IDEAS home Printed from https://ideas.repec.org/a/eee/joreco/v84y2025ics0969698925000244.html
   My bibliography  Save this article

Identifying targeted needs from online marketer- and user-generated data

Author

Listed:
  • Bai, Ye
  • Yu-Buck, Grace

Abstract

On e-retailing sites, marketer-generated content (MGC), user-generated content (UGC), and potential user-generated content (PUGC) are constantly conveying their needs. Identifying and clustering these needs, especially targeted needs, helps implement differentiated market strategies, improves the helpfulness of user's review content, and enhances potential user's purchase experiences. If so, then, how to identify diverse needs and find out where they are targeted (lower/higher). Based on Maslow's hierarchy of needs theory, the authors propose a need hierarchy framework to explore these questions. We utilize the datasets from two experiential products on Amazon.com and combine text mining methods with regression analyses to identify and cluster the targeted needs of online-generated content. The results show that the needs conveyed by MGC, UGC and PUGC are hierarchical and targeted, and the targeted needs are mapped to higher levels. Furthermore, we also find that the needs conveyed by PUGC are influenced by and aligned with needs of UGC. The findings reveal the deeper value of online-generated content for identifying needs, and provide a highlight for studying needs of Maslow's hierarchy of needs theory in the new field of e-commerce. Meanwhile, the results obtain the new ideas for enhancing the online interaction experiences of all the stakeholders.

Suggested Citation

  • Bai, Ye & Yu-Buck, Grace, 2025. "Identifying targeted needs from online marketer- and user-generated data," Journal of Retailing and Consumer Services, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:joreco:v:84:y:2025:i:c:s0969698925000244
    DOI: 10.1016/j.jretconser.2025.104245
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969698925000244
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jretconser.2025.104245?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
    ---><---

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

    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:eee:joreco:v:84:y:2025:i:c:s0969698925000244. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-retailing-and-consumer-services .

    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.