Ecommerce Supply Management UX Research

UX research to optimize AI-driven ecommerce supply management

The Challenge

How might we create a platform that that streamlines customer processes and engenders trust?

Our Process

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

The Solution

Finding similar needs of all customers and understanding the source of inconsistent data would create more trust in the client’s offerings.

Our team at Standard Beagle applied our UX research expertise to solve the issues blocking the development of the platform.

Goals

  • 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.

Results

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.

Scope

The scope for this project included usability testing and user interviews, user persona development, and insight synthesis.

Constraints

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.

Implementation

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.

Understand

We started by asking stakeholders about their product, their pain points, and what they noticed in their interactions with customers.

Stakeholder Interviews

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.

Usability Testing

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.

Explore

Define

Affinity Diagramming

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.

User Insights

  • Data Integrity

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.

  • Forecast 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.

There were several points 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.

A lot of users mentioned how they wished their internal data matched up with the client data better. Some of these comments came from a place of wanting a seamless integration between the two different platforms. Another reason was due to the mismatched data and how it affects their work.

About the User

User Persona

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.

User Flow

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.

Validate

Key Takeaways

Insights

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

User Behavior

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

We also gave clarity around one of the user personas the stakeholders worked with.

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.

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