Summary of Assessing the Impact Of Upselling in Online Fantasy Sports, by Aayush Chaudhary
Assessing the Impact of Upselling in Online Fantasy Sports
by Aayush Chaudhary
First submitted to arxiv on: 1 Sep 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Applications (stat.AP)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper investigates the effect of upselling on user engagement in the context of fantasy sports platform Dream11. The authors develop a model of users’ deposit behavior and design an experimental framework to evaluate the impact of upselling using an intensity parameter. Results from live experiments show that increased upselling intensity leads to decreased user recall, but improves deposit metrics at the cost of user satisfaction and conversion rates. To personalize upselling intensity levels, the researchers employ robust counterfactual analysis and causal meta-learners. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks into how upselling affects people’s behavior on a fantasy sports website called Dream11. The researchers create a model to understand why users make deposits or not, then test different levels of upselling to see what happens. They found that when upselling is stronger, people are less likely to come back, but they do spend more money. This means there’s an optimal level of upselling that balances these two things. |
Keywords
* Artificial intelligence * Recall
