Showing papers on "Customer relationship management published in 2016"

From Social to Sale: The Effects of Firm-Generated Content in Social Media on Customer Behavior

Abstract: Given the unprecedented reach of social media, firms are increasingly relying on it as a channel for marketing communication. The objective of this study is to examine the effect of firm-generated content (FGC) in social media on three key customer metrics: spending, cross-buying, and customer profitability. The authors further investigate the synergistic effects of FGC with television advertising and e-mail communication. To accomplish their objectives, the authors assemble a novel data set comprising customers’ social media participation data, transaction data, and attitudinal data obtained through surveys. The results indicate that after the authors account for the effects of television advertising and e-mail marketing, FGC has a positive and significant effect on customers’ behavior. The authors show that FGC works synergistically with both television advertising and e-mail marketing and also find that the effect of FGC is greater for more experienced, tech-savvy, and social media–prone custom...

Co-creation and higher order customer engagement in hospitality and tourism services: A critical review

Abstract: Purpose – This paper aims to present a review of the literature associated with co-creation and higher-order customer engagement concepts and poses critical questions related to the current state of research. Additionally, the paper presents a framework for customer engagement and co-creation with relevance to hospitality transactions. Design/methodology/approach – Earlier research on co-production, co-creation, consumer engagement and service-dominant logic are discussed and synthesized. Based on this synthesis, links and contrasts of these varying research streams are presented providing an articulation of key characteristics of each and how these might be applied within a hospitality context. Findings – Modalities in service transactions vary among traditional production, co-production and co-creation based on changes in attitudes, enabling technologies and the logic or ideology supporting the change. Transaction characteristics vary among manufacturing, quasi-manufacturing and services based on severa...

Customer Relationship Management: An Analysis Framework and Implementation Strategies

Abstract: Customer relationship management is a buzzword around businesses. “CRM comprises a set of processes and enabling systems supporting a business strategy to build long term, profitable relationships with specific customers.” There are a few components of CRM implementation, most importantly, the IT component. While revolutionary in many respects, CRM is also a natural and predictable extension of how marketing and sales have evolved over the years and, in many ways, are coming full circle. The Customer Relationship Management Cycle consists of an evaluation phase, a planning phase, an implementation phase, and a review phase. Several intrinsic business reasons are driving a great number of companies going onto the CRM highway. Companies can overlay their own data to better understand customer attributes and get better results. The most substantial impacts from CRM transitions fall into the category of information support. Customer information and the associated technology tools are the foundation upon which...

A survey of the applications of text mining in financial domain

Abstract: Text mining has found a variety of applications in diverse domains. Of late, prolific work is reported in using text mining techniques to solve problems in financial domain. The objective of this paper is to provide a state-of-the-art survey of various applications of Text mining to finance. These applications are categorized broadly into FOREX rate prediction, stock market prediction, customer relationship management (CRM) and cyber security. Since finance is a service industry, these problems are paramount in operational and customer growth aspects. We reviewed 89 research papers that appeared during the period 2000-2016, highlighted some of the issues, gaps, key challenges in this area and proposed some future research directions. Finally, this review can be extremely useful to budding researchers in this area, as many open problems are highlighted.

Interrelationships of risks faced by third party logistics service providers: A DEMATEL based approach

Abstract: This paper analyses the interrelationships between risks faced by third party logistics service providers (3PLs) in relation to one of its customers using DEMATEL. Novel analysis of both within and between risk categories and generation of threshold value to prioritize risks generate useful insights. Results show that arms-length relationship between the customer and the 3PLs has strong influence on other risks and there is a need for collaborative relationships between 3PLs and its customers. Moreover, analysis indicates that the 3PLs need to improve internal processes related to quality management, flexibility of its operations and also geographical coverage of their services.

How can SMEs benefit from big data? Challenges and a path forward

Abstract: Big data is big news, and large companies in all sectors are making significant advances in their customer relations, product selection and development and consequent profitability through using this valuable commodity. Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. In Europe, SMEs are a vital part of the economy, and the challenges they encounter need to be addressed as a matter of urgency. This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities. The paper proposes a big data maturity model for SMEs as a first step towards an SME roadmap to data analytics. It considers the ‘state-of-the-art’ of IT with respect to usability and usefulness for SMEs and discusses how SMEs can overcome the barriers preventing them from adopting existing solutions. The paper then considers management perspectives and the role of maturity models in enhancing and structuring the adoption of data analytics in an organisation. The history of total quality management is reviewed to inform the core aspects of implanting a new paradigm. The paper concludes with recommendations to help SMEs develop their big data capability and enable them to continue as the engines of European industrial and business success. Copyright © 2016 John Wiley & Sons, Ltd.

Model Selection Management Systems: The Next Frontier of Advanced Analytics

Abstract: John Boyd recognized in the 1960's the importance of situation awareness for military operations and introduced the notion of the OODA loop (Observe, Orient, Decide, and Act). Today we realize that many applications have to deal with situation awareness: Customer Relationship Management, Human Capital Management, Supply Chain Management, patient care, power grid management, and cloud services management, as well as any IoT (Internet of Things) related application; the list seems to be endless. Situation awareness requires applications to support the management of data, knowledge, processes, and other services such as social networking in an integrated way. These applications additionally require high personalization as well as rapid and continuous evolution. They must provide a wide variety of operational and functional requirements, including real time processing.Handcrafting these applications is an almost impossible task requiring exhaustive resources for development and maintenance. Due to the resources and time involved in their development, these applications typically fall way short of the desired functionality, operational characteristics, and ease and speed of evolution. We - the authors - have developed a model enabling the development and maintenance of situation-aware applications in a declarative and therefore economical manner; we call this model KIDS - Knowledge Intensive Data-processing System.

Retention Futility: Targeting High Risk Customers Might Be Ineffective

Abstract: Churn management is a top priority for most businesses as it directly ties to firm profitability and value. Companies in a variety of sectors (e.g., telecommunications, insurance, healthcare, online subscriptions) increasingly start managing churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While a significant amount of work has been dedicated to developing churn prediction models that accurately assess customers' risk of churning, no work has investigated whether it is indeed optimal to target individuals who are at the highest risk of churning. In this paper we challenge the most common practice for proactive churn management and claim that, when the main goal is to select customers for preventive retention efforts, identifying customers at high risk of churning does not suffice to drive the firm's decisions. We argue that because customers respond differently to the firm's intervention, a firm should not target those with the highest risk of churning but those with the highest sensitivity to the intervention. Consequently, we propose a new approach for proactive churn management that leverages the firm's capabilities by running a retention pilot, identifies the observed heterogeneity in the response to the intervention, and selects target customers based on their sensitivity to the intervention, hence ensuring that the retention efforts are not futile. Combining data from two field experiments with machine learning techniques, we empirically demonstrate that the proposed approach is significantly more effective than the standard practice of targeting customers at the highest risk of churning. We show that the same retention campaign would result in a further reduction of up to 6.8 percentage points in churn rate if the focal firm had followed our proposed approach (instead of the industry standard). Contrary to common wisdom, we consistently find that customers identified as being at the highest risk of churning are not necessarily the best targets for proactive churn programs. These findings suggest that retention programs can be futile not because they offer the wrong incentives, but because firms do not apply the right targeting rule.

Social media’s impact on organizational performance and entrepreneurial orientation in organizations

Abstract: Purpose Based on the system of value chain theory, the purpose of this paper is to investigate the impact of social media usage on the performance and the entrepreneurial orientation of the organizations. Design/methodology/approach A total of 174 organizations responded to the survey. Findings The result of the study showed that social media usage has a very strong positive impact on organizations’ performance, in terms of cost reduction, improved customer relations, and enhanced information accessibility. Research limitations/implications In the study, social media usage was categorized into three sub-constructs such as social media usage for marketing, social media usage for building customer relations, and social media usage for information search. This study investigated the usage of social media and its impact as a whole, considering all social media tools together. Finally, this study used a cross-sectional sample to collect data. Practical implications The result of the study benefits the managers to understand the various areas of organizational performance that can be improved by social media usage. Social implications The study also provided evidence that social media usage has strong positive influences on enhancing the entrepreneurial orientation of the organizations. Originality/value This study provides a clearer idea on the real importance of social media and its benefits. This study demonstrated the various areas of organizational performance that can be improved through social media usage.

Internet Integrated Customer Relationship Management a Key Success Factor for Companies in the E-Commerce Arena

Abstract: The purpose of this paper is to analyze the application of the Customer Relationship Management (CRM) in New Economy, which is characterized by the advancement in the information technology. The impacts of the Internet on CRM are assessed in detail in order to reveal the new opportunities and challenges related to CRM in the business settings. In addition, this paper addresses the relationship between CRM and other E-commerce applications, including ERP, SCM and Data Warehousing. Such addresses indicate the role of CRM in the E-commerce arena. Based on the analysis, CRM's future implications in the Internet era to be discussed.

Creating Value with Big Data Analytics: Making Smarter Marketing Decisions

Abstract: Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics. Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors extensive academic and practical knowledge, this book aims to provide managers and analysts withstrategic directions and practical analytical solutions on how to create value from existing and new big data. By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research, and customer relationship management.

Customer relationship management: An approach to competitive advantage in the banking sector by exploring the mediational role of loyalty

Abstract: Purpose – The purpose of this paper is to develop a comprehensive integrated model which helps in explaining the impact of Customer Relationship Management (CRM) dimensions (complaint resolution, customer knowledge, customer empowerment and customer orientation) on customer loyalty and competitive advantage of a bank. The study also explores the mediating role of customer loyalty in the relationship between CRM and competitive advantage in retail banking. Design/methodology/approach – The research is based on a theoretical model which consists of four CRM dimensions and two exogenous variables. These have been used for establishing the hypotheses to analyze relationships between the variables constituting the CRM model. The data have been collected from 278 customers of a private bank. The data were analyzed using structural equation modeling (SEM). The scale was developed and purified through factor analysis (exploratory and confirmatory factor analysis). SEM was then used to examine the causal relationships and “model fit” of the proposed model. Findings – The results provide evidence that the four CRM dimensions have a positive effect on customer loyalty and competitive advantage of the bank. Among the CRM dimensions, customer knowledge is most influential of all the dimensions. Furthermore, customer loyalty acts as the mediator in the CRM model between CRM and competitive advantage. Research limitations/implications – Since, the study involved a single bank and therefore the results should be generalized cautiously. Only four CRM variables were included in the study; additional variables can be introduced in further studies involving different contexts. Practical implications – The study highlights and supports the need for mangers to devote additional resources toward developing a better CRM system. Therefore, mangers need to think beyond the technological aspects and should focus on these four dimensions, especially customer knowledge, to enhance the loyalty and competitiveness. Originality/value – The paper investigated hitherto unexplored relationships between customer-centric CRM dimensions instrumental in providing competitive advantage to a bank through mediational analysis. Thus, it contributes to the information on the implementation of CRM practices valuable for banking sector.

Implementing Customer Relationship Management (CRM) in hotel industry from organizational culture perspective: Case of a chain hotel in the UK

Abstract: Purpose The purpose of this research is to empirically investigate the impact of organizational culture on implementing customer relationship management (CRM) in the hotel industry. Design/methodology/approach The research is conducted with a quantitative approach and a questionnaire adapted from Denison Organizational Culture Survey, and the Mendoza CRM model is the research instrument. The questionnaire was administered among 346 managers of a chain hotel in the UK. Gathered data were subjected to correlation and multiple regression analyses. Findings The correlation analysis demonstrates that organizational culture factors of adaptability, consistency, staff involvement and mission have a positive significant impact on CRM implementations. The multiple regression analysis further showed that though CRM implementation is highly correlated with these four factors, its successful implementation is not dependent on all of them. Research limitations/implications The research is conducted in the frame of a case study where a UK chain hotel is selected; therefore, the findings cannot be generalized to a larger population. This research is conducted in the context of hotel industry and the result might be different for other industries. Due to the limitation in access to all employees, only managers were selected as the sample of the study and future studies with all staff may show different results. Practical implications Organizational culture readiness is one of the most important requirements in CRM implementation initiatives. The results of this study will benefit hotel managers in measuring their organizational culture and improve it toward better CRM outcomes. Originality/value Previous studies on organizational culture and CRM with qualitative approaches have tried to highlight the role of organizational culture on CRM implementation or some have attempted to identify the organizational culture factors with potential impact on CRM implementations. However, very few of these studies have empirically investigated the impacts of organizational culture on CRM implementation, and this is the first study that empirically investigates this impact in the context of the hotel industry.

Social customer relationship management: taking advantage of Web 2.0 and Big Data technologies

Abstract: The emergence of Web 2.0 and Big Data technologies has allowed a new customer relationship strategy based on interactivity and collaboration called Social Customer Relationship Management (Social CRM) to be created. This enhances customer engagement and satisfaction. The implementation of Social CRM is a complex task that involves different organisational, human and technological aspects. However, there is a lack of methodologies to assist companies in these processes. This paper shows a novel methodology that helps companies to implement Social CRM, taking into account different aspects such as social customer strategy, the Social CRM performance measurement system, the Social CRM business processes, or the Social CRM computer system. The methodology was applied to one company in order to validate and refine it.

Customer Relationship Management Concept Strategy And Tools

Abstract: Thank you for reading customer relationship management concept strategy and tools. Maybe you have knowledge that, people have look hundreds times for their favorite books like this customer relationship management concept strategy and tools, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they cope with some infectious virus inside their laptop.

Performance evaluation of different customer segmentation approaches based on RFM and demographics analysis

Abstract: Purpose The purpose of this paper is to determine the best approach to customer segmentation and to extrapolate associated rules for this based on recency, frequency and monetary (RFM) considerations as well as demographic factors. In this study, the impacts of RFM and demographic attributes have been challenged in order to enrich factors that lend comprehension to customer segmentation. Different types of scenario were designed, performed and evaluated meticulously under uniform test conditions. The data for this study were extracted from the database of a global pizza restaurant chain in Turkey. This paper summarizes the findings of the study and also provides evidence of its empirical implications to improve the performance of customer segmentation as well as achieving extracted rule perfection via effective model factors and variations. Accordingly, marketing and service processes will work more effectively and efficiently for customers and society. The implication of this study is that it explains a clear concept for interaction between producers and consumers. Design/methodology/approach Customer relationship management, which aims to manage record and evaluate customer interactions, is generally regarded as a vital tool for companies that wish to be successful in the rapidly changing global market. The prediction of customer behaviors is a strategically important and difficult issue because of the high variance and wide range of customer orders and preferences. So to have an effective tool for extracting rules based on customer purchasing behavior, considering tangible and intangible criteria is highly important. To overcome the challenges imposed by the multifaceted nature of this problem, the authors utilized artificial intelligence methods, including k-means clustering, Apriori association rule mining (ARM) and neural networks. The main idea was that customer clusters are better enhanced when segmentation processes are based on RFM analysis accompanied by demographic data. Weighted RFM (WRFM) and unweighted RFM values/scores were applied with and without demographic factors and utilized to compose different types and numbers of clusters. The Apriori algorithm was used to extract rules of association. The performance analyses of scenarios have been conducted based on these extracted rules. The number of rules, elapsed time and prediction accuracy were used to evaluate the different scenarios. The results of evaluations were compared with the outputs of another available technique. Findings The results showed that having an appropriate segmentation approach is vital if there are to be strong association rules. Also, it has been determined from the results that the weights of RFM attributes affect rule association performance positively. Moreover, to capture more accurate customer segments, a combination of RFM and demographic attributes is recommended for clustering. The results’ analyses indicate the undeniable importance of demographic data merged with WRFM. Above all, this challenge introduced the best possible sequence of factors for an analysis of clustering and ARM based on RFM and demographic data. Originality/value The work compared k-means and Kohonen clustering methods in its segmentation phase to prove the superiority of adopted segmentation techniques. In addition, this study indicated that customer segments containing WRFM scores and demographic data in the same clusters brought about stronger and more accurate association rules for the understanding of customer behavior. These so-called achievements were compared with the results of classical approaches in order to support the credibility of the proposed methodology. Based on previous works, classical methods for customer segmentation have overlooked any combination of demographic data with WRFM during clustering before proceeding to their rule extraction stages.

Analysis of customer churn prediction in telecom industry using decision trees and logistic regression

Abstract: Customer churn prediction in Telecom industry is one of the most prominent research topics in recent years. It consists of detecting customers who are likely to cancel a subscription to a service. Recently, the mobile telecommunication market has changed from a rapidly growing market into a state of saturation and fierce competition. The focus of telecommunication companies has therefore shifted from building a large customer base into keeping customers in house. For that reason, it is valuable to know which customers are likely to switch to a competitor in the near future. The data extracted from telecom industry can help analyze the reasons of customer churn and use that information to retain the customers. We have proposed to build a model for churn prediction for telecommunication companies using data mining and machine learning techniques namely logistic regression and decision trees. A comparison is made based on efficiency of these algorithms on the available dataset.

Knowledge management capability, customer relationship management, and service quality

Abstract: Purpose – Firms survive by exploiting knowledge resources to maintain customer relationships more efficiently and effectively, as well as enhance their service quality. However, whether an enterprise can effectively utilize knowledge resources determines the effectiveness of knowledge management capability (KMC). Hence, the purpose of this paper is to investigate the relationship among KMC, customer relationship management (CRM), and service quality. Design/methodology/approach – In order to explore on KMC, CRM, and service quality, the questionnaire and partial least square (PLS) techniques were used. Findings – The results indicate that KMC has a positive influence on CRM and service quality; and further, that CRM has a positive influence on service quality. This result also reveals constructive suggestions that allow firms to strengthen their KMC and CRM, as well as enhance their service quality. Research limitations/implications – This research applied a purposive sampling method and obtained a slight...

Effective Customer Relationship Management through Web Services

Abstract: Managing effective relationships with customers has become increasingly important in the era of constrained resources and global competition. The term Customer Relationship Management (CRM) encompasses all methodologies, strategies, tools, and other technology-based capabilities that help an enterprise organize and manage its customer relationships. The focus of CRM is on providing optimal value to customers through pre-sale interactions, sales process, and post-sale interactions. Especially for companies doing business online, either completely or partly, CRM is essential for a long-term survival and success. A major prerequisite to an efficient CRM effort is the complete view of the customer, which in turn requires data — a data that is complete, accurate, current, and in the right format. An equivalent of CRM in the business-to-business arena is Partner Relationship Management (PRM). For successful PRM also what is required is business-to-business application and data integration. This paper presents a...

Online relationship marketing and affective customer commitment – The mediating role of trust

Abstract: The pervasive use of information technology has implications for consumer relationship management among financial services organisations. There is a need for increased understanding of how digital channels might influence the development and maintenance of firm–customer relationships and in particular the role of the Internet upon commitment and trust outcomes. Thus, this research aims to determine the relationship between online relationship marketing practices and affective customer commitment, and how this relationship is mediated by online channel trust. Data were collected from 200 online retail bank customers and Structural Equation Modelling was used to test the impact of five key online relationship marketing practices on affective commitment, and how trust mediates these relationships. We found that advocacy and collaboration have a direct relationship with affective commitment, while trust mediates the influence of engagement and personalisation on affective commitment. The article highlights the significance of trust in technology when using online channels to build customer relationships.

Identifying effective hunters and farmers in the salesforce: a dispositional-situational framework

Abstract: In business-to-business markets, hunting for new customers and farming existing customers are critical to achieve sales goals Although practitioners suggest that salespeople have a preference for either hunting or farming, academic research has yet to examine when and why salespeople become oriented toward hunting or farming, and whether a simultaneous engagement in both (ie, being ambidextrous) is efficient or damaging In Study 1, the authors identify the link between regulatory focus and salesperson hunting and farming orientations In Study 2, they demonstrate that (1) a promotion (prevention) focus is more strongly related to salesperson hunting (farming) orientation than is a prevention (promotion) focus, and (2) ambidextrous salespeople generate higher profits when they are customer oriented In Study 3, the authors show that salesperson expectations about hunting success and the extent to which compensation plans are based on customer acquisition activities can change the direction of the relationship between regulatory focus and salesperson hunting and farming orientations The authors discuss the implications of these findings for research and management of customer acquisition and retention at the salesperson level

Can Marketing Campaigns Induce Multichannel Buying and More Profitable Customers? A Field Experiment

Abstract: One of the most intriguing findings in the multichannel customer management literature is the positive association between multichannel purchasing and customer profitability. The question is whether this finding can be put into action. That is, can a firm develop a marketing campaign to increase multichannel purchasing and hence average customer profitability, and if so what are the key factors that enable success. We design and implement a randomized field experiment to investigate this question. The field experiment tests four marketing campaigns that vary in the communications message and the provision of financial incentives. We find that the multichannel/profitability relationship is actionable. A properly designed marketing campaign increases the number of multichannel customers and increases average customer profitability. That campaign’s message emphasizes the benefits of multichannel shopping but does not rely on financial incentives. Moreover, we use propensity score matching to show that, after...

Customer lifetime value determination based on RFM model

Abstract: – One of the salient challenges in customer-oriented organizations is to recognize, segment and rank customers. Customer segmentation is usually based on customer lifetime value (CLV) measured by three purchase variables: “Recency,” “Frequency” and “Monetary.” However, due to the ambiguity of these variables, using deterministic approach is not appropriate. For tackling this matter, the purpose of this paper is to propose a new method of customer segmentation and ranking by combining fuzzy clustering (as a segmentation method) and fuzzy AHP (as a ranking method). , – First, customers are classified based on purchase variables using fuzzy c-means clustering algorithm. Second, the variables are weighed applying an optimized version of AHP method. Considering the derived weights and customer groups, this paper follows to ranks segments based on CLV. The developed methodology has been implemented for a large IT company in Iran. , – The results show a tremendous capability to the company to evaluate his customers by dividing them into nine ranked segments. The validity of clusters has been submitted. , – For researchers, this study provides a useful literature by combining FCM and an optimized version of fuzzy AHP in order to cover the limitations of previous methodologies. For organizations, this study clarifies the procedure of customer segmentation by which they can improve their marketing activities. , – Managers can consider the proposed CLV calculation methodology for selling the next best services/products to the group of customers that are more valuable, by calculating the entire lifetime value of the customers. , – This study contributes to the process of customer segmentation based on CLV, proposing a new method which covers the limitations of previous customer segmentation methods.

Social Media – A Strategy in Developing Customer Relationship Management☆

Abstract: In this era of new technologies, social media is a must for an organization to remain competitive on the market. Social Media is a tool to manage relationships with customers and keep them closer. This paper aims to analyze how social media supports the development of customer relationship management. It is examined the significant role of social media, the use and the rise of social networks. The use of social media marketing represents a strong factor in developing a CRM strategy. CRM considers the client the center of a business and orientates the marketing policy in this direction. Based on case studies and questionnaires, this article analyzes the necessity of transition from traditional CRM to social CRM. Although social CRM is a relatively new domain, the researchers are very interested in how CRM can emerge with social media. The study emphasizes examples of how companies can benefit from the use of social media, growing sales and profitability, creating advertisements, acquiring new customers, retaining them and make them loyal. Organizations should adapt to the rise of this new trend – social media.

The effect of social media interactions on customer relationship management

Abstract: In recent years, social media have become a popular channel through which customers and companies can interact. However, companies struggle to assess whether their investments in establishing and maintaining brand pages in social media actually meet their high expectations with respect to developing and retaining customers. Based on three empirical studies, the authors explore the role of interactions through corporate social media channels, such as Facebook brand pages, in customer relationship management. The results indicate that social media interactions indeed ease the upselling efforts and reduce the risk of churn. These positive effects offset the observed increases with regard to the number of service requests and the higher overall service cost. Thus, we ultimately find customers who interact with the brand on social media to be more profitable.