Dashboard for a Sport League
I designed a dashboard for a sports league to help them analyze ticket sales on secondary markets.
The league typically fills their seats in advance by offering standard rates on the primary market. Customers however can also buy tickets from a secondary market like StubHub or Ticketmaster where tickets are resold. The price of tickets sold on these markets can fluctuate everyday leading up to the game-day. These fluctuations depend on a number of factors such as which teams are playing, how popular those teams are, how good the view from the seat is, how close to game day it is, etc.
The league wants to use this understanding of the secondary market prices to adjust their own pricing with the goal of selling tickets directly to the fans and maximizing profits.
I played the role of designer and researcher for the project. I worked closely with our team lead who was overseeing the project and also developing the dashboard.
I used Sketch and Invision for the mockups. The app was to be developed in Qlik Sense. This affected the overall layout of the views, number of visualizations that would fit on each screen. Things like the navigation, title bar, fonts, filtering mechanism and some of the chart interactions were native to Qlik Sense and could not be changed. We did however, have freedom on the types of charts to be included.
User Interviews and Personas
During our research phase we interviewed the project stakeholders to understand the goals for the project and challenges they faced. The two main personas we identified were an executive and an analyst. The executive’s main goal is to increase the revenue generated by the league as a whole. This involves working with the different teams and helping them drive ticket sales. The analyst is responsible for analyzing the secondary market and setting ticket prices with the goal of driving ticket sales and increasing profitability.
A big part of data viz research is figuring out what key questions users need to answer when they use the dashboard. Some of the goals we uncovered are listed below
1) Understand how the market perceives the value of their tickets (are they reselling above or below face value, and by how much)
2) Understand how the market perceives the value of different locations in the stadium relevant to one another
3) Understand the value of different games for variable or dynamic pricing purposes
Examples of Key Questions
How are tickets selling right now?
How many tickets are selling below above/face value?
What is the difference between resold tickets and single/season ticket? What are the gaps?
Do I need to change my pricing for an upcoming game? What is the market selling seats in this section for?
What was the price of a ticket in this section last year?
What was the price of a ticket in this section for a similar game?
We had a collaborative brainstorming session with our stakeholders to share initial ideas. The stakeholder had been in the business for a long time and one of the key questions he needed to answer was “How much above/below face value are tickets selling for and in which sections of the stadium?” This inspired a lot of our design to be about analyzing the gaps in pricing.
After our brainstorming session with the stakeholder I did some individual brainstorming. My process for this was to take the key questions and think of different charts that would effectively answer the question. We had an internal discussion to go over the different ideas and set up a meeting with our users to get some initial thoughts.
The next step was to figure out the overall views that the dashboard would need and figuring out the layout for each of the views. I explored different types of layouts and finally decided on the ones that would work the best based on the type of information starting from overview to details, the users flow of questions and the natural path of reading.
What do our ticket sales look like for past and upcoming games?
How does the resale value compare to the single game/season ticket value?
What does trend look like leading up to game day?
Single Game Analysis
Where in the stadium are resold tickets selling?
Are they above/below face value?
What is the trend of secondary market ticket sales leading up to gameday?
Multi Game Analysis
Which parts of the stadium have the highest resold tickets across the different games?
What is the trend of secondary market ticket sales across games? When are ticket sales the highest?
Season Price Details
How do season ticket sales compare to the secondary market across different games and sighlines?
How does the trend of ticket sales compare across different sightlines?
Brainstorming with stakeholders
In this project we did some initial brainstorming with the stakeholder instead of just presenting ideas to them. It helped us get abetter sense of their vision initially. It also got the stakeholder to be more invested in the design and feel more ownership of the design.
Designing upfront doesn't always work
The approach for this project was to do the design upfront and then start development. We ran into a lot of issues during development because a lot of the charts had to be custom developed for Qliksense. We had never developed these charts before so it was hard to accurately estimate the level of time and effort it would take. We went with a more ambitious design thinking that it would take less effort to develop than it actually did