Conversion Rate Modeling

Conversion Rate Modeling is a computational method that quantifies the probability of user-to-customer transformation within a given experimental timeframe by statistically characterizing the rate at which subjects transition from exposure to a treatment condition to completing a predefined target action.

181

Publications

7.9K

Citations

731

Authors

287

Institutions

Publications per year

2017–2026

77

Authors

731

  1. AM
    Alastair M. Thompson

    The University of Texas MD Anderson Cancer Center, United States

    2 publications · 89 citations

    2

    h-index

  2. EK
    Eunyee Koh

    Adobe Systems (United States), United States

    2 publications · 71 citations

    2

    h-index

  3. SH
    Seung-won Hwang

    Pohang University of Science and Technology, South Korea

    2 publications · 71 citations

    2

    h-index

  4. QL
    Quan Lin

    Huazhong University of Science and Technology, China

    2 publications · 223 citations

    2

    h-index

  5. KY
    Keping Yang

    Alibaba Group (China), China

    2 publications · 223 citations

    2

    h-index

1–5 of 731

Venues

  1. Industrial & Engineering Chemistry Research

    4 publications · 114 citations

    4

    h-index

  2. Physical review. B, Condensed matter

    PRB · 3 publications · 47 citations

    3

    h-index

  3. AIChE Journal

    3 publications · 74 citations

    3

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 3 publications · 159 citations

    3

    h-index

  5. Journal of Physics D Applied Physics

    3 publications · 111 citations

    3

    h-index

1–5