Case Study: Craigslist Redesign
Overview
This case study was a semester long group project for my Human Computer Interactions class. The assignment was to evaluate and redesign sections of an eCommerce site of our choice in order to expose us to the entire UX research and design lifecycle and several of the key processes within.
Craigslist is a site meant to sell a variety of items and services to its consumers. As such, the GUI should be easy to navigate and allow users to quickly access the items they want. However, the structure of the site is fairly outdated and the visuals are disorganized and don’t lead the user. This provides us a variety of options on the GUI elements to redesign.
Goals
Improve design/aesthetic,
organization,
ease of use
My Roles and Responsibilities
Create Empathy Map, Heuristic Evaluation, Prototypes etc.
Tools Used:
MURAL & Figma
Process
Our first step was to analyze the problem and how we can solve it. From there we went on to choose two users of Craigslist and create a user/task matrix with at least tasks they would perform on the website.
Empathy Map
Heuristic Evolution
We created our heuristic evaluation from a buyers perspective based on Jakob Nielsen’s 10 usability heuristics. We were able to use the findings from the heuristic evaluation to develop our design.
Final Design
Usability Test Script
Although we weren’t required to perform a usability test, we created a usability test protocol which we would use to test your prototype.
Two metrics we are capturing
➢ 1. Total task time/Time-Based Efficiency Metric
The time it takes the user to complete the whole test and to find an apartment sofa (via any method i.e., filtering, etc.), ‘favorite’ the appropriate listing, and email the owner.
The data we need to gather is the total number of tasks, the number of users, and the time spent by each user to complete each task. We will also collected the total time it takes the user to go through the experiment from start to finish (that will also be timed).
The moderator will assign the participant to a computer, read out the task script, and hand them a list of instructions/tasks to complete. One observer will keep track of the time it takes for the participant to complete as many sub-tasks as they can. The other observer will keep track of the time it takes the participant to complete the entire test. The notetaker will keep track of this data on a data sheet. Once the participant finishes the last task, the moderator will ask the user to sign out of the computer and go to another room to participate in the post-test procedures. The computer will be reset, and the next participant can come to start the test.
➢ 2. Success completion rate metric
The rate at which the user is able to successfully complete each task.
The data we need to gather is the completion rate of each task, per participant, which will be calculated by assigning a binary value. ‘1’ means the participant successfully completes the task, and ‘0’ means they partially completed it or cannot complete the task successfully. Using this strategy, we will measure the success rate by ((number of tasks completed successfully/total number of tasks attempted)) * 100% in order to get the success rate per task.
The moderator will assign the participant to a computer, read out the task script, and hand them a list of instructions/tasks to complete. One observer will note how many tasks they have attempted. The other observer will keep track of each task they either successfully complete or fail to complete. The notetaker will keep track of this data on a data sheet. They will then calculate the total success rate percentage of tasks. Once the participant finishes the last task, the moderator will ask the user to sign out of the computer and go to another room to participate in the post-test procedures. The computer will be reset, and the next participant can come to start the test.
