جستجوی مقالات مرتبط با کلیدواژه « مدیریت ارتباط با مشتری » در نشریات گروه « مدیریت »

The present research purpose has been dynamic modeling of customer relationship management in e-banking in Sepeh Bank and merged banks, and the conceptual framework identified in the case study was used. The statistical population is the experts in Sepah Bank's customer affairs, and a sample of 14 people has been selected through theoretical sampling method utilizing purposeful techniques. To measure the relationship between dimensions and indicators, fuzzy cognitive map was used in the form of pairwise comparison matrix questionnaire, and the reliability and validity of the questionnaires were confirmed by the test-retest method and the content validity with Lawshe method. For simulation in a certain period of time and measuring the validity of the model, Bidirectional Associative Memory(BAM) Neural Networks have been used in the FCM Expert software. The research findings show that "Customer Relationship Development" is the most central and influential and "Customer Retention" is the most affected dimension, and the mutual influence between "Customer Identification" and "Customer Relationship Development" is significant. Also, the "Customer Attraction" has the greatest impact on the "Customer Retention & Customer Relationship Development" and the "Customer Reach and Acquisition" has the greatest impact on the "Customer Attraction & Customer Retention". Based on these results, it is recommended that Sepah Bank managers pay special attention to customer attraction through branding and the implementation of advertising campaigns at contact points, and despite the low impact of the "Customer Relationship Review", its significant impact on the most central dimension, i.e. "Customer Relationship Development" should not be neglected.

With the development of digitalization of marketing activities, marketing professionals increasingly use social media as a strategic tool for effective interaction with customers and stakeholders. Experience shows that firms should have a social media presence for their activities, because the strategic use of social media can be increasingly effective to increase the firm's competitiveness, create a convenient and low-cost user experience, and improve the well-being of customers. On the other hand, the potential gains of social media technologies are evident in business markets and customers are more informed. Also, growing evidence shows that social media can be used strategically to facilitate effective communication with customers, customer retention, and improve firm performance against competitors. Accordingly, social media use is a very good predictor of improved communication and performance development. Finally, with the changes and developments of the digital space and the acceleration of activities, most firms have turned to social media to improve their market share. Based on this, the aim of this study is to investigate the mediating role of market penetration strategy and customer relationship management in the relationship between social media use and market share of knowledge-based firms.

This research is a quantitative study, which is considered an applied study due to its nature and results. The statistical population of this research includes knowledge-based firms active in the field of information technology, communication and computer software in the Iran country. The number of these firms in the country is equal to 1891 companies according to the statistics of the vice-chancellor for the development of knowledge-based companies. The data collection of this article was done by means of a questionnaire and in the form of a 5-level Likert spectrum from the statistical population. It should be mentioned that because managing directors and senior managers of firms have more control over firm policies, they were used to fill out the research questionnaire. Also, in order to be surer of the research questionnaire, validity and reliability processes were checked and the necessary corrections were applied with the opinions of experts, and the reliability of the variables was reported and confirmed. In this study, a stratified random sampling method was used from the studied population, and according to the number of the statistical population, Cochran's formula was used to estimate the sample. Also, by collecting 218 data from the statistical population, analysis was done on the subject of the research. It should be noted that several hypotheses were presented to establish the relationship between variables, which were analyzed by structural equation modeling and SPSS and Amos tools.

The outputs show that the social media use has a positive effect on the market penetration strategy. Also, the social media use has a positive effect on customer relationship management. On the other hand, social media use has a direct and significant effect on the market share of knowledge-based firms. Another finding of the study is related to the mediating role of penetration strategy in the market. The result shows that the market penetration strategy mediates the relationship between the social media use and the market share of knowledge-based firms. Finally, the results show that the mediating role of customer relationship management in the relationship between social media use and market share of knowledge-based firms is significant.

Nowadays, with the advent of the digital space, entering different markets became smoother for all types of firms, because it became possible to reach many customers in different places with little cost and little time. On the other hand, in order for firms to maintain their survival in these complex conditions, they need to access an acceptable share of resources and customers in their industry so that they can achieve a good market share and continue their existence. Based on this, the present study acted through the strategic social media use to improve the market share of knowledge-based firms. On the other hand, in order to realize this importance, we took help from market influence variables and customer relationship management to achieve this goal in the relationship between independent and dependent variables, which had not been noticed by researchers in previous studies. Therefore, the aim of the present study was to examine the mediating role of market penetration and customer relationship management in the relationship between the social media use and the market share of knowledge-based firms active in the field of information technology, communications and computer software. For this reason, the contribution of this study in increasing the subject literature and presenting a new model in line with the research variables and the target population is significant. The results showed that the mediating role of market penetration strategy is significant. In this regard, it can be stated that knowledge-based firms can implement their market penetration strategy by investing in social media platforms and activities with the aim of achieving the desired market share. Therefore, knowledge-based firms active in the field of information technologies, communication and computer software can customize their market penetration strategy for social media in order to achieve a significant market share. On the other hand, the present study showed that customer relationship management is a mediating variable in the relationship between the social media use and the market share of knowledge-based firms active in the field of information technologies, communications and computer software. This finding shows that improving the market share through the implementation of the strategy of using social media is not done in a direct way and requires improving the capabilities of managing the relationship with customers in the social media space. Based on this, managers of these firms should prepare their employees for online and digital environments and strengthen the capabilities and skills of online communication with customers in employees. Finally, based on the results, this research has provided practical suggestions for the statistical community.

The use of new marketing techniques in today's businesses is highly needed by all organizations. One of the important issues in the field of customer retention is the customer's lifetime value. Customer lifetime value has a great impact on optimizing the performance of companies, including insurance companies. The purpose of this research is to identify the influencing factors on increasing the customer lifetime value of insurance companies. This research is a type of mixed research with a qualitative and quantitative approach, which is a survey study in terms of its purpose, application, and in terms of data collection. The research population includes managers, experts, and university professors from insurance companies and organizations. who were selected using the snowball sampling method. In the qualitative part, the data collection tool was an interview, and in the quantitative part, a questionnaire was used to identify the categories, and a semi-structured interview was used, and a questionnaire was used to validate the model. In the qualitative part of the data analysis method, the data theory approach was based on the Strauss and Corbin method, which was compiled using MAXQDA software and using the coding method, and in the quantitative part, the analysis method was based on Kendall's correlation test. In order to examine the validity of the research in the qualitative part, the Cressol model was used along with content validity and intra-coder and inter-coder reliability, and in the quantitative part, in order to test the validity of the research, content validity and retest validity were used. The findings of the study identify 9 causal factors, 3 strategic factors, 4 intervening factors, and 3 contextual factors that contribute to increasing customer lifetime value in the insurance industry. The conclusion of the research is the presentation of a model that includes causal, contextual, and intervening conditions, along with strategies to increase customer lifetime value and their consequences in the insurance industry.

Considering the changes that have happened in recent years in the business process, attention to the category of business intelligence has become an important issue. Therefore, the present study examines the effect of the competence dimensions of business intelligence on marketing performance, considering the mediating role of customer relationship management in tourism businesses.

The current research is a descriptive survey regarding the applied purpose. The study's statistical population comprised experts and marketing managers of tourism companies in Tehran. In order to collect data, 300 questionnaires were distributed online and face-to-face using the non-probability sampling method, and 253 questionnaires were analyzed by removing distorted and indifferent questionnaires. The structural equation modeling method and SPSS 26 and Smart PLS 3 software were used for data analysis.

The findings showed that the competency of business intelligence has a positive and significant effect on marketing performance, and customer relationship management plays a mediating role in this relationship. This shows that one of the ways to improve marketing performance and create a sustainable competitive advantage for managers is to use business intelligence.Originality/Value: In today's highly competitive world, the quality and timeliness of business information in organizations determine the difference between survival and bankruptcy. Also, the great importance of business intelligence and the critical role that this concept can have in improving the marketing performance of business organizations have been less discussed. Therefore, the results of the current research can improve tourism companies' marketing performance by applying business intelligence.

The use of digital marketing as a communication and sales channel has led to the need and use of customer relationship management (CRM) systems based on artificial intelligence for the proper management of company information.

The purpose of this research is to design a business-to-business marketing implementation model with an emphasis on customer relationship management based on artificial intelligence

This study is a type of mixed research with a qualitative-quantitative approach, which is a survey study in terms of its purpose, application, and data collection. In the qualitative part of the data collection tool, a semi-structured interview with 18 specialists and experts in the field of business-to-business digital marketing and university professors who were selected by snowball method. The quantitative part includes a targeted sampling with 35 digital marketing experts and data gathered through a questionnaire. In the qualitative part of the data analysis method, the Grounded theory approach is used based on the Strauss and Corbin method, which is compiled using the MAXQDA software and the coding method. In the quantitative part, the validation method is based on the Kendall correlation test.

The findings of the research (6 general categories, 25 subcategories, and 173 main concepts) include presenting a model that includes causal, contextual, and intervening conditions, along with the introduction of the central phenomenon and the presentation of strategies for implementing business-to-business digital marketing and identifying its consequences.

Company managers should pay attention to factors such as customer relationship management based on artificial intelligence (analytical, collaborative, and operational) to implement digital marketing from business to business and try to weaken the inhibiting factors and strengthen the positive and influential factors. 

The present study investigates the impact of customer relationship management (CRM) as mediating variable on the relationship between customer knowledge management (CKM) and new product development (NPD). The research is applied in terms of purpose and descriptive-survey in nature. The statistical population of the research is the active companies of Khuzestan and West Azarbaijan province, among which 169 companies were selected as a sample based on Morgan Table, which sampling has been available. The data collection tool was a standard questionnaire which has taken of literature. The dimensions of customer knowledge management variable, including knowledge about the customer, from the customer, and for the customer, respectively, have been measured based on the scales of Buchnoska (2011), Moosakhani, Haghighi, and Torkzadeh (2012), and Shami Zanjani and Najafloo (2011). The dimensions of customer relationship management variable including information, value, and multi-channel communication have been measured according to the scales of Kohli and Jaworski (1990), Jarvis, et al. (2003), and Jindal, et al. (2007). Also, New Product Development variable has been measured based on the scale of Cooper and Kleinschmidt (1995). To analyze the data, partial least squares method and SmartPLS software were used. Data reliability examination using Cronbach's alpha coefficient and composite reliability test showed that the lowest value of Cronbach's alpha is related to the variable of customer knowledge with a value of 0.775 and the lowest value of composite reliability is related to the variable of customer knowledge with a value of 0.843. Therefore, the reliability of all variables was confirmed. The results showed that the path coefficient of CKM-CRM and CKM-NPD has been 0.833 and 0.612, respectively, the path coefficient of CRM-NPD has been 0.774, and the mediating effect of CRM on the CKM-NPD relationship has been 0.648. So all cases are significant at the 5% error level. These findings have several important scientific and practical implications, and therefore it is suggested that companies pay special attention to the importance of customer relationship management in activating knowledge management talent and new product development.

The aim of this research is to identify the dimensions and components of acceptance of social systems of customer relationship management by professional users using Web 2.0 technology. The current research is applicable in terms of nature, qualitative in terms of implementation method, and of descriptive and thematic kind. The statistical population of this research was made up of 15 university professors in the fields of management, business and IT along with managers of digital business companies, selected by non-random sampling method. The criteria for selecting people are having a doctorate degree with more than 10 years of experience in digital businesses, having time, interest and ability to take part in interviews (a semi-structured) and fill the questionnaires. Also, MAXQDA 2020 software was used in data analysis. The identified factors were extracted in the form of 40 indicators, 8 components and 3 dimensions. Components and indicators of dimensions and components of acceptance of customer relationship management social systems included three dimensions; organizational, customer, and technological; which organizational dimension has three components (manpower, organizational culture, organizational structure), customer dimension includes three components (value creation, customer satisfaction, expectation of performance), and technologically has two components (social networks, content production).

Customer relationship management is a strategic necessity in all organizations. The attitude and approach of many organizations to customer relationship management is from the point of view of technology. Customer relationship management is a competitive advantage for organizations. Today, companies and organizations are forced to include issues related to environmental protection in their activities and even in their marketing in order to satisfy the needs of customers and communicate more with them, and act on social responsibility and protect the rights of consumers. to use Green marketing refers to those activities and products that develop and improve pricing, promotion and distribution of goods that do not harm the environment. Therefore, organizations have tried to outdo each other by planning and implementing environmental protection activities in sync with the needs of people, because traditional marketing that overemphasizes the demands of customers and social welfare and environmental issues. It did not consider biology, it had lost its efficiency. Currently, issues such as dynamism and intensity of competition, increased concerns and awareness of consumers regarding the environment, as well as government regulations have caused commercial organizations to pay special attention to things such as the physical and mental health of consumers and the cleanliness of the environment. This issue encourages the use of green marketing. In this research, we intend to first examine the key concepts of the project and then we will review the research done in this regard, then we will examine the role of green marketing in customer relationship management.

Working on Customer Relationship Management (CRM) has an enormous impact on the activities in the tourism industry. But the success rate in CRM system implementation is too low, and failure has been seen in more than 70% of these projects. The purpose of this study is to provide a model for the successful implementation of a customer relationship management system in the tourism industry. This applied research is exploratory in nature and uses the grounded theory approach to study 35 tourism companies over a year. CRM project managers in these organizations participated in interviews, and their documents have been observed and analyzed. The results showed that successful CRM implementation in the tourism industry requires management support, organizational culture and belonging, and appropriate corporate literacy. Information Technology (IT) infrastructure and budget constraints are barriers to the deployment project. Integrating organization processes, training managers and staff, encouraging and punishing employees, strategic alignment, providing the technical infrastructure, providing sufficient customer recognition, and suitable budget development were identified as the prescriptive actions (or strategies) for successful implementation of CRM systems.

The present research was conducted with the aim of investigating the impact of innovative behavior on organizational performance by explaining the mediating role of customer relationship management and competitive advantage in the customers of Snowa refrigerator in Arak city. The method used in this research was a descriptive-survey method and applied in terms of purpose and from the field branch. The statistical population studied was the customers of Snowa refrigerator in the city of Arak, whose number is one of the unlimited communities. Using Cochran's sample size formula, 384 people were selected as a sample by simple random sampling. In this research, the standard questionnaires of Kanter's innovative behavior (1988), Hersey and Goldsmith's organizational performance (1981), Abbasi's customer relationship management (2008) and Lee et al.'s competitive advantage (2006) were used. In order to check the reliability of the questionnaires, Cronbach's alpha was calculated, which indicated the satisfactory reliability of the questionnaires. In order to analyze the data, descriptive statistics including: mean, standard deviation, minimum and maximum score, and structural equations were used in the inferential statistics section using SPSS version 21 and PLS3 software. The results indicate that innovative behavior has a positive and direct effect on organizational performance by explaining the mediating role of customer relationship management and competitive advantage in the customers of Snowa refrigerator in Arak city.

Customer Retention and maintaining customer relationships and preventing customers from Churn is one of the most important tasks of organizations in today's highly competitive markets. In this study, the issue of customer churn and customer retention strategies have been investigated. These issues have been studied through systematic literature review and from different angles such as the field of organization, degree of individualization of customer relationship management, customer segmentation, and selection of key customers, employee engagement and evaluation. In addition, a model based on deep learning networks has been used to predict customer churn. As a result, a conceptual framework and model is created based on the existing literature in this field and then combined with the customer churn prediction model using deep learning networks. The results show that the use of deep learning in predicting customer churn is a very effective and efficient way to solve the problem of customer retention and customer churn. This approach is not only able to accurately predict which of the organization's customers are turning away from the organization and disconnecting from the organization, but also can accurately identify the factors and parameters affecting customer churn and bring very valuable insight for the organization.

Nowadays, computers have affected all aspects of human life. Basic business elements such as customers' personal information are all stored in computers, and this intangible information includes a large proportion of corporate assets. E-commerce with a customer-oriented approach is defined as technology-oriented relationship marketing, which is used by companies with the intention of maintaining customer relations owing to its significant advantages over the traditional e-commerce. Iranian businesses, despite facing tough competition in domestic and foreign markets, have realized the importance of customer retention, but they are not as familiar with customer relationship management capabilities as they should be, nor do they know about e-commerce tools. If the problem is solved, the way will be paved for the successful implementation of CRM. This gap has led to economic inefficiency and the ultimate shutdown of many businesses. The main problems are the lack of managers’ understanding of the importance of communication with the customer, the use of some outdated marketing models to establish this relationship, and the lack of e-commerce capacity to implement CRM. The main purpose of this study is to identify the components of e-commerce and CRM and explain the relationship between them in the form of a comprehensive model. To this end, at first, the components of these two variables were identified using the meta-synthesis and indexing methods, and meta-synthesis models of research were presented. Then, using the interpretive structural modeling, a comprehensive research model was introduced to show the relationship between the mentioned components. The present study is exploratory mixed research in terms of method. Meta-synthesis is applied in the qualitative part, and in the qualitative-quantitative part is based on ISM. The meta-synthesis focuses on qualitative studies and their in-depth analysis with the aim of deeper understanding. ISM is technically appropriate for analyzing the effect of one element on other elements. In terms of purpose, the meta-synthesis section is an applied research work, and it is a qualitative study in terms of implementation. The ISM part is an applied research work in terms of purpose and a qualitative study in terms of implementation. Also, this method is descriptive-survey in terms of nature and partly developmental in terms of results. According to Popper's Foresight Diamond model, it is one of the semi-quantitative research methods. In meta-synthesis, library studies and web browsing were conducted to collect data. The ISM section was based on a researcher-made questionnaire. Open coding method was used for data analysis in the meta-synthesis, and Mic Mac analysis was done for ISM. The statistical population in the meta-synthesis section was the scientific articles in the field of e-commerce and CRM from 1996 to 2017 for Latin articles and from 2001 to 2017 for Persian articles. In the meta-synthesis, the criterion for sample size was theoretical saturation. In the ISM, the statistical population included 83 experts from the companies approved by the Electronic Commerce Development Center of the Ministry of Industry, Mines and Trade, which have the symbol of e-trust and operate in the field of e-commerce. The statistical sample in this method consisted of 15 experts from the mentioned companies. The sampling method was snowball sampling, and the criterion for sample size was the theoretical saturation. In the Meta-synthesis section and in the first stage of the article evaluation, there existed 52 articles in the field of e-commerce and 60 articles in the field of CRM. In the second stage, there were 45 articles in the field of e-commerce and 47 in the field of CRM. Finally, in the third stage, 29 articles were accepted in the field of e-commerce and 27 in the field of CRM. As an innovation, the indexing method was used, and new sub-fields were added to the meta-synthesis models. In the meta-synthesis E-commerce model, customer trust and satisfaction as well as the development, application and success of e-commerce were the three main components, each of which had several sub-components. In the meta-synthesis model of CRM, the key factors of success, customer satisfaction and electronic customer relationship management were the three main components with a number of sub-components. In the ISM part, according to the dependence power and the driving power, the research components were analyzed and placed in four areas in the form of Mic Mac diagrams. E-CRM was ranked in the third area as an influential variable. The components of the development, application and success of e-commerce were in the second area; they were called dependent variables. Customer trust and satisfaction in e-commerce and the key factors of success and customer satisfaction in CRM in the fourth area were considered as a linkage variables. No component was located in the autonomous region. E-CRM plays a pivotal role and is somehow related to other components through primary or secondary relationships. It directly contributes to customer satisfaction and serves as a key factor in the success of CRM. The pivotal role of this component is owing to its ability to use the Internet to attract new customers and the ability to communicate continuously with previous customers. Therefore, managers should pay good attention to this component and make it operational. This new approach can increase electronic customer loyalty to the company and is considered as a potential competitive advantage. The main limitation of the meta-synthesis approach was found to be the limited time period for reviewing articles, which can be improved by expanding the research results. In future studies, in addition to articles, authoritative books and scientific reports can be used. In the ISM, the content relationships between the components depend on the knowledge of the experts, which may affect the results. It is recommended to be used in future studies along with other methods such as analytical network processes.

Agricultural tourism is one of the newest attractions of the tourism industry. This type of tour includes a combination of agriculture, providing services and products with unique tourism experience in agricultural areas. On the other hand, in today's competitive world, attracting customers to the organization ensures the survival of the organization. With the emergence of the phenomenon of privatization and exit from monopoly, competition among organizations will increase and the survival of organizations and industries will not be possible without the existence and implementation of an efficient customer relationship management system. In this research, by presenting a conceptual model, the role of customer relationship management in the development of agricultural tourism is investigated. This research is applied in terms of purpose and in that grape harvest festival which can be a clear example for agricultural tourism in Urmia is studied as a case study. The sample size was determined based on Cochran's formula 108 and data collection was done by questionnaire. In order to analyze the collected information, the structural equation modeling method was used with Smart PLS software. The results confirm all research hypotheses and customer relationship management has a significant impact on agricultural tourism

The purpose of this study was to explain the effect of customer knowledge on improving the quality of services in the hotel industry with the mediating role of customer relationship management. The type of research was applied in terms of purpose and descriptive-correlational in terms of the nature of the method.The statistical population of the study was the customers of Sarein hotels. Simple random sampling method was used for sampling and Cochran's formula was used to select the sample size. Due to the infinity of the statistical population, the sample size was 384 people. Collection of required data using three standard questionnaires, customer knowledge (Tseng & HongWu, 2014); Customer relationship management (Abbasi,2011) and service quality questionnaire (Stefano et al.,2015) were performed. Validity was assessed using confirmatory factor analysis and reliability was assessed by Cronbach's alpha. Data analysis was performed using structural equation modeling approach using SPSS and PLS software. According to the research findings, customer knowledge has a positive and significant effect on the quality of services in the hotel industry and between the dimensions of customer knowledge, the dimension of effective communication is the most effective dimension on service quality. Customer relationship management also plays a mediating role between customer knowledge and service quality of the hotel industry, The findings of this study can be effective in moving the hotel industry to pay more attention to customer knowledge and improve the quality of services in the hotel industry.

Customer relationship management provides the basis for customer optimal communication, customer loyalty and customer retention. This requires the design of customer-based strategies, the proper implementation and applying of technology, employee empowerment and increasing the level of customers knowledge. Given the advances in e-banking and the reduction of face-to-face contact points, the use of business intelligence tools to effectively use large volumes of customer information also seems necessary. The purpose of present study is to provide a conceptual framework for customer relationship management in electronic banking using business intelligence tools in Sepah Bank and merged banks. For this purpose, a qualitative research has been conducted and first, by reviewing the studies, the initial framework has been identified and then, Theme Analysis has been used for its development in electronic banking. The research population is 7 experts of case study. Semi-structured interviews were used to collect data and credibility and confirmability were used to assess the validity of the results. After analyzing the data, the customer relationship management framework in e-banking is classified into 6 dimensions, 16 components and 35 indicators. The main dimensions of which are Customer reach and acquisition, Customer identification, Customer attraction, Customer relationship development, Customer retention and customer relationship review.

Success in customer relationship typically depends on increasing knowledge management. As the hiring of a scientist in customer relationship management becomes more prominent because there is so much information about drugs, their properties and their behavior. In such cases, use efficient algorithms and techniques to analyze this data is essential. The purpose of this study is to provide a model for customer relationship management (CRM) in discount chain stores through the use of the Internet of Things and Big Data. The data analysis method is a detailed construction modeling method. In this research, in order to fill in the questionnaires, the opinions of 20 experts in this field have been used. According to the interpretive structural model, the first level of the hierarchy belongs to “Customer Relationship Management Success (3)”, the second level of the hierarchy belongs to “Custom Marketing Advertising (1) and Customer Improvement (2)” and the third level of the hierarchy belongs to “Pricing strategy (3)” can be, which means that these variables are affected by other variables. The most influential variable is “real-time analysis” (4). The results can be a good model for the country's chain stores to better manage customer relationships and gain a competitive advantage.

The purpose of this study is to present a sales model of new products in the country's tire industry through relational marketing methods. Since in this applied research, the main goal is not only scientific discovery, but also to test and study the application of knowledge, so the method of this research is applied in terms of purpose and has been done by exploratory method. The data collection method is quantitative and the data collection tool is a questionnaire. Therefore, 375 people participated in this study. The collected data were analyzed by descriptive and inferential methods through SPSS 16 and Smart PLS software. After conducting the research, the results showed that: systematicity, technology orientation, design orientation, market orientation, use of resources, the basis of efforts for new goods, conceptualization of new goods, and finally new product management; Under the heading of market components of selling new goods by one-to-one marketing method; Approved. Model fit tests showed the validity of the model.

The use of artificial intelligence in customer relationship management as the core of marketing activities has been considered by today's businesses. The researchers first extracted the concepts by reviewing the studies and previous researches, but due to the non-relevance of some of the extracted factors to the current situation of Iranian banks, they were used by experts using the interview method and Delphi. The research method is a mixture of qualitative and quantitative and is considered developmental and applied in terms of purpose. The components were first identified through interviews with 21 experts. Then a model was developed that includes 197 indicators and 21 concepts of customer relationship management based on big data. In three stages, in order to approve the initial model, experts and managers of the western banks iran (West Azerbaijan, Kurdistan, Kermanshah and Hamadan provinces) were consulted, and finally the model was approved. Based on the obtained results, banks with data and big data algorithms have used fifteen strategies in three stages of relationship start, relationship maintenance and relationship end, and consequences such as revenue increase, cost reduction, personal and dynamic pricing, advertising targeting. , Improved profitability, development of new products and services, allocation of smart resources and assisting managers in decision making. Also, management issues and challenges and ethical issues and privacy affect these consequences.

Knowing customers and identifying profitable services is of great importance due to the diversity of bank customers and the variety of services in the country's banking system. Customer relationship management is now the core of the business world, today the electronic portals of banks using various information exchange networks such as Satna, Paya, Chakavak, Sayad and. . . They are connected to each other. The most important interbank network used in Iran is Shetab network.In this study, data mining techniques were used to classify and rank customers in the Shetab network using an improved RFM-based data mining model so that banks could analyze and evaluate their customers' behavior in this network and formulate Deal with effective policies in dealing with customers.For this purpose, the required data were extracted from the bank card switch database and the required analyzes and data mining operations were performed on it by CRISP method. This data is available in the database of the Welfare Bank and was extracted from the database of the institution using DML commands. Also, in order to review similar studies and increase information through library and internet studies, information related to the model was collected. Finally, R+FMW presented a model for clustering bank customers and their transactions. The results showed that the developed R+FMW model has a higher accuracy than the basic RFM model and by using this model, banks can identify customers active in the interbank exchange network (acceleration) and expensive customers and communication channels. Recognize in terms of fees and demographic information