Targeting, Personalization, and Engagement in an Agricultural Advisory Service

Abstract

ICT is increasingly used to deliver customized information in developing countries. We examine whether individually targeting the timing of automated voice calls meaningfully increases engagement in an agricultural advisory service. We define, estimate, and evaluate a novel recommendation system that customizes contact times to individual characteristics. This system generates significant gains, up to an 8% increase over the baseline pickup rate of 0.31. Our approach, delivered at scale, is well-suited for developing country settings. We show how to optimize around resource constraints, measure equity-efficiency trade-offs when targeting vulnerable groups, and evaluate the robustness of recommendations to technology or preference shocks.

Keywords: Recommendation Systems, Agricultural Extension Services, Agriculture, Causal Inference, Randomized Controlled Trials

JEL Classification: O13, C90, Q16