and offers some practical management tools. The identification of outcomes helps define project goals and helps connect these goals to strategy. The organisation of outcomes into themes and contexts helps managers allocate appropriate human resources to oversee projects, mitigating the impacts of a current lack of talent in this area. Additionally, using the findings of this research, firms can develop specific capabilities to exploit the project outcomes and the opportunities such projects provide. The findings can also be used to enhance relationships between firms and their customers, providing customer value.

Originality/value

This work builds on research that explores the creation of value from data and how value is created in boundary spanning contexts. This study expands existing work by providing greater insight into the mechanics and outcomes of value creation and by providing specific examples of value created. This study also offers some recommendations of capability requirements for firms undertaking such work.

Details

Journal of Business & Industrial Marketing, vol. 38 no. 6
Type: Research Article
ISSN: 0885-8624

Keywords

Article
Publication date: 19 December 2019

Sixing Chen, Jun Kang, Suchi Liu and Yifan Sun

This paper aims to build on the latest advances in cognitive computing techniques to systematically illustrate how unstructured data from users can offer significant value for…

1073

Abstract

Purpose

This paper aims to build on the latest advances in cognitive computing techniques to systematically illustrate how unstructured data from users can offer significant value for co-innovation.

Design/methodology/approach

The paper adopts a general overview approach to understand how unstructured data from users can be analyzed with cognitive computing techniques for innovation. The paper links the computerized techniques with marketing innovation problems with an integrated framework using dynamic capabilities and complexity theory.

Findings

The paper identifies a suite of methodologies for facilitating company co-innovation via engaging with customers and external data with cognitive computing technologies. It helps to expand marketing researchers and practitioners’ understanding of using unstructured data.

Research limitations/implications

This paper provides a conceptual framework that divides co-innovation process into three stages, ideas generation, ideas integration and ideas evaluation, and maps cognitive computing methodologies and technologies to each stage. This paper makes the theoretical contributions by developing propositions from both customer and firm perspectives.

Practical implications

This paper can be used for companies to engage consumers and external data for co-innovation activities by strategically select appropriate cognitive computing techniques to analyze unstructured data for better insights.

Originality/value

Given the lack of systematic discussion regarding what is possible from using cognitive computing to analyze unstructured data for co-innovation. This paper makes first attempt to summarize how unstructured data can be analyzed with cognitive computing techniques. This paper also integrates complexity theory to the framework from a novel perspective.

Details

European Journal of Marketing, vol. 54 no. 3
Type: Research Article
ISSN: 0309-0566

Keywords

Article
Publication date: 30 July 2019

Hatef Rasouli and Changiz Valmohammadi

Customer identity and access management (CIAM) is a sub-genre of traditional identity and access management (IAM) that has emerged in the past few years to meet evolving business…

Abstract

Purpose

Customer identity and access management (CIAM) is a sub-genre of traditional identity and access management (IAM) that has emerged in the past few years to meet evolving business requirements. CIAM focuses on the connectivity with the customer when accessing any type of systems, on-premises and in the cloud, from registration to track. The purpose of this study is to introduce different dimensions of CIAM toward exploiting them in organizations.

Design/methodology/approach

Based on a thorough review of the relevant literature and semi-structured interview with six experts in the field of digital IAM the necessary data were gathered. Then through the use of content analysis technique, analytic codes and also categories and sub-categories of the data were generated.

Findings

Results indicate that four categories, namely, customer identity management, customer access management and information technology and business management are the most important factors affecting the identification of CIAM dimensions.

Originality/value

Organizations could avail of the proposed conceptual model toward identification and offering customized products and services solutions to their customers.

Article
Publication date: 10 April 2017

Mokh Suef, Suparno Suparno and Moses Laksono Singgih

The purpose of this paper is to propose a methodology to use complaints, claims and company innovation as an internal data source of customer needs for product development using…

Abstract

Purpose

The purpose of this paper is to propose a methodology to use complaints, claims and company innovation as an internal data source of customer needs for product development using the quality function deployment (QFD)-Kano approach instead of an ordinary customer survey.

Design/methodology/approach

This paper confirms that the customer complaints and claims and company innovations from the internal data source are equivalent to the Kano model’s product attributes. Data were selected from the company’s documents. To investigate the data category, a Kano questionnaire was designed and tested with 100 random respondents. Based on their answers, categories for the quality characteristics were determined and compared with the initial data categories. A second survey using professional customer respondents was conducted to increase the results’ reliability.

Findings

The approach was shown to be effective in employing complaints, claims and innovations as an alternative source of customer needs in the QFD-Kano approach.

Research limitations/implications

It is assumed that companies document their customer complaints and claims, as well as their strategic innovation plans. The complaint and claim data need to be extracted to reveal their quality characteristics. For future research, data extraction using text or data mining may be useful to bridge this gap.

Practical implications

The product development team may ascertain customer needs as duly classified. This voice of the customer is more accurate and requires less time.

Originality/value

The paper may be of value to researchers and practitioners involved in product design and development, since it offers a new source of customer need data obtained internally as an alternative to customer surveys.

Details

The TQM Journal, vol. 29 no. 3
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 12 March 2018

Merlin Stone and Eleni Aravopoulou

This case study describes how one of the world’s largest public transport operations, Transport for London (TfL), transformed the real-time availability of information for its…

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Abstract

Purpose

This case study describes how one of the world’s largest public transport operations, Transport for London (TfL), transformed the real-time availability of information for its customers and staff through the open data approach, and what the results of this transformation were. The purpose of this paper is therefore to show what is required for an open data approach to work.

Design/methodology/approach

This case study is based mainly on interviews at TfL and data supplied by TfL directly to the researchers. It analyses as far as possible the reported facts of the case to identify the processes required for open data and the benefits thereof.

Findings

The main finding is that achieving an open data approach in public transport is helped by having a clear commitment to the idea that the data belong to the public and that third parties should be allowed to use and repurpose the information, by having a strong digital strategy, and by creating strong partnerships with data management organisations that can support the delivery of high volumes of information.

Research limitations/implications

This research is based upon a single case study, albeit over an extensive period, so the findings cannot be applied simply to other situations, other than as evidence of what is possible. However, similar processes could be applied in other situations as a heuristic approach to open data strategy implementation.

Practical implications

The case study shows how open data can be used to create commercial and non-commercial customer-facing products and services, which passengers and other road users use to gain a better travel experience, and that this approach can be valued in terms of financial/economic contribution to customers and organisations.

Social implications

This case study shows the value that society can obtain from the opening of data in public transport, and the importance of public service innovation in delivering benefits to citizens.

Originality/value

This is the first case study to show in some detail some of the processes and activities required to open data to public service customers and others.

Details

The Bottom Line, vol. 31 no. 1
Type: Research Article
ISSN: 0888-045X

Keywords

Article
Publication date: 1 November 2006

Malte Geib, Lutz M. Kolbe and Walter Brenner

The aim of this paper is to identify key issues and successful patterns of collaborative customer relationship management (CRM) in financial services networks.

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Abstract

Purpose

The aim of this paper is to identify key issues and successful patterns of collaborative customer relationship management (CRM) in financial services networks.

Design/methodology/approach

The study takes the form of a multi‐case analysis.

Findings

The paper finds that key issues of CRM in financial services networks are redundant competencies of partnering companies, privacy constraints, CRM process integration, customer information exchange, and CRM systems integration. To address these issues, partnering companies have to agree on clear responsibilities in collaborative processes. Data privacy protection laws require that customer data transfer between partnering companies has the explicit approval of customers. For process integration, companies have to agree on process standards and a joint integration architecture. Web services and internet‐based standards can be used for inter‐organizational systems integration. Data integration requires the development of a joint data model. Either a unique customer identification number or a matching algorithm must be used to consolidate customer data records of partnering companies.

Research limitations/implications

Because of the limited number of case studies, generalizability is limited. The findings can serve as a starting point for researchers seeking to further explore the topic with quantitative methods.

Practical implications

The findings can be used by financial services networks to improve their collaborative CRM approaches.

Originality/value

The importance of collaborative CRM in business networks is likely to increase due to the continuing deconstruction of value chains not only in the financial services industry, but in other industries as well. Nevertheless, the topic has not received much attention in research.

Details

Journal of Enterprise Information Management, vol. 19 no. 6
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 20 August 2019

Sandhya N., Philip Samuel and Mariamma Chacko

Telecommunication has a decisive role in the development of technology in the current era. The number of mobile users with multiple SIM cards is increasing every second. Hence…

Abstract

Purpose

Telecommunication has a decisive role in the development of technology in the current era. The number of mobile users with multiple SIM cards is increasing every second. Hence, telecommunication is a significant area in which big data technologies are needed. Competition among the telecommunication companies is high due to customer churn. Customer retention in telecom companies is one of the major problems. The paper aims to discuss this issue.

Design/methodology/approach

The authors recommend an Intersection-Randomized Algorithm (IRA) using MapReduce functions to avoid data duplication in the mobile user call data of telecommunication service providers. The authors use the agent-based model (ABM) to predict the complex mobile user behaviour to prevent customer churn with a particular telecommunication service provider.

Findings

The agent-based model increases the prediction accuracy due to the dynamic nature of agents. ABM suggests rules based on mobile user variable features using multiple agents.

Research limitations/implications

The authors have not considered the microscopic behaviour of the customer churn based on complex user behaviour.

Practical implications

This paper shows the effectiveness of the IRA along with the agent-based model to predict the mobile user churn behaviour. The advantage of this proposed model is as follows: the user churn prediction system is straightforward, cost-effective, flexible and distributed with good business profit.

Originality/value

This paper shows the customer churn prediction of complex human behaviour in an effective and flexible manner in a distributed environment using Intersection-Randomized MapReduce Algorithm using agent-based model.

Details

Data Technologies and Applications, vol. 53 no. 3
Type: Research Article
ISSN: 2514-9288

Keywords

Article
Publication date: 29 November 2019

Mohamad Abu Ghazaleh and Abdelrahim M. Zabadi

Internet of things (IoT) and big data (BD) could change how the societies function. This paper explores the role of IoT and BD and their impact on customer relationship management…

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Abstract

Purpose

Internet of things (IoT) and big data (BD) could change how the societies function. This paper explores the role of IoT and BD and their impact on customer relationship management (CRM) investments in modern customer service. The purpose of this paper is to develop an analytic hierarchy planning framework to establish criteria weights and to develop a general self-assessment model for determining the most important factors influencing the IoT and BD investment in CRM. The authors found that most studies have focused on conceptualizing the impact of IoT without BD and with limited empirical studies and analytical models. This paper sheds further light on the topic by presenting both IoT and BD aspects of future CRM.

Design/methodology/approach

The analytic hierarchy process (AHP) methodology is used to weight and prioritize the factors influencing the IoT and BD investment in modern CRM in the service industry. The AHP framework resulted in a ranking of 21 sustainability sub-factors based on evaluations by experienced information technology and customer service professionals.

Findings

The paper provides significant insight on the new frontier of CRM, focusing on the use of IoT and BD and the respective solutions to address them were identified. This study primarily contributes in providing the process of effectively managing and implementing IoT and BD in big businesses by identifying the connecting link between firms and customers.

Practical implications

The understanding of new frontier of CRM connective via IoT and BD can solve the dilemmas and challenges linked to the practice of implement IoT and BD in the information systems field. The study provides valuable information and critical analysis of IoT and BD with regard to the integration of CRM. Finally, this study further provides directions for future researchers.

Originality/value

IoT and BD are a growing phenomenon, which business decision-makers and information professionals need to consider seriously to properly ascertain the modern CRM dimensions in the digital economies. They also should embrace the proper CRM innovation, which is powered by IoT and BD, and discover how IoT and BD can bring the next level of maturity to CRM “CRM of everything.”

Details

International Journal of Organizational Analysis, vol. 28 no. 1
Type: Research Article
ISSN: 1934-8835

Keywords

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