Outcome: Creating and enabling co-ownership of our farmer roles using the jobs-to-be-done framework. These farmer roles paired with our new understanding of farm type, application use (website & mobile app), and subscription create our farmer building blocks.
The Problem
After completing several research projects, I realised our personas didn't capture the full picture of the farmers we interviewed, they lacked information about their role, farm type, size, FarmIQ subscription, and other factors that affect their decision-making.
From this point on, when conducting our regular research the design team committed to asking all participants the same introduction questions to learn more about their daily life on the farm, responsibilities, goals, motivations, frustrations, device use, and FIQ's value. After every user interview session, we created a farmer on a page, this helped us gather the necessary information to create a refined framework to help us understand our diverse customers more.
We reviewed our current personas
Whilst gathering this information we reviewed the current personas to see why we didn't find them easy to use, and what might be stopping us from using them in our day-to-day roles.
We found the friction around using the personas was that we had two personas a Data Farmer and a Traditionalist. These farmers have the same role as Farmer Owner Operators (managers). Their differentiator was their different levels of adoption of technology. We had one persona for a worker, and their adoption of technology was not included. At this time with six months of experience researching with our customers, I had never spoken to a worker. However, I had spoken to several small farm Owner Operators and a Stock Manager who used the mobile app. When reviewing our personas we felt they were oversimplified in some areas, yet in others missed important contexts that would affect their decision-making more than their technology adaption. For example, farm size and number of employees are huge factors in how farmers' use our farm management software.
Applying ArgiTech's research
We understood that farmers' different levels of technology adoption are one of the barriers to using a farm management tool and affect how that farmer would use our product. Since the creation of FarmIQ's personas in 2020, AgriTech conducted research titled 'Baseline of Digital Adoption in Primary Industries'. In this research, their team interviewed over 1,000 farmers across the whole of New Zealand documenting their attitudes towards technology.
It was insightful to see their six personas on a quadrant graph using low/high pressure and low/high intent. We adapted this framework and included our personas - Data Farmer and Progressive Traditionalist. We now use this graph as a tool during customer interviews. This helps us determine whether the customer's technology adoption is a voluntary or obligatory decision for them.
Understanding Farmers' Roles
After implementing the new farmer introduction questions, reviewing the farmers on a page, and summarising our findings it became apparent that a defining part of a farmer's mindset is their role.
As the Senior Product Designer and I are not from a farming background we ran a few sessions with our internal farming experts to understand the different roles on a Sheep, Beef, and/or Dairy farm. In these workshops, we co-created our farmer roles from our internal staff's farming knowledge and our experience conducting customer research. We found that even these work-in-progress roles on a page, helped us to think of our customers' JTBD, and we quickly started to use them.
After completing our review, we identified our role priorities. Our top priority is to ensure that all users who frequently use our applications have a seamless experience. Even though workers do not pay for the tool, if it is difficult to use, they may not utilise it, leading to a potential cancellation of the subscription by the Farm Owner. Our second priority is to cater to our third-party users, particularly compliance roles, such as auditors, environmental consultants, and rural professionals, to ensure that they have the information from FarmIQ at their fingertips to perform their tasks efficiently.
Refining our farmers' roles
We placed all of our 'farmers on a page' from the past year of interviews and grouped them into their roles. We used these to validate and update our work-in-progress roles.
We discovered that our roles on the farm could be classified into three distinct groups. The first group consists of owners who have a financial interest in the farm. The second group comprises non-owners who work on the farm daily. The third group consists of individuals who require access to the farm for third-party purposes. To make it easier to differentiate between these groups, we have assigned each of them a different colour.
Example of our roles on a page
Understanding our farmers' "Jobs-to-be-Done"
We took everything we learned from our 1on1 interviews and farmer roles and started to apply the Jobs-to-be-Done (JTBD) framework. At its core, the JTBD theory is that people buy products to get their “jobs” done. When innovation understands the customers' jobs, the success of the product goes from a mere 17% to 86%.
We took time to understand FIQ's place in the market and our core farmers' JTBD - managing life on the farm.
Farmers are loyal to the job they need to get done, not the solution. Managing life on farm is their core JTBD
Then we understood what FIQ's JTBD Growth Strategy Matrix is to understand which part of the marketplace we are targeting to win. As FIQ offers different levels of subscriptions we adopt a dominant and disruptive strategy.
The Solution
Our farmer roles are just one part of our modular Farmer Building Blocks. With our roles understood and defined we worked on looking at the other aspects that affect farmers' decisions. To date, our farmer system includes JTBD, roles, packs, technology adoption, and farm staff structure/size. We are constantly validating these after every research project. In the future, we want to also consider the implications of farm size, stock type, and level of debt.
Although every farm is unique, there are some common examples of farm staff structures that can be used as a guideline.
Successfully Implementing the Solution
We have a variety of components in our core library that help us understand our customers' needs. Our components range from small role visuals for observing current user behaviours to more complex roles with detailed descriptions, specifically for the new FarmIQ staff. Each role is listed on a page that includes motivations and goals, device usage, pain points, FarmIQ barriers, value, and up next for FIQ. Additionally, we have a dedicated component for each pack, and diagrams illustrating the most common operational structures.
To leverage our knowledge effectively, we regularly utilise our "Farmer Building Blocks." They assist us in our discovery process by helping us understand user flows, customer pain points, enhancement requests, and upcoming research.
At the end of a season of customer research, we review and update our roles using our "farmer-on-a-page" findings - this is part of our team objectives that I track. This ensures that we always empathise with our customers, especially considering that farmer pain points are often factors beyond their control, such as compliance, profits, and weather.
Work completed whilst at FarmIQ