illustration of food and a virus particle

Food in the time of Covid

A qualitative UX research study
The pandemic has been an unparalleled time of stress and upheaval for so many people. I wanted to discover what those life changes meant for people, particularly what impact they had on their previous routines with food. During this time, people have been spending a lot more time at home, and the ways they access food have changed. The types of foods they have access to/seek out have changed as well. I wanted to uncover any insights that might help people to deal with those changes in their food habits brought on by Covid-19.
Background Info
Role: Solo project - worked on research + synthesis + research presentation.

Timeline: Total time - 5 weeks. Establishing research goals and moderator guide - 1 week. Recruitment and Interviews - 2 weeks. Synthesis and deliverable creation - 2 weeks.

Final deliverables: Research readout prepared for stakeholders of a food habit tracker app.

Research Statement

The purpose of this research was to assess in what ways people's eating habits have been impacted by changes in their work and life routines due to Covid-19. I wrote some research objectives to help me make that assessment.

Research objectives
• Were users able to maintain their dietary habits? What changes have they experienced in their dietary habits over the last 2 years?
• Where do users spend most of their money on food during the pandemic? What foods are they eating?
• How has Covid-19 impacted snacking habits or eating for reasons outside of hunger? How has it affected users’ relationship with food?

I let these objectives guide the rest of the research - from writing the interview guide, to the synthesis and insight forming at the end.

Methodology & Participants

I used qualitative user interviews for this research. I conducted five 20-30 minute virtual interviews with five different participants. Interviews were chosen as the primary methodology because I wanted to tap into the user's experience in their words - and understand better how they perceived changes in their habits over the last 2 years.
Two people in a virtual interview
I asked my very gracious family and friends to participate in this research, and they kindly obliged!

The target participants: People whose work situation had been fundamentally impacted by Covid. This meant people who had lost their employment due to Covid, or had their work life changed dramatically - for example, moving from an office to working from home. These were people who were now spending a significant amount of time at home, what did that mean for meals and routines?

All 5 participants in the study fit our target profile - they had all, in some way, had their employment impacted by Covid-19. Some lost jobs, some moved from a full time office position to remote work, and some left their jobs due to new challenges presented by the pandemic.

Sample Questions & Moderator Guide

"Has Covid-19 changed the way you order and pick up food? How so?"

"How would you describe your relationship with food? Have you seen changes in that relationship since the start of the pandemic?"

"Are there any foods you’ve been eating more of during the pandemic? Alternatively - anything you’ve been eating less of?"

Analysis & Synthesis

I transcribed and edited all the interviews, and coded them using these groups:
A table of coding groups used in the interviews
I wanted to understand my participants better - better understand their behaviors, and their feelings about those behaviors. That's why I chose these particular groupings. I went through the transcribed interviews, and used the color coding you see up there to mark up the text by group.
sample of the interview color coded by group
After that it was time to pull out the virtual stickies! I started to affinity map out all the coded quotes I had highlighted. First I organized them by user and coding group, then within each coding group, I started matching up similar responses from different participants, and giving those similar responses a category name.
a virtual white board with sticky notes organized into groups
My goal was to move from the more highly specific details, to general insights that could both speak to the research objectives, and that I felt could lead to actionable recommendations. The organization never stops. I organized the categories, then put similar categories into buckets with a general theme that kept popping up in the responses.
themes grouped into circles and labelled with a description
I looked at the themes that appeared from my new buckets, and from there discovered the insights I would present.
3 insights from the research with an illustrated background


I created a research read out designed to be presented to stakeholders working on a food habit tracking app. The presentation gave details on the context of the research and the participants, and delivered key insights. From those insights I delivered useful recommendations for the food habit tracker app that would address the things I found - how might we deal with the dietary habit changes brought on by the pandemic?

Check out the full presentation here.
introduction powerpoint slideexample of a powerpoint slideexample of a powerpoint slideexample of a powerpoint slide
What's next?
  • Set scope and requirements of the food habit app from the business side.
  • Begin ideating on a habit tracking app, keeping the recommendations in mind as key features.
  • Competitive analysis to see how similar apps are tackling a Covid-19 world.
What went well?
Coming up with a synthesis process that worked well for me, that I can apply to future projects. I got to work on my presentation skills (always nerve-wracking and always necessary) and research read out was received well.

What needs improvement?
The interviewing process is an ever-developing skill for me. Becoming more comfortable with stepping away from the moderator guide and asking off the cuff questions. I used a digital transcription service, which required a lot of editing, and therefore a lot of time. I'd like to try manually transcribing to compare the amount of time spent.