Cooper UX Intensive: Fair Trade USA

My design process and learning in 4day social innovation project.

Photo Credit: Fair Trade USA

Whenever I get a chance to level up my skills as a UX designer, I take it.

The 4 day UX intensive course at Cooper, really inspired me because it would help me learn and apply the Cooper way of design thinking in a fast paced four day design workshop. Being passionate about working for social causes, I was particularly excited to see that the NGO we were working for was Fair Trade. They are doing such phenomenal work in providing better lives for farmers by establishing sustainable relationships with brands.

The workshop was led by the amazing Jenea Hayes and Shannon McGarity from Cooper along with guidance on data quality from Thomas Y Lee. I also had the awesome opportunity to meet and discuss personas and tech with Alan Cooper himself! 😃😃😃

Ready, Set Go!

Day 1: Client Background and Stakeholder Research

Our first step was to get to know our client and understand their goals. Bennett Wetch and Kate Williams from Fair Trade gave us an introduction to their organization and the importance of a better designed data collection system.

“Data collected is a reflection of what is happening on the ground with Fair Trade benefits. It drives our decisions and strategy for brand engagement and producer benefits.”
— Bennett Wetch, Director of Technology Innovation at Fair Trade USA

Primary Stakeholders:

Being a curious person, my mind was soon buzzing with a lot of questions for Kate and Benett. To maximize the information we gathered, we broke out in smaller teams and came up questions around different topics. A combination of the background research and our interview session with Bennett and Kate gave us a clearer picture of our client.

1. For Fair Trade data collection methods needed to be: More scalable, economical and have higher quality.
2. Existing methods presented data that was a mix of qualitative and quantitive inputs. There was no way to compare all the data on a single metric.
3. Training new data collectors and convincing farmers to provide data was the biggest hurdle in effective data collection.

We will provide statements:
We created rough problem statements that linked the solution, goal and target user together in quick ‘we will provide’ statements. 
Example: We will provide streamlined processes in order to collect high quality data for Fair Trade.

💡 This was an amazing way to kick start our brains and get all our initial concepts out on the board. It helped me clear my mind of initial solution ideas and be open to absorb more information from our client.

We will provide_________In order to________for___________

Stakeholder Research
We conducted two sessions over Skype calls, with a coffee producer in Guatemala (Vanessa) and a supply chain manager for fisheries (Ashley). I moderated the call with Vanessa, supported by great follow up questions from my team.

💡Learning: The short time span we had with our client, forced us to boil down our questions to only the most critical ones only. Being used to the luxury of having enough time to plan research questions at work, we had to quickly adjust and be more careful about what we asked our stakeholders.

Day 2: Research synthesis and Building Journey Maps

Based on our research notes, we went about creating categories of research insights. We divided ourselves into new groups and tackled different insight categories.

Grouping research insights for Producers

Some insights that informed my designs:
1. Providing Data= cumbersome, opaque and lengthy
2. Inconsistent data collection methods
3. Being a part of Fair Trade was more than just $$ benefits. It was the structure that Fair Trade provides around business and community benefits.
4. Fair Trade training = self empowerment and growth

Producer Pain Points:
1. Only provide data. Never see the results or benefits of it
2. Giving data= spending time away from work, but time = money $$
3. Afraid that data collected will be used against them by Fair Trade

Producer Goals:
1. Want to benefit from data collected by Fair Trade.
2. Need to make informed decisions on business growth according to market needs.
3. Would like to contribute more to the community welfare based on Fair Trade benefits

As each team mapped similar goals and pain points for enumerators from the research rounds, within a short span of time we had gained more understanding about our end users. This helped us define our primary personas.

I loved the persona creation process in the workshop. Especially when Alan Cooper walked us through the importance of personas.😎😎
I especially liked the following quote:

“Make one person ecstatic, a million will follow.”— Alan Cooper

💡Even though I have worked with personas in almost every project, understanding its origin and seeing how passionately Alan walked us through them has really inspired me as a designer.

All throughout the rest of the workshop, I tried to focus on talking about my designs through the eyes of Carlos, our persona for a coffee farmer from Guatemala.

Journey Mapping
Based on what we had learnt about Carlos + information from Fair Trade, we then mapped out Carlos’s journey. Narrowing the scope for the journey map was particularly challenging due to the number of assumptions we were still making.

🤔 I felt that the limited time for user research was a major constraint for us throughout the four days. All our design steps were based on tons of assumptions, that we still needed to validate.

Journey Maps + HMWs for Carlos

We chose to map out Carlos’s journey from the time he gets certified with Fair Trade until he gives two rounds of data to the Fair Trade enumerators.

A lot of discussions, questions, clarifications and assumptions helped us populate all the swim lanes in the journey map to the best of our knowledge.

We then created How Might We statements to identify opportunities for innovation in this scope Carlos’s journey.

How Might We…Incentivize Producers to participate in Fair Trade data collection?

Day 3: Ideation

The ideation day consisted of a lot of short sprints of idea generation, followed by focusing on one set of ideas.

After a very exciting, fast paced idea generation process, with my team of 5, we finally synthesized our ideas down to three main goals:

  1. Tiers: engagement model by Fair Trade for producers such as Carlos
  2. Data feedback loop: Use data to create self sustaining career building methods to measure and address impact of being a Fair Trade farmer
  3. Focused training/ advice sessions for producers

Proposed Solution
The solution we proposed consists of two parts:

  1. Integrated data collection in the community:

We proposed the introduction of a community leader who is selected from each community. These leaders are then trained to be Fair Trade representatives from their community.

Their main tasks comprised of:
1. Collecting data from each community producer
2. Leveraging Fair Trade tools to share the data with Carlos and Fair Trade
3. Using the data collected to discuss and decide on training activities that the whole community needs

2. Tool kit of incentives:
We designed four buckets of incentives that Fair Trade could choose from to incentivize Carlos for providing data. These buckets could be mixed and matched, to allow Fair Trade to adjust their incentives according to what each community accepted and required.

Purpose Driven Incentive:

Material Driven Incentive:

Day 4: Pitch!

Friday was all about planning our pitch and figuring out the storyline for our presentation. I chose to present the problem statement and current journey map for Carlos. My most favorite part of the presentation!

One of the feedback points that Benett brought up inspired me to take this project forward. He asked us to explore how the questions asked during data collection could be derived from the incentives we provide to the producers.


1. Make one person ecstatic, a million will follow
2. Shorter timeframes for each task forced us to be precise and critical which could be translated into my everyday work.
3. Projects with a short timeline also forced me to work while making many assumptions. 
4. Personas are made of clay, they need to be molded and shaped as we get more inputs in the project.
5. I enjoyed bodystorming! Never tried simulating an app experience with people! Loved it.