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Valuing an Engagement Surface using a Large Scale Dynamic Causal Model

Author

Listed:
  • Abhimanyu Mukerji
  • Sushant More
  • Ashwin Viswanathan Kannan
  • Lakshmi Ravi
  • Hua Chen
  • Naman Kohli
  • Chris Khawand
  • Dinesh Mandalapu

Abstract

With recent rapid growth in online shopping, AI-powered Engagement Surfaces (ES) have become ubiquitous across retail services. These engagement surfaces perform an increasing range of functions, including recommending new products for purchase, reminding customers of their orders and providing delivery notifications. Understanding the causal effect of engagement surfaces on value driven for customers and businesses remains an open scientific question. In this paper, we develop a dynamic causal model at scale to disentangle value attributable to an ES, and to assess its effectiveness. We demonstrate the application of this model to inform business decision-making by understanding returns on investment in the ES, and identifying product lines and features where the ES adds the most value.

Suggested Citation

  • Abhimanyu Mukerji & Sushant More & Ashwin Viswanathan Kannan & Lakshmi Ravi & Hua Chen & Naman Kohli & Chris Khawand & Dinesh Mandalapu, 2024. "Valuing an Engagement Surface using a Large Scale Dynamic Causal Model," Papers 2408.11967, arXiv.org.
    • Handle: RePEc:arx:papers:2408.11967
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    References listed on IDEAS

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    1. George Athanasopoulos & D. Poskitt & Farshid Vahid, 2012. "Two Canonical VARMA Forms: Scalar Component Models Vis-à-Vis the Echelon Form," Econometric Reviews, Taylor & Francis Journals, vol. 31(1), pages 60-83.
    2. Susan Athey & Stefan Wager, 2021. "Policy Learning With Observational Data," Econometrica, Econometric Society, vol. 89(1), pages 133-161, January.
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