Comprehensive usability testing of the FastFood App, yielding actionable insights

A summative usability case study to assess the effectiveness of the FastFood mobile application for food delivery in different scenarios and gather insights to help improve the application.

The video is uploaded with the participant’s consent and intentionally muted.

Roles and responsibilities

A team of 5 members performed the usability test where each individual evaluated the FastFood app based on Nielsen Norman Group’s 10 Usability Heuristics and the severity of the issue. Collaboratively, we worked on feature comparison and SWOT analysis for the application. We divided our work of recruiting and interviewing 5 participants and where we tested 6 sets of tasks. Further, we suggested design recommendations based on issues and findings across the interview, as well as the assessed System Usability Score.

Testing Approach

Research Design
Data Collection
Data Analysis

Heuristic Evaluation Summary

For heuristic evaluation, we used Nielsen Norman Group’s 10 Usability Heuristics to evaluate the interface of the FastFood App. We analyzed every screen based on the rules of thumb to measure the usability independent of walkthroughs. Overall, Consistency & Standards, Aesthetic & Minimalist Design, and Visibility of System Status were major violations in the design. A few insights from the report are mentioned below:

Competitive Usability Evaluations

We conducted a holistic feature and design comparison to evaluate how direct and indirect competitors perform in relation to the FastFood app. We did a SWOT analysis to assess what competitors are doing, how they’re doing it, what’s working, and what’s not.

Competitive Analysis

Usability Testing Overview

Affinity Diagram: Issues per task

After conducting a usability test with five users between the ages of 24 and 32, we transcribed the recordings and examined the problems users encountered with each activity. The top three heuristics were used to group common problems. We listed the problems caused by the Figma tool itself, and we also included the tasks that went with no problems at all.

Issues per task
System Usability Score (SUS)

Overall, users felt comfortable while performing the first three tasks, however, they faced many difficulties while performing the other three tasks. Through the SUS tests, the FastFood app earns an average score of 70.5 which is higher than the SUS benchmark of 68. In addition, the score of 70.5 represents that our participants accepted the FastFood app. Although the app was acceptable, we gained a grade of C on SUS tests which indicates our participants face some difficulties throughout the usability tests.

SUS score

Observations & Recommendations


Review the application’s information architecture. Before beginning design, think about developing a feature blueprint and user testing the way the features are organized.


To understand users’ mental processes and get their opinions of the program, we used a think-aloud protocol.


Font sizes and colors need to be more extensive to ensure readability and avoid eye strains as per WCAG guidelines.

Making it intuitive to the real world

Add helper text, mandatory fields, buttons, and necessary features that are required, such as the “deliver to” or “edit address” in the location screen. Rethink the placement of features, such as “Delete Account” or “Select User” and place them in the expected menus.

Access to system status

Re-evaluate the interface to keep the user informed about the progress. This includes showing the delivery charges upfront and providing all the contact support options.

Simplifying the app

Some screens can be completely removed and in other instances, many screens seem to overwhelm the participants because of the information overload.


Diversify pool of testing participants: Increase the diversity pool by enlisting participants from diverse backgrounds including individuals with impairments. This would enable us to investigate how their experiences and capabilities influence their preferences for food delivery.
Rigorous dry run: Invest additional time in making sure everything is operating as intended because the tool's screens took a long time to load during the initial test. To ensure the test flowed as smoothly as possible, performing a few dry runs beforeeferable beginning is preferable.
Researching for a diverse user base before designing: A broad set of user knowledge, experience, and background is required which will help ensure that the app wasn't solely aimed at experienced users. Concrete research would help us pursue various design solutions.