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Milk-able Moments: New Tech and Farmer Behavior Change

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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.

 

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.

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