Valuing an Engagement Surface using a Large Scale Dynamic Causal Model
This addresses the need for businesses to evaluate returns on investment in engagement surfaces, though it appears incremental as it applies causal modeling to a specific domain.
The paper tackled the problem of quantifying the causal effect of AI-powered Engagement Surfaces on value for customers and businesses by developing a large-scale dynamic causal model, and demonstrated its application to assess effectiveness and inform investment decisions.
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.