Research
We planned to test grouping dishes by useful themes for the user. To do this, we conducted a quantitative study to identify the most important dish parameters for users.
To conduct the study, we created a survey and showed it to Unimeal users who had used the recipe swap feature.
We first asked an open-ended question to gather unbiased responses and uncover new insights. Then, we followed up with a matrix question based on our prior research.
The open-ended question didn’t provide new insights, but it confirmed our choices for the next question. 😎
We then calculated the weighted average of responses to rank the parameters based on user ratings.
Unfortunately, I can't show the full image due to confidentiality reasons and my commitment to the signed NDA 🤷♂️
Solution
In the first iteration, we grouped the recipes based on the most important parameters for users.
In the second iteration, we focused on one of the most important parameters — ingredients.
We combined this with insights from open responses and previous research, leading to the implementation of a search by recipe name and ingredients.
Conclusion
We learned the most valuable parameters users consider when choosing a dish. The research helped us make more informed decisions and changed our perspective on the importance of specific parameters.