مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

1,359
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

0
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

PREDICTING CUSTOMER LIFETIME VALUE BASED ON FINANCIAL AND DEMOGRAPHIC CHARACTERISTICS USING GMDH NEURAL NETWORK CASE STUDY: INDIVIDUAL CUSTOMERS OF A PRIVATE BANK OF IRAN

Pages

  833-860

Abstract

 The role of CUSTOMER RELATIONSHIP MANAGEMENT as a strategic tool in development of manufacturing and service organizations, and also acquisition and retention customers in competitive industries, is undeniable. Identification, valuation and classification of customers and allocating resources to them based on their value for organization are the main concerns in CUSTOMER RELATIONSHIP MANAGEMENT. One of the most important tool in this direction, is calculating and predicting CUSTOMER LIFETIME VALUE (CLV). “CLV” is a value which is expected customer bring to the organization in specified period.In this paper, calculating and predicting CUSTOMER LIFETIME VALUE is as a key tool in the implementation of CUSTOMER RELATIONSHIP MANAGEMENT in banking. The GMDH NEURAL NETWORKs due to its high performance in terms of PREDICTION, is applied and with genuine customer demographic and transactional information of a private Iranian bank, the CLV forecasting is evaluated. The results show that this tool can be used to accurately predict over 90% of CUSTOMER LIFETIME VALUE.

Cites

  • No record.
  • References

  • No record.
  • Cite

    APA: Copy

    KHANLARI, AMIR, AHRARI, MEHDI, & MIRPOOR, SOMAYE. (2017). PREDICTING CUSTOMER LIFETIME VALUE BASED ON FINANCIAL AND DEMOGRAPHIC CHARACTERISTICS USING GMDH NEURAL NETWORK CASE STUDY: INDIVIDUAL CUSTOMERS OF A PRIVATE BANK OF IRAN. JOURNAL OF BUSINESS MANAGEMENT, 8(4 ), 833-860. SID. https://sid.ir/paper/140131/en

    Vancouver: Copy

    KHANLARI AMIR, AHRARI MEHDI, MIRPOOR SOMAYE. PREDICTING CUSTOMER LIFETIME VALUE BASED ON FINANCIAL AND DEMOGRAPHIC CHARACTERISTICS USING GMDH NEURAL NETWORK CASE STUDY: INDIVIDUAL CUSTOMERS OF A PRIVATE BANK OF IRAN. JOURNAL OF BUSINESS MANAGEMENT[Internet]. 2017;8(4 ):833-860. Available from: https://sid.ir/paper/140131/en

    IEEE: Copy

    AMIR KHANLARI, MEHDI AHRARI, and SOMAYE MIRPOOR, “PREDICTING CUSTOMER LIFETIME VALUE BASED ON FINANCIAL AND DEMOGRAPHIC CHARACTERISTICS USING GMDH NEURAL NETWORK CASE STUDY: INDIVIDUAL CUSTOMERS OF A PRIVATE BANK OF IRAN,” JOURNAL OF BUSINESS MANAGEMENT, vol. 8, no. 4 , pp. 833–860, 2017, [Online]. Available: https://sid.ir/paper/140131/en

    Related Journal Papers

    Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    Move to top
    telegram sharing button
    whatsapp sharing button
    linkedin sharing button
    twitter sharing button
    email sharing button
    email sharing button
    email sharing button
    sharethis sharing button