The Background
When companies have overstock or returned inventory, they often sell these items to liquidators at a reduced price. Then, the liquidators group these items together on pallets which they sell for a flat rate to the public. In most cases, the buyer is unable to see everything that is on the pallet before purchasing. Most people who purchase the pallets then sell the items individually at a highly reduced rate in the hopes of turning a profit.
The Problem
The client for this project was a retired real estate agent who got into the liquidation pallet business as a way to keep his mind sharp and make a little income on the side. He quickly found that in order to get the most out of each pallet, there was a lot of research and gambling involved. He came to us asking for an app that would:
streamline the research process
minimize the gambling risk
track inventory and sales of the individual items.
The Process
Cognitive Task Analysis
In order to better understand the pallet buying process, I completed a cognitive task analysis with the client. I accompanied him to the liquidation warehouse where he often purchased pallets to observe his process, as well as the processes of other customers. Our client used a combination of QR or bar code scanners, Google Lens, and standard Google searches to determine the lowest retail price of visible items. He needed to use at least one of these tactics for each item that he could see on a pallet, and then keep track of each price either in his head or in another separate app. This method left a lot of room for error, especially for retirees like our client.
Requirements Gathering
Once I had gained a better understanding of the process, I complied a list of potential features for the app. Once I had this list, I completed a MoSCoW analysis with the client to determine what would be needed for an MVP.
Prototyping
Our client was very hands on, and wanted to be regularly updated on the project status. As a result, I met with him nearly every week to deliver progress reports. Each time we met, the client would provide feedback on what I had created, and requested changes or additions. During these meetings, I frequently needed to educate the client on design thinking process, as he had no prior development experience or knowledge of best practices.
User Testing
Once the prototype was complete, and the client was satisfied with the state it was in, I began user testing. I conducted the user testing remotely, utilizing the research subject pool maintained by Penn State Erie’s Psychology department. I tested six total users, having them complete a predetermined set of tasks within the prototype, and then discussing their experience and overall thoughts. Once I had gathered my data, I complied it into a report and presentation for the client, highlighting specific errors and pain points that the users encountered, recommending specific changes to resolve those issues.