Sizing the market for drone spraying services before a national launch

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

An agri-tech start-up expanding into South-East Asia, working in Malaysia & Indonesia. Client identity is withheld to protect confidentiality.

Organisation

An agri-tech start-up expanding into South-East Asia

Sector

Agriculture

Team engaged

Market Research

Services

Research consultancy, Quantitative research, Financial modelling

The start-up had a working drone service and investor interest, but its market estimates came from optimistic desk research. Before raising its next round, it needed a defensible view of how many farmers would actually pay for spraying, at what price and for which crops.

• Deliver on the brief: sizing the market for drone spraying services before a national launch.
• Understand the views, needs and behaviour of farmers.
• Understand the views, needs and behaviour of expert.
• Measure how widespread each pattern is, and explain the reasons behind it.
• Give the client evidence it can act on within 6 weeks.

The work focused on 1,200 farmers and 25 expert.

• farmers1,200
• expert25

Audiences we typically reach in agriculture

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

Coverage: Malaysia & Indonesia. Markets: Malaysia and Indonesia.

• Malaysia
• Indonesia

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

1. 1Brief
2. 2Farmer survey
3. 3Expert interviews
4. 4Bottom-up market model
5. 5Insight

We combined interviews with agronomists, farm service providers, plantation managers and agrochemical dealers with a farmer survey covering crop, farm size, current spraying practice and willingness to pay at several price points. Our finance team turned the results into a transparent bottom-up model with clear assumptions and scenarios.

Research consultancyQuantitative researchFinancial modelling

farmers

1,200

expert

25

• Business respondents were screened on role, company size and involvement in the decision before being invited.
• Respondents were selected across Malaysia & Indonesia 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.

• Trained local-language interviewers conducted interviews in person, supervised in the field.
• Interviews and discussions were led by experienced moderators using a guide agreed with the client.
• Secondary sources and client data were compiled and cross-checked before modelling.

• 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
• Market model built from secondary data and primary evidence

• Demand was strongest among mid-sized paddy and wheat farmers facing labour shortages at peak season, and much weaker for smallholders on mixed crops.

A smaller, well-evidenced market estimate is more persuasive to investors than a large number nobody can explain.

• Build on the core insight: a smaller, well-evidenced market estimate is more persuasive to investors than a large number nobody can explain.
• Focus effort where the evidence was strongest: demand was strongest among mid-sized paddy and wheat farmers facing labour shortages at peak season, and much weaker for smallholders on mixed crops.
• Re-measure after the changes to confirm the effect.

• The founders narrowed their launch to two provinces and two crops, and presented the model with its assumptions to investors.

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

• Repeat the measure after changes are in place to track progress.
• A natural follow-on question: which channels reach farmers before sowing?