Summary of Valuing An Engagement Surface Using a Large Scale Dynamic Causal Model, by Abhimanyu Mukerji et al.
Valuing an Engagement Surface using a Large Scale Dynamic Causal Model
by Abhimanyu Mukerji, Sushant More, Ashwin Viswanathan Kannan, Lakshmi Ravi, Hua Chen, Naman Kohli, Chris Khawand, Dinesh Mandalapu
First submitted to arxiv on: 21 Aug 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Econometrics (econ.EM); 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 proposed paper develops a dynamic causal model at scale to analyze the causal effect of AI-powered Engagement Surfaces (ES) on customer and business value. The model aims to disentangle the value attributable to an ES, assess its effectiveness, and inform business decision-making by understanding returns on investment in the ES and identifying product lines and features where it adds the most value. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper explores how AI-powered Engagement Surfaces affect customers and businesses. It’s like a digital assistant that helps you find things you want to buy online. The researchers created a special model to figure out how much value this technology brings to both sides. They’re trying to answer questions like: what makes people spend more money because of these surfaces? And which products are most affected by them? |
