Milk-able Moments: New Tech and Farmer Behavior Change

Overview

How to unlock a new wave of milk productivity in Tanzania? I conducted a causal study to help donors understand the impact of a four-year project that used competitions to incentivize suppliers to deliver productivity-enhancing technologies to dairy farmers.

With improved availability of dairy technologies (fodder, vaccines, parasite control, artificial insemination), I measured user behavior change in treatment and comparison groups by tracking metrics such as conversion rates, income, and milk yields, and churn.

Analytical Approach

The study used a difference-in-difference design to measure the extent farmers adopted dairy technologies. For farmers who adopted dairy technologies, a before-after analysis was conducted to compare milk yields and income before and after the project. ADD MATCHING

Survey data was collected from 5,000+ farmers, sampled across treatment and comparison groups in six regions in Tanzania, complemented by dozens of stakeholder interviews and focus groups.

Key Metrics

Conversion rate, technology adoption, income, milk yields, churn.

My Role and Impact

Conducted panel survey data analysis that generated insights informing the next generation of investments under the $152M AgResults initiative.
Delivered high-quality data by managing survey data collection across 5,000+ households in treatment and comparison areas in 6 regions in Tanzania.
Led on-site training of 36 enumerators in Tanzania to ensure high-quality data collection that program decisions can confidently rely on.
Presented the methodology and limitations to improve stakeholder’s understanding of the study approach.
Co-developed research and analysis plans.