Definition
Farmer Organisation (FO) segmentation refers to companies categorising FOs into different groups or levels, whereby the provision of goods, services and incentives are tailored to each group depending on needs, profile, organisational capacity, performance or any other relevant factors. Segmenting farmer organisations in this way and tailoring services helps companies to optimise impact and get the most value from those services.
Lead Actors
Input Provider; Financial Service Provider; Off-taker; Other Service Provider; Trader
Target Demographics
Farmer Organisations; Smallholder Farmers
Objectives addressed
Farmer related
Improve yields:
Farmer segmentation enables tailored support which can boost yields. By identifying farmers with low productivity or limited access to services, companies can deliver targeted interventions such as specialised agronomic training or input support. Segmentation also highlights gaps in access to quality seeds, fertilisers, and mechanisation, allowing for more effective solutions that can enhance farm performance.
Increase farmer income:
Tailored service provision can help farmers improve the quality and volume of their production, enabling them to access better or new markets. This may ultimately increase their income.
Address gender inequalities:
Women farmers often face distinct barriers, including limited access to resources, training, inputs, and financial services. Segmenting farmers by gender and other socio-economic factors allows interventions to be tailored to these challenges. This may promote greater inclusion, empowerment, and improved productivity among women farmers.
Business related
Strengthen organisational processes:
Segmentation enables companies to strengthen organisational processes by improving resource allocation, decision-making, supply chain management, and financial planning. It helps agribusinesses operate more efficiently, deliver better outcomes for farmers, and scale their operations sustainably.
Lower credit losses:
Farmer segmentation can serve as a risk management strategy by limiting input credit or loans to well-performing farmers, which may reduce the risk of loan defaults.
Reduce side-selling:
Once farmers are segmented, it becomes easier for the company to manage expected quality, quantity, and pricing for each segment. Clearer communication on requirements and pricing can improve farmers' access to markets. Combined with tailored service provision, this enhanced communication can also incentivise farmers to sell to the company.
Reduce cost-to-serve:
Segmentation may lower the cost of serving farmers by allowing companies to tailor support based on specific needs rather than applying a uniform approach. By focusing resources on the right farmers with the right services at the right time, companies can avoid the inefficiencies of blanket service delivery.
Improve sourcing efficiency:
By segmenting farmers, companies can better assess the performance of specific groups, such as yield, quality, and harvest timing, and use this information to schedule sourcing more efficiently.
Contexts Best Suited to
Tight value chains: FMIS works across all value chains but is most efficient in tighter chains with existing investments in farmer engagement, such as contracts or data collection efforts.
Infrastructure: Strong digital and rural infrastructure facilitates efficient data collection.
Scattered Farming models: FMIS is particularly useful where diverse farming models (e.g., semi-subsistence and commercial) create greater farmer heterogeneity, making segmentation more valuable.
Infrastructure: Strong digital and rural infrastructure facilitates efficient data collection.
Scattered Farming models: FMIS is particularly useful where diverse farming models (e.g., semi-subsistence and commercial) create greater farmer heterogeneity, making segmentation more valuable.
Key Risks
Exclusion: exclusion of vulnerable farmers deemed too risky or costly.
Poor decision-making: if based on outdated or low-quality data, leading to low service adoption or mismatches.
Farmer distrust: if segmentation results in unequal service offerings without clear communication. Safeguards include validating findings with farmer organisations and community leaders and ensuring timely updates to maintain data quality and community trust.
Poor decision-making: if based on outdated or low-quality data, leading to low service adoption or mismatches.
Farmer distrust: if segmentation results in unequal service offerings without clear communication. Safeguards include validating findings with farmer organisations and community leaders and ensuring timely updates to maintain data quality and community trust.
Environmental Impact
Limited:
Limited direct environmental impact.
Ambition level
Medium
Time
Developing a segmentation strategy requires an initial time investment for data collection and farmer classification. Strategies based on multiple factors or limited existing data demand greater effort. Segmentation is a dynamic process that requires continuous monitoring and updates to keep criteria and interventions relevant as farmers’ circumstances evolve due to market, environmental, or policy changes.
Investment Need
Similar to time investments, costs depend on the complexity of the segmentation strategy and the availability of relevant data (e.g., through an existing FMIS or farmer touchpoints). Costs can rise with the number of variables used and the size of the farmer base. If in-house data analysis skills are lacking, external experts may be needed to analyze the data and identify farmer groupings based on predefined variables.
