Autoscrap™ is an app designed to help people who are in need of a car part for the cheapest possible price. This app will also help those who have parts to sell move inventory with ease and maintain an online listing for any parts they have to sell. So the users are buyers and sellers alike and will hopefully have their interests met with our app. In this sprint, we are more focused on improving the usability of our app to make it easier for those who are not adept in the general use of computers, as well as, improve the experience for repeat users.
For this phase, we had our fellow UX researchers perform a Cognitive Walkthrough for each of our personas and scenarios. Each of our 3 personas had a scenario attached to them. Five Cognitive Walkthroughs were performed by outside UX researchers. Each Cognitive Walkthrough broke down a scenario into the steps they took and at each one they would answer some questions: Will the user know what to do? If the user does the right thing, will the user know that they did the right thing and is making progress toward the goal? These questions were answered and documented at each step until either the task was complete or could not be pursued further.
Our other main research method this phase was the use of informal feedback. We gave our fellow software engineers three questions to ask for feedback during their sprint I demonstration:
Is there any feature missing from the homepage that you think is needed?
How easy is it currently to navigate and find listings for parts?
Are there any changes you would make to make this more user friendly?
The rest of the software engineers in their section would give constructive feedback for these questions. Our software engineers documented the feedback and gave us the results.
Through our Cognitive Walkthroughs, we found key weaknesses and missing features needed in our application. This research method showcases how usable and learnable the current interface of the product is and where there could be improvements. All of the Cognitive Walkthroughs performed were unable to complete their task in full due to either missing features or confusion on where to go next. The tasks seemed doable up until being able to either put parts for listings or for actually being able to bid or buy a part after finding it. There was also confusion on whether our product was meant to host the part listings or if the user would be redirected to a new site to continue the process. Streamlining the process for finding and bidding on parts is paramount in keeping users from becoming frustrated and discouraged.
Through our informal feedback, we received multiple varied insights from outside software engineers for each of the three questions we posed. We saw that having a way to filter or sort the listings was needed for easier navigation. Another good missing feature suggested was using user car information to easily narrow down part searches. Finally we got some suggestions for other user friendly options like user reviews, bid history, and an auction timer.
The findings from both the Cognitive Walkthroughs and informal feedback revealed significant usability issues and identified missing key features. Users encountered difficulty navigating our application, particularly in tasks such as listing parts and completing purchases, where clarity was lacking. To address these challenges, we propose several UX design enhancements. Firstly, we aim to declutter our app interface, ensuring a clear task flow and seamless navigation for users. Secondly, implementing a search bar and filtering algorithm will ensure users are presented with relevant parts based on their car information. Additionally, integrating interactive features such as user reviews, bid history, and an auction timer can greatly enhance overall user satisfaction. User reviews offer valuable insights for buyers, fostering trust within the community, while bid history enables users to strategize their bids effectively and stay informed about market trends. Additionally, incorporating a timer for auctions adds excitement and clarity to the bidding process, making the platform more engaging. Moving forward, our UX team will continuously monitor user interactions and behavior to guide ongoing improvements, ensuring that our app effectively meets user needs.
It's important to address some considerations and limitations regarding the methods we used and the findings we obtained from our research. First of all, the limited number of users remains a challenge, leading to heightened competition and less feedback, which might hinder our ability to gather enough data on users' needs and preferences, as noted in our previous report. Additionally, while the cognitive walkthroughs and informal feedback sessions offered valuable insights, they might not have fully revealed certain user experiences or perspectives. For instance, many of our feedback providers may have limited or no experience working on cars, which is our main audience. Furthermore, it's crucial to recognize that while wireframes are helpful for early-stage design exploration, they might not precisely showcase our final product's appearance and functionality, potentially affecting how users perceive and provide feedback on it. Additionally, some elements were missing from our wireframes during the cognitive walkthrough, which might have influenced participants' understanding and interaction with the interface. Even though our methods gave us helpful information, it's really important to remember these limitations and try to provide other research methods to keep enhancing our application.