AI-powered food streaming and ordering app 01 | Meetfood

AI-powered food streaming and ordering app 01 | Meetfood

Generating revenue in 3 months

20K+
20K+

users onboarded in 3 months

10%
10%

click-through rate

20+
20+

restaurant partnered

SKILLS

Strategy

Product design

Information architecture

User research

Design systems

role

Lead product designer

Timeline

Spring 21 Fall '21

SKILLS

Strategy

Product design

Information architecture

User research

Design systems

role

Lead product designer

Timeline

Spring 21 Fall '21

Food discovery on social media often stalled before purchase, leaving opportunity on the table. I designed MeetFood to bridge that gap, transforming food videos into direct ordering experiences. Within three months, we partnered with 20 restaurants and generated revenue, fueling platform growth.

Food discovery on social media often stalled before purchase, leaving opportunity on the table. I designed MeetFood to bridge that gap, transforming food videos into direct ordering experiences. Within three months, we partnered with 20 restaurants and generated revenue, fueling platform growth.

Food discovery on social media often stalled before purchase, leaving opportunity on the table. I designed MeetFood to bridge that gap, transforming food videos into direct ordering experiences. Within three months, we partnered with 20 restaurants and generated revenue, fueling platform growth.

PROBLEM

When finding food through social media apps, foodies often get frustrated using multiple tools to order the showcased food

To delve into foodies' pain points and desires regarding online food discovery and ordering, I conducted surveys and interviews with our target audience.

The research revealed that users wanted a direct way to act on food content without switching across multiple apps.

strategy

Combine food videos with ordering, use AI for video recommendations, and make sharing tasting experiences easy

Based on research findings, I held working sessions with my cofounders to define our strategy.


  • Discover food videos nearby

  • Get AI-powered recommendations

  • Order through trusted delivery apps

validation

Validating idea with low-fidelity prototype

Based on the design strategy, I created low fidelity wireframes for users to test and establish the overall direction.

The onboarding process helps us understand user preferences. Using this data and location information, the algorithm suggests personalized video recommendations. Users can buy directly from the video screen through third-party apps.

Solution

Making onboarding easy

After users create an account, they can set their food preferences. I iterated design based on user testing feedback to discover the most effective way of allowing users to set their food preferences.

Using images with text for easier recognition, plus distinct styling to show selection clearly.

Optimizing home screen video layout

When designing home screen video layout, I explored options for displaying vary amounts of videos. My goal is to create an intuitive layout that promotes user engagement.

I conducted user testing to find out the optimal choice.

Testing showed users prefer viewing more videos at once, making it easier to quickly browse through various food videos and discover new dishes.

Simplifying same restaurant video exploration and return to main feed

When users select a video from the home screen or search results, they enter the video screen, where they can swipe up and down to view the next recommended video.

One important question emerged: when users are on video screen, how can they seamlessly discover more dishes from the same restaurant while easily returning to the main video feed?

I began with a design that guided users to the restaurant profile screen through the 'Explore restaurant' button, allowing them to view all videos related to a specific restaurant. Once a video is selected, users can swipe up and down to see the next video related to the same restaurant. However, user testing revealed that having to use the back button twice to return to the main video feed was inconvenient.

I went back to the drawing board to explore other options to simplify this process, aiming to solve the problem without requiring users to leave the video screen.

Exploration 1: A toggle button allows users to activate or deactivate the 'view videos related to the same restaurant' mode.

Exploration 2: Swipe left to access videos related to the same restaurant, swipe up and down to go back to main feed. User testing showed that users prefer this option to view same restaurant videos because of its simplicity and straightforwardness.

Eliminating wait time during video uploading

Because every video is user-generated, smooth uploading is essential. I streamlined the process so users dont have to pause, they can continue exploring while their video posts in the background.

Uploads complete in the background, and users get real-time posting updates.

impact

Rapid adoption

Over 20,000 users onboarded and actively used the app within the first three months.

High engagement

The platform delivered strong performance with a 10% click-through rate and 8% conversion rate.

Business growth

Partnering with 20 restaurants through influencer reviews generated revenue and expanded the platforms reach.