The idea of reLabel.it started with the founder’s frustration with food labels. Even though we were not the first to try to solve the problem of translating confusing nutrition fact labels, we took an entirely different approach to design.
We didn’t want just to make regular labels better; we wanted to create an app that would provide a complete experience: simple, personalized and intuitive grocery shopping assistant.
Occupy Whole Foods. When I started working on this project, the first question I had in mind was “what do people actually look for on food labels?” I took the entire team to Whole Foods to observe shoppers and engage in casual conversations about food quality and diet.
What do people actually look for on food labels?
The first important thing I noticed was that there was a significant number of shoppers carefully examining food labels. I started conversations with them and asked what information they were trying to find. We talked about their diets and frustrations with ingredient lists and nutritional breakdowns.
Seeing Patterns. After a day spent in Whole Foods, our team had piles of notes and quite a few stories. When sharing our findings, it became clear that there were clear patterns in what people were looking for on food labels.
We started putting words that we heard people often say on sticky notes and arranging them in some basic mental model. There were surely three different types of shoppers that could be our potential users: people with health concerns like diabetics, people following a certain diet like vegetarians and vegans, and health conscious customers.
There were three patterns of what people were looking for in food labels… That was exactly what we wanted to highlight in our app
Mental model and three personas that we created became the basis for the app. All existing apps at that moment didn’t solve the problem of making shopping easier. We wanted to help people by building a personalized experience that would highlight what is relevant to a particular user and her concerns.
There were three patterns of what people were looking for in food labels: ingredients they could absolutely not have because of specific health conditions or diet, ingredients that they tried not to consume, like artificial colorings and preservatives, and finally ratios, like sugar to fiber and good fat to bad fat. That is exactly what we wanted to highlight in our app.
We wanted to make it as simple as “Yes, buy it”, or “No, it has soy.”
Buy or Not to Buy. Through customization flow, users could choose their diet preferences and concerns, and the app would automatically look for specific ingredients in food labels giving the users just the information they needed. We wanted to make it as simple as “Yes, buy it”, or “No, it has soy”.
It was imperative for me to apply our research and findings to the final design. That is why specific food concerns were the first thing users would see after scanning a label. The ratio of bad fat to carbs and fiber to sugar come next, and finally other commonly tracked ingredients, like sodium and proteins.