🔮 Project Overview

Preciser is an early stage startup and provides high accuracy data analytics for Fantasy Sports players. Fantasy Sports is a growing market and is projected to have 500 million users by the end of 2030. Currently, there are over 80 million people who play Fantasy sports but there is no tool in the market that provides game data that is fully functional. Of those 80 million active users, only 20% of players report they know how to use the data correctly. As an early hire, I was actively involving in UX research to define user persona, problem areas, and pain points, and laid down the design foundation as well as built a design system for the team to ensure design consistency throughout the platform. I was responsible for overseeing the end-to-end product design process and communicating the voice of the brand to the end user. How can we stand out from the competitors and improve the user experience?

✨Analytics

The industry standard for sports betting platforms is that the users spend 7 minutes a day on average on the platforms. We want to increase this number by introducing community so the players can connect with each other and share information as well as form private and public leagues to enjoy their game.

During the initial survey round, we were able to define user archetype for Preciser. A common customer archetype is made up of:

• 80% male,

• 50% between the age of 18 and 34

• 67% are employed full-time

• 47% make more than $75,000

• 78% play fantasy baseball

• 34% play fantasy basketball(NBA)

• 19% play fantasy baseball

Problem Area

We live in a world with an overwhelming amount of data. With the right usage, the data can be very helpful, but not many people know how to use the data we have available. One of the biggest problems for Fantasy sports players is that there is no real analytics tool out there they can use to help understand the game data. The analytics tools that are available are difficult to use because they often do not provide any context for the user to understand the data, and are not beginner friendly.

Pain Point

Current analytics tools focus on providing numbers like Excel sheet where, unless the user is already familiar with the layout of the site and understands exactly what to look for, looking for a valuable data set becomes very difficult. One area we are going to focus on is the data visualization. In order to present the data in a more beginner-friendly, human centric way, it is important to move away from a huge list of numbers and design a data visualization graphs that are cohesive, easy to understand, and intuitive. We are achieving that by using color coding, selecting the information and data that actually matter to the user’s decision making process, and giving the full control of the data and how it’s presented back to the users.

Data Visualization

Data visualization will be the key factor that distinguishes Preciser from its competitors by organizing and presenting data in a way that is scannable. I worked closely with the Data Scientist to understand the raw data that we have and turn it into a visually cohesive graph.

So we took data that looks like the images on the left and organized them visually to present the same data to look like the images on the right to help the viewer digest the information better.

Now that we have the type of data that we like to present, we had to figure out information architecture and work on how people will use the platform and find analytics.

Information Architecture

First, we worked on mapping out the user workflow when they enter the platform as a new user.

Second, we worked on the actual layout of the website like nav bar, sub nav bar, and the subsequent pages.

We also worked out a flow for the filter options to help the users manipulate the graphs for the most optimal results.