HEB wanted to consolidate their siloed reporting into a single integrated portal, as to better understand category performance in their stores . Currently they had a range of reports, from excel sheets to SQL queries that were used to put together an incomplete picture. They wanted to know who was leading in product categories, but also if they had opportunities to grow their own brands in those segments.


The primary objective was to create a set of web dashboards that would address questions concerning category health, brand loyalty, and potential opportunities for HEB.


My responsibility was to define the key metrics necessary to effectively answer these questions, but also uncover the flow that would logically arrive at useful answers. The final deliverable was a series of high fidelity prototypes for how the solutions should be developed.


  • Card Sorting
  • User Interviews
  • User Personas
  • Experience Map
  • Brainstorming
  • Iterative Mockups


The process began with understanding the questions users wanted to answer. This was done through a series of interviews to understand how users currently made decisions and accessed information.

These interviews and insights helped me construct a fuller picture of what the users were trying to accomplish and create a persona for the primary user group: buying managers.


The initial list of metrics was over 100, which made things more confusing than necessary. After interviews and a few card sorting sessions, we were able to narrow these metrics down into a much more manageable and meaningful dataset.



The discovery process helped me understand the complete experience map at the time. It consisted of 3 primary stages: review, decision, and order.

From this map, I was able to see that the review and decision making process for what to buy and why, were the key problems that needed to be solved. Everything centered around better understanding the categories and brands.


A useful part of the definition process was reviewing the solutions that business users had created themselves. This further showed what was important to the user group and also gave initial guidance on where to begin my own designs.


Based on the information gathered and the user sessions, I started my brainstorming process to devise the best approach for the defined problems. One key realization was the need to separate the solution into two primary dashboards: category health and brand loyalty. This would allow buying managers to get a high level understanding of their category, but also dive deeper into brands as needed.

I selected a key question to answer for each screen that was created, to ensure all data and visualizations fit the proper narrative. The first step was determining what information a user wanted: category or brand.

If category was selected, the user would be able to clearly understand that categories performance and potential. Based on these metrics, they would know whether pursuing promotions of underlying brands was worthwhile.

If it was a promising category, the user could dive deeper into the brand loyalty screen. A key component of this screen would be a suggestion area that would utilize an algorithm to provide guidance on the value of promotion within that category. This feature would solve the biggest challenge for the user group and give solid insight on what action to take.


The designs were iterated and reviewed repeatedly with end users to land on the optimal layout and flow of the final dashboard. This include visualization selection, algorithm tweaking, and key metric decisions.

In the end, three final prototypes for the landing page, category health, and brand loyalty were delivered. Through this flow, the business user was able to navigate their key questions and find the answers they desired.