In the summer of 2018, I had the opportunity to intern at Groceristar, a Ukrainian startup focused on simplifying meal planning by using machine learning. My role as a UX Designer was to design and build the MVP of their flagship project - ‘Meal Planning UX.’
In the modern world, we are always caught up in a constant rush -- to work and eat unhealthy meals on autopilot. Researchers call this “mindless eating.” It is highly necessary to eat healthful foods and also save time and money while planning meals.
Groceristar’s Meal Planning UX allows people to browse menus, plan meals and be aware of the calories they consume on a certain day. It allows people to set diet plans and save money, using machine learning algorithms.
It can be said that each individual is different from the other.
Our user demographics can be categorized into three types:
People who not are aware of the calories they take in and want to set diet plans
People who want to explore new menus, different cuisines
People who want to buy food smarter by saving money and time
Our goal was to simplify the process of how a user buys food items and chooses recipes. The average user flow of actions consists of five steps, while we have simplified it into three steps.