Measuring what farmers really understand about crop insurance

What is shaping agriculture

Agriculture supports a large share of rural livelihoods, and its buying decisions are made close to the soil: at the village dealer, the cooperative and the neighbouring lead farmer. Seasonality, weather and credit shape almost every choice a farmer makes.

• Purchase decisions cluster in short pre-sowing windows
• Trusted dealers and lead farmers carry more weight than advertising
• Digital payments, agri-fintech and crop insurance are changing how farmers buy

A state agriculture department, working in Rajasthan. Client identity is withheld to protect confidentiality.

Organisation

A state agriculture department

Sector

Agriculture

Team engaged

Market Research

Services

Government research, Offline data collection (CAPI), Data processing & analytics

Enrolment in the crop insurance scheme looked healthy on paper, yet claims were rarely filed and complaints kept reaching the department. Officials wanted to know whether farmers understood what they were covered for, and where the process was breaking down.

• Deliver on the brief: measuring what farmers really understand about crop insurance.
• Understand the views, needs and behaviour of farm households.
• Measure how widespread each pattern is, and explain the reasons behind it.
• Give the client evidence it can act on within 10 weeks.

The work focused on 3,200 farm households.

• farm households3,200

Audiences we typically reach in agriculture

Farmers and growersAgri-input dealersCooperatives and FPOsAgronomists and extension workersAgri-fintech users

Coverage: Rajasthan. Market: India. 16 districts covered.

• India

A mixed-method design: structured research measured how widespread each pattern was, and qualitative conversations explained why.

1. 1Brief
2. 2Household survey
3. 3Focus groups with women farmers
4. 4Insight

We designed a household survey that asked farmers to explain the scheme in their own words rather than simply say whether they had heard of it. Separate group discussions with women farmers captured voices that household surveys often miss. GPS-tagged interviews and independent back-checks gave the department confidence in the data.

Government researchOffline data collection (CAPI)Data processing & analytics

farm households

3,200

• Respondents were selected across Rajasthan using quotas set in advance for each location and respondent type, so no single area or group dominated.
• Qualitative participants were recruited purposively to cover the full range of experiences that mattered, rather than for statistical representation.

group discussions

12

• Trained local-language interviewers conducted interviews in person on tablets (CAPI), with time and location recorded for every interview.
• Interviews and discussions were led by experienced moderators using a guide agreed with the client.

• Back-checks on a share of completed interviews
• Time and location checks on field interviews
• Supervisor accompaniment in the field
• Recordings and transcripts for every session
• Re-screening of qualitative recruits
• Logic and range checks on the final data
• Work carried out under our ISO 20252 quality procedures

• Cross-tabulation by key groups and locations
• Significance testing on the differences that mattered
• Thematic coding of interviews and discussions
• Journey and decision mapping
• Interactive dashboard for ongoing tracking

• Many enrolled farmers did not know they were insured, because premiums were deducted automatically with their crop loans.
• Very few knew the deadline for reporting losses.

Asking people to explain a scheme, not just recognise its name, reveals the real level of understanding.

• Build on the core insight: asking people to explain a scheme, not just recognise its name, reveals the real level of understanding.
• Focus effort where the evidence was strongest: many enrolled farmers did not know they were insured, because premiums were deducted automatically with their crop loans.
• Re-measure after the changes to confirm the effect.

• The department used the findings to redesign village awareness sessions and to add SMS reminders after extreme weather events.

What changed in the business as a result of the work. Impact is described qualitatively.

• Insight report and management presentation
• Cleaned data file and data tables
• Interactive dashboard
• Evaluation findings with programme recommendations

• Repeat the measure after changes are in place to track progress.
• A natural follow-on question: what do dealers recommend, and why?