Industry overview
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
Client background
A dairy cooperative, working in Uttar Pradesh. Client identity is withheld to protect confidentiality.
- Organisation
- A dairy cooperative
- Sector
- Agriculture
- Team engaged
- Market Research
- Services
- Quantitative research, Offline data collection (CAPI), Research consultancy
Client challenge
The cooperative planned to change collection timings and introduce digital milk testing. Leaders were worried that farmers might switch to private buyers if the changes were poorly received.
Research objectives
- Deliver on the brief: listening to dairy farmers before redesigning milk collection.
- Understand the views, needs and behaviour of dairy farmers.
- Measure how widespread each pattern is, and explain the reasons behind it.
- Give the client evidence it can act on within 6 weeks.
Target audience
The work focused on 1,100 dairy farmers.
- dairy farmers1,100
Audiences we typically reach in agriculture
Farmers and growersAgri-input dealersCooperatives and FPOsAgronomists and extension workersAgri-fintech users
Geographic coverage
Coverage: Uttar Pradesh. Market: India. 60 village collection centres covered.
- India
Research methodology
A mixed-method design: structured research measured how widespread each pattern was, and qualitative conversations explained why.
- 1Brief
- 2Farmer survey
- 3Collection centre observations
- 4Insight
We surveyed farmers at their homes and observed morning and evening collections to understand queues, testing disputes and payment practices. Questions explored what farmers valued most: price, fair testing, prompt payment or convenience.
Quantitative researchOffline data collection (CAPI)Research consultancy
Sampling strategy
- dairy farmers
- 1,100
- Respondents were selected across Uttar Pradesh 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.
Data collection
- 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.
- Auditors and mystery shoppers followed a standard checklist, recording evidence at each visit.
Data quality & validation
- 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
- Photo or document evidence for audit points
- Second-reviewer checks on scores
- Logic and range checks on the final data
- Work carried out under our ISO 20252 quality procedures
Data analysis
- Cross-tabulation by key groups and locations
- Significance testing on the differences that mattered
- Thematic coding of interviews and discussions
- Journey and decision mapping
Key findings
- Fair, visible fat testing and on-time payment mattered far more to farmers than collection timings.
Asking first prevented a well-intended change from damaging trust.
Recommendations
- Build on the core insight: asking first prevented a well-intended change from damaging trust.
- Focus effort where the evidence was strongest: fair, visible fat testing and on-time payment mattered far more to farmers than collection timings.
- Re-measure after the changes to confirm the effect.
Business impact
- The cooperative introduced digital testing with printed slips first, communicated the change at village meetings, and adjusted timings only in villages where farmers requested it.
What changed in the business as a result of the work. Impact is described qualitatively.
Deliverables & next steps
- Insight report and management presentation
- Cleaned data file and data tables
- Repeat the measure after changes are in place to track progress.
- A natural follow-on question: what do dealers recommend, and why?
Client identity is withheld to protect confidentiality.