Investigating customer relationship management and evaluating the impact of data mining in CRM

  • سال انتشار: 1403
  • محل انتشار: بیست و چهارمین کنفرانس بین المللی فناوری اطلاعات، کامپیوتر و مخابرات
  • کد COI اختصاصی: ITCT24_042
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 125
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نویسندگان

Mohammad Kazem Beshkani

Master's degree in business management-e-commerce, Hakim Nizami Qochan Higher Education

Amir Shahraieni

Department of management,payame Noor University,Tehran,Iran

Masomeh Laghaie Tabar

Department of Management Gilan University

چکیده

Customer relationship management is all the strategies, processes and technologies that create,maintain, develop and optimize long-term and valuable relationships between the customer andthe company and cause customer retention. Customer relationship management is not a new termand in the past it was very famous among businesses as people management. But the methods ofimplementing customer relationship management in today's environment are different. Acustomer relationship management system can be simple or complex depending on the nature ofyour business. Data warehouse tools and technologies, data mining and other customerrelationship management techniques are methods that have provided new opportunities forbusiness. In fact, the product-oriented view has given its place to the customer-oriented one.Therefore, by collecting customer data and making decisions based on the patterns extractedfrom the hidden relationships between the data by means of data mining tools, it is possible tofulfill the customer's desire. CRM deals with new ways of interacting with customers thatpromises a higher return on investment for businesses by improving customer-oriented processessuch as sales, marketing and customer service. Data mining techniques for automating thediscovery of related patterns in databases help hotels to establish personal and profitablerelationships with customers by identifying and predicting customer needs throughout thecustomer life cycle.

کلیدواژه ها

Customer relationship management, data mining, customer life cycle,CRM

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