fengtong-xiao/DMBGN
The implementation of the accepted paper "Deep Multi-Behaviors Graph Network for Voucher Redemption Rate Prediction" in SIGKDD 2021 Applied Data Science Track.
This project helps e-commerce businesses predict the likelihood of a customer redeeming a voucher. It takes customer behavior logs, voucher collection data, and item features as input to produce a prediction of whether a specific customer will use a particular voucher. Marketing managers, data scientists, and product owners in e-commerce would use this to optimize their promotional campaigns.
No commits in the last 6 months.
Use this if you need to accurately forecast voucher redemption rates to improve the effectiveness of your marketing campaigns and reduce wasted incentives.
Not ideal if you are looking for a general-purpose recommendation system or a solution for predicting other types of customer actions besides voucher redemption.
Stars
14
Forks
6
Language
Jupyter Notebook
License
BSD-2-Clause
Last pushed
Jun 02, 2021
Commits (30d)
0
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