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# Background Social impact interventions often involve the introduction of a product intended to create positive impact. Program decision makers need data to routinely review product delivery as well as predict potential outcomes and impact to optimize intervention plans and allocate resources effectively. We propose a novel model to support data-driven decision-making in data and budget-constrained settings and use of routine monitoring to ensure progress towards program outcomes and impact. # Methods We present a complete model to estimate product reach of durable and fast-moving consumer products, which includes required inputs, potential data sources, formulas, trade-offs, and assumptions. # Results We illustrate the use of the model by applying it to the case study of fortified rice introduction in Brazil and estimate that the intervention, which aimed to improve nutrition status and health outcomes reached 2.4 million consumers. # Conclusions The model can cover a broad range of social-purpose interventions that involve the introduction or scale-up of various types of consumer products. It provides a relatively simple, comprehensive, flexible, and usable framework to estimate product reach, an indicator that can be an input into impact estimates or, in many scenarios, the actual endpoint of the intervention.