data driven attribution
LiDDA: Data Driven Attribution at LinkedIn
Bencina, John, Aykutlug, Erkut, Chen, Yue, Zhang, Zerui, Sorenson, Stephanie, Tang, Shao, Wei, Changshuai
Data Driven Attribution, which assigns conversion credits to marketing interactions based on causal patterns learned from data, is the foundation of modern marketing intelligence and vital to any marketing businesses and advertising platform. In this paper, we introduce a unified transformer-based attribution approach that can handle member-level data, aggregate-level data, and integration of external macro factors. We detail the large scale implementation of the approach at LinkedIn, showcasing significant impact. We also share learning and insights that are broadly applicable to the marketing and ad tech fields.
- North America > United States > Minnesota > Hennepin County > Minneapolis (0.14)
- North America > United States > California > Santa Clara County > Sunnyvale (0.05)
- Research Report > Experimental Study (1.00)
- Research Report > New Finding (0.68)
- Information Technology > Services (0.94)
- Marketing (0.93)
Position Based Attribution vs. Data Driven Attribution: Where Machine Learning Fits in
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