For this project, I was part of a team of designers who were asked to find usability improvements that could be made for a desktop data analytics web application oriented toward the wine industry.

Our objectives were to understand existing product and identify opportunities for improvement in the user interface, implement improvements into a clickable prototype, and provide next steps and suggestions for the client.

The company we worked for is called Winosaurus, and they're concerned with matching suitable wines to consumers using a machine-learning model and user-defined terms or descriptors. For example, a customer can input “fruity” or “smoky” and receive wine recommendations associated with those flavor profiles.

They offer two connected products:

Firstly, a business-to-consumer recommendation application that can be embedded onto winery-operated e-commerce websites to assist with natural language processing when customers browse for wine.

Secondly, a business-to-business data analytics web application. An existing version of this product was our focus for this project. Analysts are meant to use this app to organize wine data and help guide business strategy.

During this analysis, we wanted to consider attributes that were important both to our client’s business and quality of utility and experience for the users.

I aimed to survey the most depended-upon heuristics dashboard interface design as employed by others in the analysis market.

While looking at the competition, we found that many of our direct competitors didn't provide many core features that were mentioned during our initial information interviews with analysts. This opened up possible avenues for Winosaurus to take advantage.

After five initial informational interviews with data analysts, we created some flows and wireframes to model a typical sequence of actions an analyst might take when using this software.
We organized a simple path for the user which aims to highlight essential screens each house the main features of the app:
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- A home dashboard screen
- An intuitive graph builder for the creation of visualizations
- A data dashboard screen

The navigation between these screens resulted in this user flow:

To question the target audience, we aimed to recruit data analysts preferably with experience working in the wine industry. Our key insights were as follows:

1: Users wanted to see expanded functionality to support an exploratory interface where users can come with questions.

2: The UI was difficult to navigate for many of the participants- certain functionality was expected (and provided in the app) but weren't easy to find.

3: We also found that many elements of the visual design didn't provide adequate contrast, which posed several readability and accessibility issues for users.

Below is an example of the graph editor in which an analyst would direct data sources to create a particular visualization for their needs.

We chose to incorporate a geographical visualization for the prototype, though we learned through testing that we probably should’ve gone with a simpler graph such as a bar graph. The final product would support most graph types, but here we wanted to illustrate something a winery might be concerned with, such as regional sales.

In hindsight, this project was an incredibly insightful dive into the world of information dashboard design. This was the first time my team handled such a project, and although we learned quite a lot in a short amount of time, I was compelled to supplement my understanding through further research in this area.