a sports betting learning tool
Sports viewers who want to partake in sports betting find it difficult to understand how it works, and need a simpler way to learn.
Some questions that were formulated for the problem statement:
How might we make the sports betting experience easier?
How might we help users feel more comfortable learning about sports betting?
How might we create a simpler experience for novice sports bettors?
These HMW (how might we) questions were born after I was approached by three guys who identified a gap between the expert sports bettors and the novices who occasionally dabble in March Madness or Fantasy Football. The current sports betting market had proved to be too difficult for novices to be motivated to learn how to sports bet.
By focusing deeply on the discovery phase (surveys, research, concept testing), we were able to narrow the target audience to provide a tangible solution to fix the learning curve of sports betting.
Timeline & Role
February 2019 - Present.
The team is projected to have a working MVP by June 2019.
In a team of 6 people made of two business-oriented guys, one data whiz guy, one legal sports betting expert, and one full-stack developer, I am the UX/UI designer who is leveraging her experience in UX and product design to help turn an idea into a working prototype and viable MVP.
It will expand into a responsive, mobile-first website after our MVP is rolled out to ensure users can access BetSmart Analytics across all devices. We tabled the option to launch a native application due to the decreasing number of app downloads across iOS and Android devices. Instead, we will be launching a native application after there is a demand from our users for a native app.
User research (surveys, in-person interviews)
Creating user flow
Site mapping web app architecture
Card sorting with target users to validate site map
Wireframing by hand and by using Sketch
UI development and high-fidelity prototyping
Where surveys and user interviews help either validate or debunk our assumptions so our products stay user-centered.
With every idea, the first step is to test it and validate any assumptions stakeholders may have in order to create user-friendly products from the get-go and to save time and effort when building products.
I'm not a master sports bettor, either. I’ve played basketball and golf competitively growing up so the only “betting” I’m familiar with is my bet to myself that I will push through to win matches.
Putting aside any personal or group assumptions, I sent out a survey that garnered over 70 responses in three days. The goal was to:
Validate assumptions of the market opportunity.
Validate assumptions of the needs of who we believe our users are.
Discover how people perceive sports betting as well as sports viewing.
For people who have experience in sports betting, discover what their current frustrations are with the existing workflow.
Learn people’s motivations when it comes to staying in touch with sports.
Learn why people stay away from sports betting or sporting viewing.
Narrow target audience from “Sports Viewers” because that is too general for an MVP to survive meeting the needs of a variety of users.
Note: Due to the web app being in its earlier stages, I will only be sharing the main findings of the survey so that I don’t share any details that should not be shared.
Based on these findings and after hosting three in-person interviews, I decided to create two archetypal user personas who best represented the target audience.
Creating these user types helps all stakeholders stay aware of who might use the product, while being mindful of user goals, needs, frustrations, and experiences related to the MVP.
User personas humanize the research process so that the product development process stays grounded in empathy.
Meet Cole and Elena:
Establishing user flows, site architecture, and wireframes, then validating with user testing.
Having a good product to me means starting with understanding how users will navigate the web app, which is why I created a user flow to break down how our potential users would be walking through the platform.
After creating the user flow, I worked with our data scientist and most experienced sports bettor to make sure the site map depicted accurate features. I also wanted to make sure that the site map included features that the stakeholders found to be most important for the MVP.
Card Sorting and Site-mapping
In order to keep all features and architecture of the web app as user-friendly as possible, I hosted three card-sorting sessions with three different types of users:
Experienced sports bettor
Sports fanatic but not a sports bettor
Not a sports bettor or sports enthusiast
I also wanted to host the card sorting sessions because I wanted to be in the shoes of our users. In order to develop wireframes, I wanted to understand how our users would interpret certain features.
Below you’ll find the card sorting exercise. One of the participants resides in Colorado, so I decided to aggregate results on Draw.io, a free website where people can create user flows, diagrams, site maps, and more. Click on each image to see it enlarged in a lightbox.
Tool used: Sketch
The goal of this stage is to quickly lay out the fundamental interactions of the web app using a mostly gray-scale color palette so that the team is not distracted by trying to make the app “pretty” — because a pretty app that’s not intuitive doesn’t create a seamless experience for users.
In order to make the experience as user-friendly as possible, I will be testing the wireframes with five users from the target audience in the coming week of April 8th, asking them to complete main tasks and goals with the app.
Sample questions I will be asking:
What are your first thoughts when you look at the app?
What do you think you can accomplish with this app?
Can you complete [[XYZ - tasks and goals the app is made for]]?
How would you describe the experience?
What you can expect on this page in the next two months.
As you can see, the web app hasn’t launched yet.
In order to create the most optimal experience for our target users and stakeholders, we will be holding one more user test after the wireframes are finished so that we can reiterate features people find confusing or unnecessary.
Up next in my to-do’s:
Test wireframes with members of our target audience, then make any changes to the wireframes.
Develop style tiles, mood boards for the higher-fidelity prototype.
Work hand in hand with the full-stack developer and data scientist to turn the high-fidelity prototype into a working MVP.