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Designing an AI Testing Platform

Overview

Global App Testing (GAT) helps businesses ensure their software quality through crowdsourced testing. In order to meet revenue targets, the product team was given the challenge of integrating AI and machine learning into the testing processes. After brainstorming, we decided to focus on creating an AI-powered platform to assist Test Managers. My early assumption was that users would be skeptical about AI taking over parts of their job. I conducted extensive user research to figure out how to introduce AI in a way that would appeal to users and meet the busines goals.

The outcome

My contribution

UX/UI Design
User interview
Prototyping

The team

1 Designer
5 Engineers
1 Project Managers
1 Data Scientist
Global App Testing SaSS Dashboard mockup

Understanding the problem

As this project tied in directly with a key business goal, before conducting any research or design work I wanted to ensure I had a strong understanding of the reason for the project and what the business would consider a successful outcome. GAT was looking for opportunities to reduce operational overhead and free up Test Managers capacity.

User research

We ran weekly user research session to observe Test Managers navigating their current processes. From this study we discovered the following insights:

Image of Miro Board where we map out all Test Manager tasks
Image of spreadsheet Test Managers were using

Designing the solution

Solution design involved user testing and multiple iterations. High-level logic was mapped out, followed by prototypes. We explored various options, particularly around automating decision-making processes. The challenge was presenting complex testing data in a simple, easy-to-understand way while incorporating AI assistance.

Image of the software as low fidelity wireframe
Image of the software as Hi-fidelity mockup

User feedback

Prototypes were iterated on after remote user testing sessions. Users were asked to complete a full testing cycle using the designs. We observed their understanding of the AI-assisted process and followed up to understand how they expected the new system to impact their workflow.

The result

The final design transformed the way Global App Testing Managers run the testing process. The new platform stores and tracks data previously managed in spreadsheets. It uses machine learning and AI to automate most of the Test Managers decisions and actions.

Where do we go from here?

First, I would recommend conducting usability testing again with new participants. Have the changes made it easier for users to complete their tasks?

If usability testing is not an option, I would recommend tracking the following metrics:

What I learned

Communicating design decisions in light of the business goals.

It is much easier and natural for me to explain my decision decisions based on user insights. However, it is equally valuable to consider how those decisions also support the business goals.

Next Project

How I designed a testing platform that increased efficiency by 35%


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