Finding an Open Table — with OpenTable
By: Sara Choi
Tags: User Research, OpenTable, Dining, Design, User Experience

Cornell University has been lauded for bringing students back to campus and successfully containing virus cases this fall. Coming back to Ithaca this semester, however, I knew the university’s plans meant a lot of fundamental changes to daily activities like eating at dining halls.

Cornell recently partnered with OpenTable to regulate dining room capacities and safely distance students who want to get takeout, encouraging us to download the app and make reservations ahead of time. It’s worth noting that OpenTable is part of Booking Holdings, an engineering company that services international travel and booking search engines, so its main users aren’t college students.

This poses a few problems specific to the college experience because dining halls don’t function the same way as public restaurants. Colleges have their own student meal plans and payment and check-in systems in place, which may not align with the policies of public restaurants.

In this case study, I explored filtering for more relevant information on OpenTable through a search by categories feature.

Problem Space

Initial Thoughts

Based on my experience with the app, I expected other students to have run into the same issues I did, such as finding the hidden search bar, realizing the “missed reservation” notification system isn’t synced with Cornell’s official GET check-in system, and figuring out the notifications about rewards don’t apply to college dining halls.

Current Search Feature

Current Filter Feature

Before conducting user research, I started with a tentative people problem:

OpenTable allows college students to make reservations at dining halls ahead of time. However, it is hardly used because: 1. Using the app requires a lot of guesswork. 2. Users consult multiple apps to get the information the OpenTable app doesn’t provide.

User Research

Users

On OpenTable, there are two main types of college-age diners:

Occasional: Students who live off-campus and are not on a meal plan. They occasionally visit dining halls and rarely use the OpenTable app. Frequent: Students who live on campus and are on a meal plan. They visit dining halls frequently for their meals and use the OpenTable app each time to make a reservation.

My goal was to identify key pain points in the reservation process that might be discouraging students from using the app by answering these questions:

What barriers do users face when making a reservation on OpenTable?

How do users get the information they need to make a reservation?

How does the pandemic influence users’ dining decisions?

Interestingly, trends in my results showed that before users can even make a reservation, they have a lot of trouble finding the place they want to eat at in the app.

Key insights

Most users navigated to the search feature tab first to look for a search bar.

Users couldn’t see dining halls until they specifically searched for them.

Users prefer takeout over dining in to save time.

Users were unsure if they successfully made a reservation.

New People Problem

OpenTable allows college students to make reservations at dining halls ahead of time. However, it is hardly used because:

They have a hard time finding relevant search results. The app doesn’t communicate enough information about reservations to users.

Figuring Out What Feature Space to Improve

Brainstorming

Virtual Brainstorming Session

I recruited my friends Vivienne and Trevor as brainstorming buddies. After exploring and narrowing down the solution space, I decided to pursue one of three possible features:

Add separate rows for college eateries and dining halls in search results

2. Sort by eatery type

3. Sort by different payment options

However, after discussing this with my peers, I decided it would be best to combine the last two ideas into a single, overarching feature related to searching by categories within the OpenTable app.

Content

Users were frustrated because they couldn’t find relevant results very quickly with the current search feature. After sketching a few of my ideas, I identified some key feature requirements for the feature:

Advanced search Federated search Search result filters

Finding an Entry Point