IDEAS home Printed from https://ideas.repec.org/a/aza/ama000/y2016v2i1p73-83.html
   My bibliography  Save this article

Intelligent profiles and segments equals pure power for business: Combining profiles, segment and predictive analytics

Author

Listed:
  • Ahlemeyer-Stubbe, Andrea

    (Director Strategic Analytics, servicepro GmbH, Germany)

  • Horvath, Stephan

Abstract

Business is excellent. Customers are more than loyal; they are in love with the brand. Marketing campaigns regularly bring good results and new customers. Innovative products precisely meet current needs. Who would not like to say such things about their company? The way to get to this nirvana is through thoughtful consolidation and analysis of all relevant information about customers and prospects in order to calculate profiles and segments — and to extrapolate them into the future. The general use of audience segments is not new, and marketing profiles have existed since before data grew big. But by collecting and using online and offline behavioural data, location data and touchpoint data, in combination with the power of predictive modelling, we can provide insight-driven, individualised communication and interactions with customers and prospects. This provides indispensable fuel for daily business and drives client success. This paper will outline the framework for these newly developed and successfully implemented methods and will describe some of the business opportunities they can empower.

Suggested Citation

  • Ahlemeyer-Stubbe, Andrea & Horvath, Stephan, 2016. "Intelligent profiles and segments equals pure power for business: Combining profiles, segment and predictive analytics," Applied Marketing Analytics: The Peer-Reviewed Journal, Henry Stewart Publications, vol. 2(1), pages 73-83, February.
    • Handle: RePEc:aza:ama000:y:2016:v:2:i:1:p:73-83
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/4443/download/
    Download Restriction: Requires a paid subscription for full access.
    File URL: https://hstalks.com/article/4443/
    Download Restriction: Requires a paid subscription for full access.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    intelligent profiles; intelligent segments; automated predictive models; predictive modelling; unsupervised learning; clustering; imputation;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

    Statistics

    Access and download statistics

    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:aza:ama000:y:2016:v:2:i:1:p:73-83. 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: Henry Stewart Talks (email available below). General contact details of provider: .

    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.