Ecommerce Supply Management UX Research
UX research to optimize AI-driven ecommerce supply management
Our client is developing a platform to uniformly digitize their current data management offering for their customers.
Many of their customers receive inventory recommendations in the form of spreadsheets sent via email. Any changes to business logic or data must be done by the client in the back-end of their algorithms and services.
The client wants to create a uniform platform that will meet all their customers needs, however there are several concerns they wish to address before moving to development in earnest.
- Customers say they don’t completely trust the data given by the client
- Each customer has specific needs that are not uniform across the industry
- Because each customer company is organized differently, the user personas are unclear
How might we create a platform that that streamlines customer processes and engenders trust?
The scope for this project included usability testing and user interviews, user persona development, and insight synthesis.
We gathered data over a 3 month period. Users had limited time to meet for prototype testing, and several users were in global time zones. In a few instances, scheduling did not allow for a complete prototype test.
During our process, we worked closely with the client to understand the industry and connect to their customers. We iterated on our test guide with stakeholder feedback.
Our team at Standard Beagle applied our UX research expertise to solve the issues blocking the development of the platform.
- Find the origin of customers’ distrust.
- Get a clear picture of the user personas the client was missing.
- Understand the users’ task flows and recommend how to accommodate it into the platform.
We needed to find similar needs of all customers and understanding the source of inconsistent data would create more trust in the client’s offerings.
We recommended adding data points relating to warehouse capacity and increasing transparency in communications to gain customer trust in the new product.
We also made recommendations to the prototype UI so that stakeholders can better understand their customer’s task flow.
Ultimately, we validated the client’s assumptions about their users, provided more insights into their customers’ behaviors and work flow, and reiterated the need for dedicated user research for their UX team.
We started by asking stakeholders about their product, their pain points, and what they noticed in their interactions with customers.
Along with the client kickoff meeting, we interviewed 3 stakeholders in depth to assess what questions their team needed answered. Their biggest questions were about:
- their customers’ workflow
- the cause of the distrust with the client offerings
- what information would their customers need to bolster their offerings.
We were also given access to an early-stage prototype. Within the prototype we needed to know if the metrics and data points offered were valuable to customers, and if not, what data would bring value. The client also wanted to understand the customers’ workflow and how to better align the prototype to meet it.
For this project, user testing was performed via Zoom. We tested 7 users with the prototype (2 were internal client employees, 3 were performed by the client), and 5 user interviews.
With three of the users, it was brought to our attention after initial blind usability tests that English may not be their first language, and therefore we would need an interpreter. In order to facilitate a smooth test with another person present, we created a guide for intermediaries.
We organized all of the responses to our tests onto a Mural board. After transcribing all data onto sticky notes on the board, we first sorted cards by certain categories
- User thoughts on a particular function within the prototype
- What confused the users
- What users found limiting
- What users found important
- Data pertaining to the User Persona the client wished to know
From there, other groups were formed to give further insights. Within these general groups, we created more specific data points.
Users had to juggle internal information against the client’s information on product dimensions and quantities, which added extra work to their flow.
Insights and Opportunities1
The most important piece was information around item size and weight. From this information, they could figure out larger issues around capacity to carry the items and speed up their workflow.
Forecasts and trends
Users liked to see this data, but they were unclear how these trends were being calculated. One user noted that they had addressed the confusion with the client but it was never answered.
Insights and Opportunities2
Lack of communication around the calculation of trends and forecasts created mistrust around the client’s data.
Lack of data
There were several points of data that users found were important to have, but felt they could not trust the data from the client. They acknowledged the data inconsistencies stemmed from their own data, but also admitted the client did not have access to all data points they deemed important.
Insights and Opportunities3
The client needed access to data in order to give accurate data to their customers.
Many users mentioned how they wished their internal data matched up with the client data better. They wished the client tools would synch seamlessly with their internal tools.
Insights and Opportunities4
Users wanted a seamless integration between the two different platforms to save time comparing and translating data between them. They felt this would help solve their issue with mismatched data and how it affects their work.
We developed a user persona for one of the two users that stakeholders are in contact with. The client wanted to know more about this persona to understand how their current offerings are not meeting their needs.
From our interviews, we determined this persona’s most common role within a company, the departments they communicate with, the data they oversee, how they utilize the platform, and their major pain points.
The user flow was difficult to discern due to usability issues with the prototype. Users did not know what steps to take within the platform, and problems with the UI did not help to lead users to their goals.
In order to get information about the data displayed on hard-to-find pages, we had to directly instruct users where to find the correct button or page. In this way, we were unable to discern if the user would naturally turn to these pages and the information they offered.
Stakeholders had several assumptions that our testing and interviews validated. These were:
- certain data points were very important to users (mostly data that would help determine space in their fulfillment centers)
- certain features on the prototype added value to the platform, especially if it were used as a tool to automate inventory assortment
- a glossary function was very helpful to users
Through our testing, we determined that users did not have enough guidance through the platform to determine their natural task flow. We gave recommendations for future iterations:
- Several UI changes to the prototype to ensure future testing would give more insightful results.
- Adding a dashboard screen after login with a task list
- In-platform help guides
The Importance of UX Research
We gathered the results from our research and presented our findings. Stakeholders were pleased with how insightful our result were, noting how a dedicated user research team would benefit the company.