Abstract
This study examines whether limited access to high‑quality demand and supplier information constrains the growth of small retailers in developing countries and whether an AI‑driven mobile application that pools sales data across shops can overcome this barrier. It will further test what the returns are to increasing the size of the data pool. One thousand Lusaka‑based retail shops will be randomly assigned in equal proportion to (i) an inventory‑management app only (control); (ii) the app plus lower-priced supplier recommendations generated from data pooled across a relatively small number of similar shops; or iii) the app plus lower-priced supplier recommendations generated from data pooled across a relatively large number of similar shops; or (iv) the app plus product recommendations generated from data on similar shops. Further, within the arm assigned to receive product recommendations, half the stores will receive a buy-back offer to mitigate against the risk of adopting new products that do not sell well. We will followup with the shops 3 times during and immediately after the intervention, and again 3 months later, in order to collect detailed data on adoption of the recommended products and suppliers, weekly sales, and business income. Results will inform policies aimed at supporting SME productivity through digital data‑sharing platforms.