IDEAS home Printed from https://ideas.repec.org/h/spr/sptchp/978-3-662-55381-7_18.html
   My bibliography  Save this book chapter

Future of CRM

In: Customer Relationship Management

Author

Listed:
  • V. Kumar

    (Georgia State University)

  • Werner Reinartz

    (University of Cologne)

Abstract

This chapter discusses the current and future states of CRM. As it stands, there are three current CRM perspectives: (1) Strategic CRM, has as an objective to mold the interactions between a firm and its customers in order to maximize CLV for the firm. (2) Analytical CRM, which is designed to help firms migrate from relying entirely on traditional marketing metrics to customer-based value metrics. (3) Operational CRM, is gaining significant traction among firm due to changes with respect to (a) consumers, (b) marketplaces, (c) technology, and (d) marketing functions. This chapter also discusses three key areas in which CRM will be expanding in the near future: (1) Social CRM (2) Global CRM and (3) Database CRM.

Suggested Citation

  • V. Kumar & Werner Reinartz, 2018. "Future of CRM," Springer Texts in Business and Economics, in: Customer Relationship Management, edition 3, chapter 18, pages 385-404, Springer.
    • Handle: RePEc:spr:sptchp:978-3-662-55381-7_18
    DOI: 10.1007/978-3-662-55381-7_18
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Karen L. Orengo-Serra & María Sánchez-Jauregui, 2021. "Coping with earthquakes and COVID-19: A perspective of customer relationship management," Estudios Gerenciales, Universidad Icesi, vol. 37(159), pages 318-331, June.
    2. Guha, Abhijit & Grewal, Dhruv & Kopalle, Praveen K. & Haenlein, Michael & Schneider, Matthew J. & Jung, Hyunseok & Moustafa, Rida & Hegde, Dinesh R. & Hawkins, Gary, 2021. "How artificial intelligence will affect the future of retailing," Journal of Retailing, Elsevier, vol. 97(1), pages 28-41.
    3. Lamrhari, Soumaya & Ghazi, Hamid El & Oubrich, Mourad & Faker, Abdellatif El, 2022. "A social CRM analytic framework for improving customer retention, acquisition, and conversion," Technological Forecasting and Social Change, Elsevier, vol. 174(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sptchp:978-3-662-55381-7_18. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.