Combining visual customer segmentation and response modeling

Zhiyuan Yao, Peter Sarlin, Tomas Eklund, Barbro Back

    Forskningsoutput: TidskriftsbidragArtikelVetenskapligPeer review

    12 Citeringar (Scopus)

    Sammanfattning

    Customer relationship management is a central part of Business Intelligence, and sales campaigns are often used for improving customer relationships. This paper uses advanced analytics to explore customer behavior during sales campaigns. We provide a visual, data-driven and efficient framework for customer-segmentation and campaign-response modeling. First, the customers are grouped by purchasing behavior characteristics using a self-organizing map. To this behavioral segmentation model, we link segment-migration patterns using feature plane representations. This enables visual monitoring of the customer base and tracking customer behavior before and during sales campaigns. In addition to the general segment-migration patterns, this method provides the capability to drill down into each segment to visually explore the dynamics. The framework is applied to a department store chain with more than 1 million customers.
    OriginalspråkOdefinierat/okänt
    Sidor (från-till)123–134
    Antal sidor12
    TidskriftNeural Computing and Applications
    Volym25
    Utgåva1
    DOI
    StatusPublicerad - 2014
    MoE-publikationstypA1 Tidskriftsartikel-refererad

    Nyckelord

    • Business Intelligence
    • Campaign-response modeling
    • Customer relationship management (CRM)
    • Customer segmentation
    • Visual analytics

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