Customer Relationship Management Features Research Articles

Mediating Role of Customer Relationship Management between Buying Behavior and Critical Risk Factors via Digital Buying

Purpose: To examine the mediating effect of Customer Relationship Management (CRM) amid Digital Buying Behaviour (DBB) and Risk Factors (RF). Methods: The structured questionnaire was adopted to analyse critical factors of DBB, RF and CRM. The instrument was designed and validated with the help of exploratory factor analysis and confirmed the items by confirmatory factor analysis. The model fitness is verified. The reliability of the scale was tested along with CR. The field testing is done to remove ambiguity. The nativity changes were incorporated to align the current study. The responses were collected using convenience sampling method through the e-mail survey and 410 valid responses (digital consumers) considered. The data were collected during August – November 2022. Quantitative approach is used to examine both directions of the considered variables. First, the direct effect of DBB on RF is examined. Secondly, the direct effect of CRM is studied. Further, mediating effect of CRM in relationship amid DBB and RF is established. Findings: The DBB is significant and directly connected with RF (b = 0.952, p < .001), CRM is significant and positively allied with RF (b = 0.471, p < .001). DBB is significant and positively related to CRM (b = 0.779, p < 0.001), after removal of mediating variable (CRM), b weight of DBB is reduced from 0.952 to 0.703. Sobel test is steered to confirm the significance of the mediation effect of CRM, test statistic (z= 3.09, p <.001). Thus, CRM act as a partial mediator amid DBB and RF. Novelty: The present study integrates DBB, RF and CRM features associated in digital buying in solitary manner unlike sliced approach. The study of CRM role especially in digital buying is a uniqueness of the present research. Further, studying the partial mediating effect of CRM amid DBB and RF itself is a new attempt. Keywords: Digital Buying Behaviour (DBB); Risk Factors (RF); Customer Relationship Management (CRM); Mediating Effect; Confirmatory Factors Analysis; Sobel Test

Perancangan Website dengan Menerapkan Customer Relationship Management (CRM)

With the technology that is currently developing, especially in the online sales business, an online sales website is designed on the Wishy Store Distro by designing customer relationship management in attracting customer shopping interest in the products sold by providing and supporting the best service to customers. . The customer relationship management features that are presented and designed include, among others, customers can get a discount for a certain amount of purchase, customers can get free shipping for a certain number of purchases, customers can contact the Wishy Store Distro admin to ask about products for returns for shipping errors or defects. products, customers can create and send statuses about products being sold and can give likes to fellow customers or other users who have posted statuses on the feed page. The design of Customer Relationship Management on the Wishy Store Distro uses PHP as the programming language with MySQL as the database, Sublime Text 3 and Notepad ++ as the script editor.

A Time-Frequency Based Suspicious Activity Detection for Anti-Money Laundering

Money laundering is the crucial mechanism utilized by criminals to inject proceeds of crime into the financial system. The primary responsibility of the detection of suspicious activity related to money laundering is with the financial institutions. Most of the current systems in these institutions are rule-based and ineffective (over 90 % false positives). The available data science-based anti-money laundering (AML) models to replace the existing rule-based systems work on customer relationship management (CRM) features and time characteristics of transaction behaviour. Due to thousands of possible account features, customer features, and their combinations, it is challenging to perform feature engineering to achieve reasonable accuracy. Aiming to improve the detection performance of suspicious transaction monitoring systems for AML systems, in this article, we introduce a novel feature set based on time-frequency analysis, that uses 2-D representations of financial transactions. Random forest is utilized as a machine learning method, and simulated annealing is adopted for hyperparameter tuning. The designed algorithm is tested on real banking data, proving the results’ efficacy in practically relevant environments. It is shown that the time-frequency characteristics are discriminatory features for suspicious and non-suspicious entities. Therefore, these features substantially improve the area under curve results (over 1%) of the existing data science-based transaction monitoring systems. Using time-frequency features alone, a false positive rate of 14.9% has been achieved, with an F-score of 59.05%. When combined with transaction and CRM features, the false positive rate is 11.85%, and the F-Score is improved to 74.06%.

Customer relationship management technology: bridging the gap between marketing education and practice

The recent machine learning and analytics advances in customer relationship management (CRM) technologies place new demands on marketing education and practitioners to develop the skills needed to use the technology. Compounding the issue, research on the use of technology in sales curriculum is underdeveloped. In a comprehensive review of the sales education literature, one study identified that only six articles on sales technology were published in major marketing education journals from 1979 to 2013. In an effort to bridge the gap between critical industry competencies and marketing curriculum, understanding the impact of technology use and training is important for educational planning and student development. Using a survey of 82 salespeople in the United States, the current study empirically evaluates how use of technologically advanced CRM features influences self-perception of CRM knowledge, the perception that additional technology training would be beneficial, and adaptive selling performance of sales practitioners. A majority of survey respondents in the current study cited a need for college students to receive increased exposure to advanced CRM technology training and skill development. We propose an experiential learning approach to teach marketing college students advanced CRM features to help them bolster their effectiveness and value in the workplace.

A TIME FREQUENCY BASED SUSPICIOUS ACTIVITY DETECTION FOR ANTIMONEY LAUNDERING

Money laundering is the crucial mechanism utilized by criminals to inject proceeds of crime into the financial system. The primary responsibility of the detection of suspicious activity related to money laundering is with the financial institutions. Most of the current systems in these institutions are rule-based and ineffective (over 90 % false positives). The available data science-based anti-money laundering (AML) models to replace the existing rule-based systems work on customer relationship management (CRM) features and time characteristics of transaction behaviour. Due to thousands of possible account features, customer features, and their combinations, it is challenging to perform feature engineering to achieve reasonable accuracy. Aiming to improve the detection performance of suspicious transaction monitoring systems for AML systems, in this article, we introduce a novel feature set based on time-frequency analysis, that uses 2-D representations of financial transactions. Random forest is utilized as a machine learning method, and simulated annealing is adopted for hyperparameter tuning. The designed algorithm is tested on real banking data, proving the results’ efficacy in practically relevant environments. It is shown that the time-frequency characteristics are discriminatory features for suspicious and non-suspicious entities. Therefore, these features substantially improve the area under curve results (over 1%) of the existing data science-based transaction monitoring systems. Using time-frequency features alone, a false positive rate of 14.9% has been achieved, with an F-score of 59.05%. When combined with transaction and CRM features, the false positive rate is 11.85%, and the F-Score is improved to 74.06%.

Взаимоотношения с потребителем: подход менеджмента качества

This article is devoted to research of features of customer relationship management from the standpoint of quality management. The main stages of the process of attracting and retaining consumers are identified. The article presents the basics of building a full relationship with consumers. Implementation of the requirements and recommendations of ISO 9000 series in terms of processes associated with the consumers is considered. The comparative characteristic of existing methods of customer relationship management is given.

The adoption of customer relationship management (CRM) technology in SMEs

Purpose – The aim of this paper is to use an innovation decision process to examine CRM technology adoption in small to medium-sized enterprises and its intrinsic link to the nature of the organisation and the individuals within it. Design/methodology/approach – A survey was administered to SMEs in Southern California to measure the organisational characteristics, specifically management characteristics, employee characteristics, IT resources and firm characteristics. The perception of CRM, decision to adopt CRM, and extent of CRM implementation were also measured. Previously validated instruments were used where required. The data were analysed using multivariate and logistic regression. Findings – The results indicate that management's innovativeness affects the firm's perception of CRM systems, but age, education and gender do not. The decision to implement a CRM system is influenced by management's perception of CRM, employee involvement, the firm's size, its perceived market position, but not the industry sector. However, the number and types of CRM features implemented are affected by management's perception of CRM, employee involvement, the firm's size, the industry sector, but not its perceived market position. Research limitations/implications – This study is specific to Southern California and the sample size is relatively small, although sufficient for this analysis. The study should be replicated in more diverse geographic settings with a larger sample. Practical implications – The study provides evidence of the need for management to be supportive of innovation and technology, to evaluate the available resources (IT knowledge, skills, infrastructure) within the organisation, to recognise the importance of employees' contributions, and to be aware of the features appropriate to their company's size and industry sector before undertaking CRM technology adoption. Originality/value – The findings from this study extend the understanding of CRM adoption in SMEs and help in building a greater understanding of the factors associated with such adoption. It will be of great value to owners/managers in SMEs who are considering adopting CRM.

Adapted customer relationship management implementation framework: facilitating value creation in nursing homes

This paper proposes a framework to support customer relationship management (CRM) implementation in nursing homes. This work critically considers existing studies, which conducted in-depth questionnaires to identify critical CRM features (termed value-characteristics) that were identified as potentially adding the most value to nursing homes if implemented. Although the existing research proposed an implementation framework, summary of, and inconsistent inclusion of value-characteristics, limits the practical use of this contribution during implementation. In this paper we adapt the originally proposed framework to correct perceived deficiencies. We link the value characteristics to operational, analytical, strategic and/or collaborative CRM solution types, to allow consideration in context of practical implementation solutions. The outcome of this paper shows that, practically, a ‘one solution meets all characteristic’ approach to CRM implementation within nursing homes is inappropriate. Our framework, however, supports implementers in identifying how value can be gained when implementing a specific CRM solution within nursing homes; which subsequently supports project management and expectation management.

CRM 2.0 within E-Health Systems: Towards Achieving Health Literacy &amp; Customer Satisfaction

Customer Relationship Management (CRM) within healthcare organization can be viewed as a strategy to attract new customers and retaining them throughout their entire lifetime of relationships. At the same time, the advancement of Web technology known as Web 2.0 plays a significant part in the CRM transition which drives social change that impacts all institutions including business and healthcare organizations. This new paradigm has been named as Social CRM or CRM 2.0 because it is based on Web 2.0. We conducted survey to examine the features of CRM 2.0 in healthcare scenario to the customer in Brunei Darussalam. We draw the conclusion that the CRM 2.0 in healthcare technologies has brought a possibility to extend the services of e-health by enabling patients, patients families, and community at large to participate more actively in the process of health education; it helps improve health literacy through empowerment, social networking process, and online health educator. This paper is based on our works presented at ICID 2011.

Critical issues in CRM adoption and implementation

Customer relationship management (CRM) is a fast growing category of application software. CRM is gaining interest because of its focus on the customer and thus its potential for increasing revenue. It enhances the ability of a firm to compete and to retain key customers. Furthermore, given the rapid growth of e-business applications and the increasing need to sell to and support customers through the web, CRM provides a focal point for all customer-facing activities. This review of CRM product capabilities and key CRM vendors identifies three distinct categories of CRM vendors and finds that they are attempting to offer a rich or full set of CRM features and are rapidly integrating web access into their products. The study proposes a model to aid in the selection of CRM products and the evaluation of CRM vendors.