What makes farmers continue using a digital tool? The Agile Data Approaches and Innovations for Monitoring (ADAIM) study in Burundi explored this question by introducing a farmer-centered App during one coffee harvest period and monitoring farmers’ participation over an entire year.

Overall participation averaged around 34% over the study period, but engagement varied considerably among farmers. Some farmers used the App regularly, while others participated much less frequently. The analysis helps explain this variation, pointing to two factors that were directly associated with continued participation: learning from other farmers and learning through the repeated use of the App itself.

The first is peer learning. Farmers were significantly more likely to use the App when other farmers at their Coffee Washing Station were also actively using it. The more engaged the community, the more likely individual farmers were to participate. This suggests that technology adoption is not exclusively an individual decision. Farmers observe what others are doing, exchange experiences and learn from their peers. In other words, digital adoption can spread through social networks. A farmer may be more willing to try out and continue using a new technology when they see other farmers around them using it.

Farmers were more likely to use the App when other farmers around them were using it too.

The second important factor was learning by doing. Farmers who reported becoming more familiar with the technology through repeated use were more likely to continue participating. Repeated use may have helped farmers become more comfortable with the App and better able to integrate it into their regular activities, making continued participation easier. In a related COSA article on our Agile Data pilot in Côte d’Ivoire, this relationship is explored further by examining whether participation is also influenced by the extent to which farmers receive useful information in return for using the app (i.e. Data DemocracySM).

Do incentives and socio-demographics drive participation?

Financial incentives appeared to coincide with an increase in participation, but the study could not determine whether the incentives themselves caused this increase. The farmers who received the incentives were already among the most engaged participants, participating 80% of the time during the first semester. This makes it difficult to separate the effect of the incentives from the characteristics and prior engagement of the farmers who received them. The key lesson is that who receives an incentive matters when assessing whether it works. To better understand the effect of incentives, COSA is exploring this question through a randomly assigned incentive pilot in a Colombia case study.

Furthermore, participation closely followed the agricultural calendar. Engagement was highest during the coffee harvest, from April to July 2025, when farming activities were most intensive and the information requested by the App was most relevant to the farmers’ daily work. This suggests that the timing and relevance of data collection are also important. Farmers may be more willing to interact with a digital tool when the information being collected is closely connected to what they are doing at that moment.

The study design did not allow incentives to be randomly assigned; therefore their causal effect could not be isolated

Interestingly, socio-demographic characteristics such as age, gender, and education did not significantly affect participation. This suggests that engagement with the App was driven less by who the farmers were and more by their experience within the project and the environment in which they were using the technology.

Farmer engagement was about experience, not demographics

Taken together, these findings suggest that successful digital data collection is about much more than providing farmers with a smartphone or an app. Farmers participate when technology is relevant to their lives, when they can learn from others, and when they gain something useful from the process themselves. Building these elements into digital data initiatives may be just as important as addressing connectivity and technical barriers. The Burundi experience therefore points towards a broader lesson for digital agriculture: sustained participation needs to be designed into the technology and the program from the beginning, rather than treated simply as a question of whether farmers have access.

More about the Case Study

A Farmer-Centric App for Collecting Cost of Production and Actual Income Data in Burundi

JNP Coffee is a coffee exporter and importer that produces, promotes, and trades African specialty coffee. This company has a mission to generate a future of hope for coffee farmers in Burundi, East Africa by rewarding growers, building self-esteem, and promoting inclusion for women and youth.

COSA’s collaboration with JNP coffee in Burundi demonstrated the power of Agile data collection in practice. The multi-year project assessed the production costs and actual incomes of coffee farmers in JNP Coffee’s supply chain. The purpose of this pilot, funded by the Gates Foundation, was to allow COSA to evaluate the viability and effectiveness of high-frequency data collection approaches. It also provided JNP Coffee with access to new Agile data tools and approaches that could rapidly yield useful insights. This allowed JNP to better understand the drivers of cost and income for its farmers so that the company could optimize their prices. Learn more about this pilot in Sustainability Unplugged.

More about the Agile Data Project

Agile data approaches are transforming how development programs monitor, evaluate, and integrate data-driven knowledge. By allowing teams to collect and analyze data more frequently and efficiently, Agile methodologies offer real-time insight into key metrics, enabling faster strategy adaptation and more meaningful engagement with stakeholders. When combined with Agile data principles, which emphasize thoughtful, respectful, and resource-efficient data collection, the result is enhanced experiences for data contributors, better-quality information, and stronger decision-making.

COSA’s work exemplifies this synergy by integrating standardization, relevance, and rigor into Agile data frameworks. Through the Agile Data Approaches and Innovations for Monitoring (ADAIM) project we champion frequent, low-cost, and actionable data snapshots. These snapshots provide information about what does and does not work while the project is still in process. This allows for mid-course adjustments and real-time integration of data-driven insights, improving efficiency and impact.