By analyzing usersβ buying and consumption patterns, the app provides data-backed recommendations to regulate and optimize π grocery buying behavior. The application integrates fridge ποΈ and pantry inventory into a single platform making data accessibility easy and efficient. In addition to its intelligent capabilities like competent shopping support π₯, shelf-life estimation β, and smart recipe suggestions.π¨π³
A survey by BuySmart found that 100% of respondents don't use any app to manage their groceries, despite challenges in managing household inventory and multiple app options. After primary and secondary research, the main issue was found to be proposed solutions relying on user input, which users don't incorporate into their daily lives and therefore lack motivation to continue using the apps.
All team members gathered together and took 30-45 min to read through the findings from the interviews. We also discussed the persona and its challenges/motivations - which gave all team members a better idea of our potential customers.
Now, we took a 25 min quick brainstorm session to come up with feature suggestions and write it on post it notes,
which helped us rapidly come up with ideas.
Next, we categorized the features into broad categories: Meal planning, Recipes, Gamification, Shopping, Inventory, Alerts/Notifications.
Now, we used the dot-voting method for all of us to go through everyoneβs ideas and vote for the ones they feel work better. Later, for the post-its with zero votes, we as a team talked and discussed to see if they should be eliminated or considered.
If given more time, I wouldβve ideally wanted to come up with Design principles to filter out ideal features & ideas. This would have helped us come up with better criteria than effort & impact.
