Munch Match: Making Group Dining Decisions Easier

Project Overview

Munch Match is a mobile app concept designed to solve a surprisingly common problem: deciding where to eat with a group of people.

We’ve all heard someone say “I’m fine with anything,” only for every suggestion that follows to get turned down. Munch Match was created to give that phrase a little more meaning. Instead of asking everyone to come up with a restaurant, the app gives the group a shared selection of options and lets each person privately decide which ones they would actually be willing to eat at.

The goal was to create a simple experience that reduces some of the anxiety and frustration that comes with making a decision as a group.

The Problem

Choosing a restaurant becomes increasingly difficult when several people are involved. Everyone may have different budgets, dietary needs, preferences, and ideas about how far they are willing to travel.

The target audience for Munch Match is anyone who struggles with making decisions when those decisions affect other people. The app needed to help users find options that worked with their location, budget, dietary restrictions, and preferences while making sure everyone was choosing from the same set of restaurants.

Rather than asking:

“Where does everyone want to eat?”

Munch Match asks a much easier question:

“Would you be okay eating here?”

That small change became the foundation of the app.

The Solution

Munch Match uses a lobby-based system that allows a group to make the decision together.

One person creates a lobby and invite the rest of the group to join. The app then generates restaurant options based on information such as location, budget, dining, preferences, and allergy information stored in each user’s profile.

Users swipe right on restaurants they would be happy with and left on restaurants they don’t want.

If everyone swipes right on the same restaurant, its a Much Match.

The session is designed to last no more than two minutes. If the group doesn’t reach a unanimous decision before time runs out, the restaurant with the majority of votes becomes the group’s match.

This keeps the experiences quick while still giving everyone a voice in the decision.

Designing Around Real-World Restrictions

One of the more important considerations for Munch Match was determining what should happen when the group couldn’t agree.

Simply choosing a completely random restaurant could introduce the same problems the app was supposed to solve. Instead, Munch Match prioritizes the group’s existing preferences.

If necessary, the app can gradually loosen filters such as budget to find additional options. However, allergy information is never removed from the search criteria.

This was an important distinction because some preferences are flexible, while others directly affect whether a restaurant is safe or accessible to a user.

Creating a Different Kind of Restaurant Picker

During my initial research, I found that many restaurant decision tools use a random wheel or roulette system. These tools are fast, but they don’t necessarily account for whether everyone in the group actually wants the result.

Munch Match approaches the problem differently.

Instead of randomly choosing for the group, the app looks for the overlap between everyone’s choices.

The concept was also designed around larger groups. My original project brief proposed allowing up to 15 people in a lobby, making the experience useful for groups of friends, families, coworkers, and other situations where more than two people need to make a decision together.

User Experience

The core user flow was designed to stay as simple as possible:

1. Create or join a lobby → A host starts the session and invites the group.
2. Set preferences → Location, budget, dietary needs, and other preferences help determine the available restaurants.
3. Start swiping → Each person privately accepts or rejects the same restaurant options.
4. Find the overlap → Munch Match compares everyone’s selections.
5. Get your match → A unanimous choice wins immediately; otherwise, the app determines the best option when the timer ends.

The swipe interaction makes the decision feel less like a group debate and more like a quick activity. More importantly, users don’t have to defend every choice they make. They simply decide whether they would be willing to eat somewhere.

What I Learned

Munch Match helped me think beyond what an interface should look like and focus more on what the experience needs to accomplish.

The biggest lesson from this project was that a useful solution doesn’t always require eliminating choices. Sometimes the better approach is to change how people make the choice.

Instead of trying to find everyone’s favorite restaurant, Munch Match looks for the restaurant everyone can agree on.

That distinction helped shape everything from the swipe mechanic to the lobby system and preference filters. It also pushed me to consider edge cases, such as what happens when users can’t reach an agreement or when certain filters conflict.

Ultimately, Munch Match became an exercise in using UI/UX design to simplify group decision-making while still allowing each person to have an equal say.