Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.04174 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866912017359568896 |
|---|---|
| author | Pilkauskaitė, Vaiva Gamper, Jevgenij Giniūnaitė, Rasa Reklaitė, Agne |
| author_facet | Pilkauskaitė, Vaiva Gamper, Jevgenij Giniūnaitė, Rasa Reklaitė, Agne |
| contents | In this study, we evaluate causal inference estimators for online controlled bipartite graph experiments in a real marketplace setting. Our novel contribution is constructing a bipartite graph using in-experiment data, rather than relying on prior knowledge or historical data, the common approach in the literature published to date. We build the bipartite graph from various interactions between buyers and sellers in the marketplace, establishing a novel research direction at the intersection of bipartite experiments and mediation analysis. This approach is crucial for modern marketplaces aiming to evaluate seller-side causal effects in buyer-side experiments, or vice versa. We demonstrate our method using historical buyer-side experiments conducted at Vinted, the largest second-hand marketplace in Europe with over 80M users. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_04174 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Towards Measuring Sell Side Outcomes in Buy Side Marketplace Experiments using In-Experiment Bipartite Graph Pilkauskaitė, Vaiva Gamper, Jevgenij Giniūnaitė, Rasa Reklaitė, Agne Machine Learning Applications In this study, we evaluate causal inference estimators for online controlled bipartite graph experiments in a real marketplace setting. Our novel contribution is constructing a bipartite graph using in-experiment data, rather than relying on prior knowledge or historical data, the common approach in the literature published to date. We build the bipartite graph from various interactions between buyers and sellers in the marketplace, establishing a novel research direction at the intersection of bipartite experiments and mediation analysis. This approach is crucial for modern marketplaces aiming to evaluate seller-side causal effects in buyer-side experiments, or vice versa. We demonstrate our method using historical buyer-side experiments conducted at Vinted, the largest second-hand marketplace in Europe with over 80M users. |
| title | Towards Measuring Sell Side Outcomes in Buy Side Marketplace Experiments using In-Experiment Bipartite Graph |
| topic | Machine Learning Applications |
| url | https://arxiv.org/abs/2409.04174 |