Donor Data Mining

Donor Data Mining is a systematic analytical process within prospect research that identifies, extracts, and interprets patterns, relationships, and predictive indicators from donor-related datasets to uncover actionable insights for fundraising and development strategies.

35

Publications

1K

Citations

110

Authors

60

Institutions

Publications per year

2017–2026

20

Authors

110

  1. AS
    Austin Strange

    William & Mary, United States

    1 publications · 182 citations

    1

    h-index

  2. EC
    Eddie Cheng

    Oakland University, United States

    1 publications · 10 citations

    1

    h-index

  3. WK
    Wendy K. Tam Cho

    University of Illinois Urbana-Champaign, United States

    1 publications · 61 citations

    1

    h-index

  4. SA
    Salih Aksu

    Hacettepe University, Türkiye

    1 publications · 29 citations

    1

    h-index

  5. MC
    Michael Chau

    University of Hong Kong, Hong Kong SAR China

    1 publications · 10 citations

    1

    h-index

1–5 of 110

Venues

  1. American Journal of Political Science

    AJPS · 2 publications · 130 citations

    2

    h-index

  2. ACM SIGKDD Explorations Newsletter

    2 publications · 63 citations

    2

    h-index

  3. 2

    h-index

  4. 1

    h-index

  5. Symmetry

    1 publications · 23 citations

    1

    h-index

1–5