March 20, 2018 | Cody Haro

Data-Driven Design Series, Part III: Pre-Design Analysis

Design with intention: Finding and Keeping What Works

The previous post in our series examined the importance of attitudinal data and creating a detailed test plan based on user-centered KPIs. Here we move on to the next step, pre-design analysis.

The focus of this phase is to gather data and knowledge so the team can begin the iterative testing process from an informed position. Before beginning your designs, you need to know what is working and what needs to change. Harnessing the deep expertise of the ForeSee Usability team is a great way to do that.

The pre-design analysis process begins with a baseline user-experience assessment of the current site. One way to accomplish this involves conducing a usability audit review (UAR) on the specific site sections that will be included in upcoming usability testing. UARs are detailed heuristic evaluations that use ForeSee’s proprietary database of thousands of usability best practices. These best practices, rooted in cognitive science, allow us to identify which areas to change on and which to leave alone—with surgical precision. For instance, a utility company planning an upcoming round of usability testing to evaluate a new customer dashboard may choose to conduct a UAR focused on the My Account experience. This would allow identification of previously unknown design flaws that adversely impact usability and, of course, CX. Understanding where the current site falls short helps prevent similar issues from being replicated and ushers in improvements to the new design.

A baseline user-experience assessment could also include a competitive usability audit review to better understand the industry landscape. Clients select three or more competitors they would like to be evaluated against based on strengths, weaknesses, areas for opportunity, and threats. The report offers insight into how competitors address common design challenges and can also be used to highlight approaches that have not been previously considered. After assessing the weaknesses in the current design and evaluating the competition, the design team is ready to begin creating and refining the first iteration of the design.

Designing with Certainty—Using Predictive Data

If navigation is a known issue, conducting a predictive information-architecture design study can be helpful. To get the right information, the process involves asking your key persona groups to sort the content into groupings that make sense to them. With ForeSee, actual users of the site are invited to take part in an information architecture assessment using our Smart Thank You Pages. Results are then compiled into data visualizations that show how users classify and label the content. We have the only CX solution that can link this to a predictive methodology, bringing certainty to the process. This enables our clients to quantify how much the expected improvement will drive desired outcomes, such as likelihood to purchase or recommend.

Once an initial design has been crafted, ForeSee can conduct a prototype review to evaluate the usability of the new design. This type of report can be incredibly valuable for clients in terms of the time and development costs saved, because design issues are identified and corrected before developers start writing code.

When glaring usability issues are addressed early in the design process, usability tests will be more successful at capturing nuanced issues that will allow you to take your user experience to the next level. Once you know what works, what doesn’t, and are sure your site organization aligns with your customers, your team can create designs based on certainty instead of guesswork and hope!

About the Author

As a Usability Analyst with ForeSee, Cody has worked with clients across a range of industries including retail, telecommunications, utilities, and healthcare. His work encompasses numerous usability audits, internal design projects, as well as a number of reports focused on Replay analysis. He graduated from the University of Michigan with a Master’s degree in Human-Computer Interaction and also holds a Bachelor’s degree from the University of Minnesota.

More by this author