IDEAS home Printed from https://ideas.repec.org/a/vrs/gfkmir/v8y2016i2p24-29n3.html
   My bibliography  Save this article

On Storks and Babies: Correlation, Causality and Field Experiments

Author

Listed:
  • Lambrecht Anja

    (Associate Professor of Marketing, London Business School, United Kingdom of Great Britain and Northern Ireland)

  • Tucker Catherine E.

    (Professor of Management Science, MIT Sloan School of Management, Cambridge, United States of America)

Abstract

The explosion of available data has created much excitement among marketing practitioners about their ability to better understand the impact of marketing investments. Big data allows for detecting patterns and often it seems plausible to interpret them as causal. While it is quite obvious that storks do not bring babies, marketing relationships are usually less clear. Apparent “causalities” often fail to hold up under examination. If marketers want to be sure not to walk into a causality trap, they need to conduct field experiments to detect true causal relationships. In the present digital environment, experiments are easier than ever to execute. However, they need to be prepared and interpreted with great care in order to deliver meaningful and genuinely causal results that help improve marketing decisions.

Suggested Citation

  • Lambrecht Anja & Tucker Catherine E., 2016. "On Storks and Babies: Correlation, Causality and Field Experiments," GfK Marketing Intelligence Review, Sciendo, vol. 8(2), pages 24-29, November.
    • Handle: RePEc:vrs:gfkmir:v:8:y:2016:i:2:p:24-29:n:3
    DOI: 10.1515/gfkmir-2016-0012
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/gfkmir-2016-0012
    Download Restriction: no
    File URL: https://libkey.io/10.1515/gfkmir-2016-0012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:vrs:gfkmir:v:8:y:2016:i:2:p:24-29:n:3. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.