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Image by Andhika Y. Wiguna

Exploratory Research with Indian Farmers

This was a generative research study conducted for an international fertilizer company that wanted to understand Indian rice farmers.
Contextual inquiry and semi-structured interviews were used as research methods.
Personas and journey maps were our key deliverables.
I worked cross-functionally with
product, design and marketing teams.


An international fertilizer company that was relatively new to the Indian agricultural scene wanted to understand it's customers, the Indian farmers - particularly the rice farmers in North India to better understand them and find more ways to engage with them to encourage the use of it’s products. 

Determining Study Goals

After talking to the client, my team came up with 3 clear research goals:

1. To understand the Indian rice farmers: who they are, what are their everyday needs and challenges, how they use mobile and technology.

2. To understand the rice farmers' ecosystem: who are the supporting actors in the farmers ecosystem, what are their roles and responsibilities.

3. To understand farmers' rice growing journey: how and when rice farming tasks are carried out.

Determining Research Sample

The focus was on discovering needs and opportunities for products so, we maximized the number of users to 30.


We decided to divide this number equally between participants from 2 prominent rice growing states in Northern India: Uttar Pradesh and Haryana.


We decided on recruiting farmers with varied farming experience - 10 farmers with >15 years of experience, 10 farmers with 5-10 years of experience and another 10 farmers with less than 5 years of experience.

Recruiting Participants

I felt relieved when the client promised to provide contacts of farmers that could be potential participants. But, the recruitment process was never easy.

Challenge: Many farmers I called for screening, politely declined to participate. They were skeptical of some unknown people calling from big cities, asking if they would like to participate in some study that they neither cared about nor had the time to participate in. They were also worried about frauds.

I had to refine my narrative several times to convince them that I was genuine. I often sought help from local fertilizer retailers who knew the farmers, to prime them so they can anticipate my recruitment calls. 

Determining Research Methods

1. Diary Study: When we began considering research methods, my first instinct was a diary study - because it would give us a window to farmers' everyday lives, daily goals and frustrations and details of their rice growing journey. But, I soon realized that the farmers were so busy throughout their day, that they wouldn’t have the time or patience to produce diary entries for us. So, this option was scrapped.

2. Ethnographic field study: We chose this method because we could visit farmers' fields and homes, observe them closely and see their daily struggles and needs. However, we realized we couldn't collect all the information about growing rice only through a week long contextual enquiry, we needed a supplementary method.

3. In-depth interviews: We decided to conduct detailed 45 minutes, semi-structured interviews to understand tasks related to the rice growing cycle and to fill out any gaps left in the ethnographic study.

Pre-study Preparation

It was clear through our recruitment calls that the farmers in Haryana and Uttar Pradesh spoke different dialects of Hindi, some words in their lexicon were simply unknown to us. So, I did some secondary research and created a glossary for my team to familiarize ourselves with their dialects. I used these words while writing the discussion guide as well.

Challenges on the Field

  • Explaining consent forms to farmers: Farmers were not familiar with consent forms and had difficulty in understanding why they needed to sign one. Another major problem was that our consent forms were in English and most farmers who were not confident often relied on younger family members who could understand English, before signing these forms. I learnt the importance of having consent forms in a language users are most comfortable in.

  • Famers felt obligated to pay attention to us: Despite my best efforts to not make my presence felt while observing the farmers' activities, farmers felt awkward as it was an unusual experience for them. They also felt the need to make us feel comfortable - by offering us tea, lunch and requesting us to stay indoors if the sun was too hot. 

  • Interrupted sessions: The interviews were conducted inside farmers’ houses and were often interrupted by other family members or neighbors,  joining the sessions to give their own opinions. It was quite difficult for me to politely ask others to not participate in the conversation and keep the session going.

A participants' backyard which is usually a space for the cattle and farming tools

A participant reading information in Hindi about latest harvest selling prices on a agricultural news website

Data Analysis

  • Data were collected as field notes and audio recordings of the interviews which were then transcribed. This data was shifted to Miro as stickies to conduct thematic analysis using the affinity mapping technique.

  • Challenges:

    • There was a gigantic amount of data coming from 30 users - rich and detailed. And even though we were 4 researchers analyzing data, it took us a week to get through it.

    • Sometimes there was contradictory data and hence reaching definitive findings was tough.

  • For validation, I often asked my team if the themes we came up with were well supported by data - I checked whether a theme was saturated with a lot of instances and looked for any data that could contradict our themes. 

Stickies from Miro containing quotes from two participants on how they gather information related to farming activities.


  • Personas: Since one of the main goals was to understand who the farmers were, we created 3 different personas based on the ways in which farmers gathered information related to crops and about selling their produce. 

    • Tech-savvy online information seeker

    • Non-tech, retailer-dependent farmer

    • Limited tech, multi source information seeker.

  • Journey Map: Another main goal was to understand the rice growing process and associated needs and challenges. So, we designed a journey map that showed farmers’ journey from sowing seeds to selling yield.

  • Ecosystem Map: Another major goal was to understand who were the supporting actors in the farmers' rice growing journey - their exact roles and responsibilities. I created an map showing farmers' ecosystem,  that consisted of smaller sub-ecosystems like the government, community (family and fellow farmers) and mandi (the traditional marketplace to sell rice)

  • Detailed Report: Apart from the above findings, my team submitted a detailed report explaining all the findings in depth. 


I believe that the research impact is made at three levels, as described by Tao Dong here. 

In this study, the research impact was realized at the first two levels:

1. Research Questions Answered: The three well defined research questions - who are the rice farmers, what does their ecosystem look like and what is their journey of growing rice were answered clearly and the findings were accepted by the client.

2. Decisions Informed by the Research: This research helped the client develop an app for farmers which is a farm-focussed community platform and a weather companion, allowing farmers to connect with fellow farmers and agricultural experts to discuss issues and seek advice as well as to check weather updates easily.

I know this was a lot to read. Here's a cookie if you made it till the end! 

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