context
Ex Machina is a canvas-based data analytics platform that enables anyone to develop, scale, and apply AI/ML insights without writing code. I collaborated closely with the product and engineering teams to deliver various key features in Ex Machina. I created a new product-led onboarding experience to increase retention rate, implemented effective error handling mechanisms and designed intuitive experiences for complex data preparation and analysis capabilities.
users
Syd, 28
Data Analyst at Good Foods
Primarily engage in data cleansing, visualization, and manipulation tasks to generate actionable plans
Familiar with performing data transformations on small datasets using tools like Excel
No data science or programming expertise
problems
📊 Competitive analysis
Our team conducted an in-depth analysis of key competitors within the market. This process involved evaluating their product features, user experiences, and strategies to identify potential opportunities, strengths, and areas for differentiation.
👥 User interviews
We conducted user interviews with a diverse group of 12 external target users. This group included individuals with various roles such as data analysts, sales strategy associates, business analysts, and cyber risk and regulation analysts. We used a combination of semi-structured interviews and think-aloud tests.
🧐 Heuristic evaluation
The design team conducted a heuristic evaluation of the product to delve into usability issues and identify areas with high severity ratings. This evaluation aimed to gain a deeper understanding of the challenges users might face and prioritize the issues that require immediate attention.
[problems]
what are the key insights from research?
1
First-time users struggled to understand product value
When users first land on the homepage, they encounter a lack of guidance and unclear next steps. This leaves many unsure of where to start or what the platform offers, making it difficult to grasp its value quickly.
2
Users needed more learning resources and documentation
When users encountered challenges during a project, they struggled to find adequate resources and clear documentation. This lack of support made it difficult for them to resolve issues independently, often leading to frustration.
3
Users frequently encountered errors but lacked guidance to resolve them
Users experienced errors even before starting their tasks, with no clear instructions on troubleshooting or resolution. This led to confusion and stalled progress, as users were unable to understand the root cause of issues or how to proceed.
ideating
We explored various directions to improve onboarding, documentation and error handling. After evaluating the potential impact and effort required for each option, we prioritized the most valuable features to focus on.
keywords that guided our design
1
Usable
The new design ensures ease of use, providing a straightforward interface and intuitive navigation that empower users to complete tasks efficiently.
2
Reliable
By prioritizing consistency and robust error handling, the design builds user trust, ensuring dependable performance and minimizing friction points.
3
Valuable
By streamlining access to critical data and analytics tools, the new design enables users to make informed decisions.
final design
The final design centers on three core principles to create a seamless, user-focused experience that enhances onboarding, documentation, and error handling.
Onboarding
before
After
Learning and Documentation
before
After
Error Prevention and Handling
before
After
After
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