Brian Carden Design
Product Design Leader based in Austin, TX


As part of a product design leadership triumvirate at BigCommerce, one of my roles is to define and articulate our product design process. The following is a blog post I wrote detailing our team’s approach and methodology.


Product Design at BigCommerce

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Our process begins with empathy. The first step to a creating a successful experience is to develop a deeper understanding of our user. What problems are they trying to solve? What motivates them? What tools are they currently using? Are there UX gaps or opportunities not currently being addressed?

Engaging with our users can take various forms depending on the type of information we are looking to gather. The most common form of qualitative user research we conduct at BigCommerce are 1:1 interviews.

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When we begin a project we set up a number of these interviews to help us identify user needs and identify opportunities. Once interviews are completed, the research is synthesized and a report is generated. Insights are generated, initial assumptions can be validated or disproved.

Competitive Analysis is another method we use during the discovery phase. How is our competition attempting to solve problems similar to our own? What feature sets do they offer? Are there opportunities in the market for us to capitalize on.

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As part of this process we map the journeys of our competitors and conduct an evaluation based on Nielsen's Usability Heuristics for Interaction Design. A set of criteria that allows us to evaluate an experience without having to account for aesthetics or personal tastes.


The results of this evaluation are then rendered in a “rainbow plot” to allow us to easily identify trends and spot opportunities for improvement within our own product.


In addition to “qualitative” inputs like user interviews we examine “ quantitative” data as well. Using tools like Segment our team evaluates user behaviors and intent based on actions taken within the experience.


Once we have a sufficient amount of background, we begin the process of partnering with Product and Engineering to help Define the Problem.

This is the most important part of a product designer’s job. Far too often product organizations fall prey to the trap of "institutional knowledge”. Stakeholder interviews are a valuable source of knowledge, but cannot be the only source of input. Beware the product owner that says “I know what our users want.” Many engineering hours have been wasted building features users don’t want and didn’t ask for. Taking the time to validate assumptions with users pays exponential dividends.

The following is an example from our team’s Intro to Design Thinking presentation. At this point in the presentation, we ask the audience: “What’s the problem here?”

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Inevitably someone will answer “He needs an umbrella.” This is an example of jumping to solutions.

The problem statement is: “He is wet.” An umbrella is a solution, like a raincoat, an awning, or in an MVP (minimal viable product) sense a newspaper.

A Discovery Canvas is a tool we use to kick-off projects with our partners in product, engineering, and marketing. This series of whiteboard, post-it note, and small group exercises is a way for team members to share knowledge and perspective, and allow the team and stakeholders to align around the keys aspects of the project including: definition of problem, value proposition, targeted users, and metrics for determining success.

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The output from the Discovery Canvas should be a clear understanding of the Objectives and Key Results we hope to accomplish from this project.

With our OKRs in hand, we are ready to begin solutioning! Ideation begins with How might we…? questions based on the insights generated during our Discovery phase.

For example: “How might we… make it easier for our users to on-board?“


Our Discovery Workshop has helped us define an MVE (Minimal Viable Experience) for the project. An MVE is the first incremental improvement towards a grander vision for an experience.

In this phase, development of one or more concepts begins. Design team members partner with Product and Engineering to define timelines and deliverables. Information architecture and wireframe explorations begin.


Validation of our hypotheses begin via rapid prototyping. Low fidelity prototypes are tested with coworkers or friends and family. With the team sufficiently confident in a direction, higher fidelity prototypes are created and real users are recruited for user testing. These tests are ideally conducted in person and recorded. A user is asked to complete a series of tasks and articulate their experience/thoughts etc. Feedback is gathered and adjustments to the experience are made.

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With our prototype testing well with users, we are ready to move on to the Delivery phase. Design team members meet more regularly with Product and Engineering counterparts as they prepare to hand off production files. Our team at BigCommerce has been hard at work developing our Design Language System called BigDesign.


Along with principles and guidelines for designers, we have partnered with our engineering team to create a React Component Library in order to streamline the design to developer handoff and help standardize our interface patterns and behaviors.

With production code being developed, Designers and researchers begin recruiting users based on targeted cohort groups. Users join a closed beta and are introduced to the feature. After several weeks our team conducts a follow up interview to gauge the success of the feature.

Once results have been deemed satisfactory, the feature is move to open beta, and available for all users to opt in. Feedback from users is encouraged through contextual prompts. Engineering and product prioritize bugs as the team meets with the Product Marketing Team to discuss got to market plans.  

Do It Again

Our feature has achieved General Availability within the product and is now available to all users. But, our journey is just beginning. The design team partners with product and engineering on a post-launch roadmap to plan the next wave of feature development. We gather new data points from users as they interact with the feature, we discover new opportunities for improvement, and the cycle begins again.