Personalized Betting Market Discovery
Personalized Betting Market Discovery
Responsibility
Responsibility
Lead Designer
Product Designer
Duration
Duration
4 Weeks
4 Weeks
Team
Team
1 UXR, 2 PMs, 1 DA, 8+ Devs
1 UXR, 2 PMs, 1 DA, 8 Devs
Our cross-functional team helped sport bettors make quick and easy betting decisions.
As the main designer, I led the design process from opportunity identification to delivery. Adopting the Lean UX approach, we ensured an efficient process with minimum cost and risk.
Our cross-functional team helped sport bettors make quick and easy betting decisions.
As the main designer, I led the design process from opportunity identification to delivery. Adopting the Lean UX approach, we ensured an efficient process with minimum cost and risk.
Background
Background
Background
The company features two main apps: theScore and theScore BET.
The company features two main apps: theScore and theScore BET.
The company features two main apps: theScore and theScore BET.
theScore (TSM)
theScore (TSM)
Media app covering news updates and scores information on different sports and leagues.
Media app covering news updates and scores information on different sports and leagues.
theScore BET (TSB)
theScore BET (TSB)
Sportsbook offering betting market and bet tracking experience.
Sportsbook offering betting market and bet tracking experience.
theScore (TSM)
Media app covering news updates and scores information on different sports and leagues.
theScore BET (TSB)
Sportsbook offering betting market and bet tracking experience.
Our Team: The ecosystem
Our Team: The ecosystem
As a team that lives between the sports app and the bet app, our vision is to showcase the offerings of our bet app and help betting-curious users have a easy discovery and transition into sports betting. Therefore, we introduced betting market touch points across the sports app.
As a team that lives between the sports app and the bet app, our vision is to showcase the offerings of our bet app and help betting-curious users have a easy discovery and transition into sports betting. Therefore, we introduced betting market touch points across the sports app.
What is a Betslip?
What is a Betslip?
A betslip is like a shopping cart for bet markets, containing markets users selected. "Placing bets" means checking out with the selections.
A betslip is like a shopping cart for bet markets, containing markets users selected. "Placing bets" means checking out with the selections.
Our Team: The ecosystem
As a team that lives between the sports app and bet app, our vision is showcase the offerings of our bet app and help betting-curious users have a easy discovery and transition into sports betting. Therefore, we introduced betting market touch points across the sports app.
What is a Betslip?
A betslip is like a shopping cart for bet markets, containing markets users selected. "Placing bets" means checking out with the selections.
What's Wrong?
What's Wrong?
What's Wrong?
Our users don't build betslips in TSM
Our users don't build betslips in TSM
Our users don't build betslips in TSM
These bet markets in the TSM app have a poor user engagement rate, therefore failing to acquire new betting users or to encourage betting activities behaviors.
These bet markets in the TSM app have a poor user engagement rate, therefore failing to acquire new betting users or to encourage betting activities behaviors.
These bet markets in the TSM app have a poor user engagement rate, therefore failing to acquire new betting users or to encourage betting activities behaviors.
Discovering the cause
Discovering the cause
Discovering the cause
Identifying the cause without primary research - What did we do?
Identifying the cause without primary research - What did we do?
Identifying the cause without primary research - What did we do?
Constraints
Constraints
Constraints
We had no user researcher to help us conduct a primary research.
We had no user researcher to help us conduct a primary research.
We had no user researcher to help us conduct a primary research.
Reference Mining (Secondary Research)
Reference Mining (Secondary Research)
Reference Mining (Secondary Research)
I performed an audit on existing artifacts and also collaborated with the data analyst to pull useful numbers.
I performed an audit on existing artifacts and also collaborated with the data analyst to pull useful numbers.
I performed an audit on existing artifacts and also collaborated with the data analyst to pull useful numbers.
Extract existing user data
Most of markets in TSM are rested 3-4 layers deep.
The majority of bets are placed during pre-game stage.
86% of bet that users placed in TSB are available in TSM.
Conclusion
The main problem of low market engagement rate is not poor market availability, but their location being hard to access.
Relatable research artifacts
Users review sports information before making betting decisions, including:
Team / player stats
Historical rival data
Player injuries
Weather information
These information are provided in the TSM app, but scattered in different places.
Conclusion
Users like to collect information in order to make the "smartest bets". But gathering and analyzing these information is a troublesome process.
I presented these findings to the team, and we collaboratively concluded the main cause of the problem.
I presented these findings to the team, and we collaboratively concluded the main cause of the problem.
I presented these findings to the team, and we collaboratively concluded the main cause of the problem.
Extract user data
Most of markets in TSM are rested 3-4 layers deep.
The majority of bets are placed during pre-game stage.
86% of bet that users placed in TSB are available in TSM.
Conclusion
The main problem of low market engagement rate is not poor market availability, but their location being hard to access.
Relatable research artifacts
Users review sports information before making betting decisions, including:
Team / player stats
Historical rival data
Player injuries
Weather information
These information are provided in the TSM app, but scattered in different places.
Conclusion
Users like to collect information in order to make the "smartest bets". But gathering and analyzing these information is a troublesome process.
Extract existing user data
Most of markets in TSM are rested 3-4 layers deep.
The majority of bets are placed during pre-game stage.
86% of bet that users placed in TSB are available in TSM.
Conclusion
The main problem of low market engagement rate is not poor market availability, but their location being hard to access.
Relatable research artifacts
Users review sports information before making betting decisions, including:
Team / player stats
Historical rival data
Player injuries
Weather information
These information are provided in the TSM app, but scattered in different places.
Conclusion
Users like to collect information in order to make the "smartest bets". But gathering and analyzing these information is a troublesome process.
Goal and hypothesis
Goal and hypothesis
Goal and hypothesis
With the findings from the secondary research, we've arrived at our goal.
With the findings from the secondary research, we've arrived at our goal.
With the findings from the secondary research, we've arrived at our goal.
"How might we allow users to easily find the Betting Markets of interests and understand the Information related to these betting markets?"
"How might we allow users to easily find the Betting Markets of interests and understand the Information related to these betting markets?"
"How might we allow users to easily find the Betting Markets of interests and understand the Information related to these betting markets?"
By doing so, we should achieve an increase in betslips started from the TSM app.
By doing so, we should achieve an increase in betslips started from the TSM app.
By doing so, we should achieve an increase in betslips started from the TSM app.
Ideations
Ideations
Ideations
We adopted the Lean UX approach for this opportunity.
We adopted the Lean UX approach for this opportunity.
We adopted the Lean UX approach for this opportunity.
Competitive analysis
Competitive analysis
Competitive analysis
Conducting on both sports apps and bet apps. I focused on three questions:
Conducting on both sports apps and bet apps. I focused on three questions:
Conducting on both sports apps and bet apps. I focused on three questions:
How do they encourage discovery of market?
What type of markets do they promote?
How do they help users gather and understand relevant information?
How do they encourage discovery of market?
What type of markets do they promote?
How do they help users gather and understand relevant information?
How do they encourage discovery of market?
What type of markets do they promote?
How do they help users gather and understand relevant information?
Quick Ideation Exercise
Quick Ideation Exercise
Quick Ideation Exercise
Next, I conducted this exercise with a smaller group including the UXR and product managers for quick ideas generation.
Next, I conducted this exercise with a smaller group including the UXR and product managers for quick ideas generation.
Next, I conducted this exercise with a smaller group including the UXR and product managers for quick ideas generation.
Two Kinds of Strategies?
Two Kinds of Strategies?
Two Kinds of Strategies?
01: High Risk, High Reward
01: High Risk, High Reward
01: High Risk, High Reward
Tapping into users' natural flow and spread touch points at several places
Pros: it's contextual, allowing a better experience for target users.
Cons: It might be disturbing to non-betting users; it also yields cross-team dependencies which broadens the scope.
Tapping into users' natural flow and spread touch points at several places.
Pros: it's contextual, allowing a better experience for target users.
Cons: It might be disturbing to non-betting users; it also yields cross-team dependencies which broadens the scope.
Tapping into users' natural flow and spread touch points at several places
Pros: it's contextual, allowing a better experience for target users.
Cons: It might be disturbing to non-betting users; it also yields cross-team dependencies which broadens the scope.
02: The Safe Bet
02: The Safe Bet
02: The Safe Bet
Introducing one contained section at the bet section
Pros: Non-interruptive to non-betting users and easier to build.
Cons: It diverges users from their nature path, adding to the user effort and reducing our confidence.
Introducing one contained section at the bet section
Pros: Non-interruptive to non-betting users and easier to build.
Cons: It diverges users from their nature path, adding to the user effort and reducing our confidence.
Introducing one contained section at the bet section
Pros: Non-interruptive to non-betting users and easier to build.
Cons: It diverges users from their nature path, adding to the user effort and reducing our confidence.
Negotiation and Tradeoff
Negotiation and Tradeoff
Negotiation and Tradeoff
Can we mitigate the risk through controlled release to more specific audience?
Can we do a combination of both?
Can we mitigate the risk through controlled release to more specific audience?
Can we do a combination of both?
The Alignment
The Alignment
The Alignment
Since the entire project is not supported by solid and direct research evidence, we decided to take an experimental mindset.
Since the entire project is not supported by solid and direct research evidence, we decided to take an experimental mindset.
Since the entire project is not supported by solid and direct research evidence, we decided to take an experimental mindset.
"Minimal risk, low cost, fast iteration. If we fail? We move on."
"Minimal risk, low cost, fast iteration. If we fail? We move on."
Solutions
Solutions
Solutions
MVP: Quick rollout to test the water
MVP: Quick rollout to test the water
Bring selective markets related to user's favourite players and teams to the home page of bet section (1st level page)
Simple data analyzer that gathers, summarizes and analyze information related to the markets we provide
Bring selective markets related to user's favourite players and teams to the home page of bet section (1st level page)
Simple data analyzer that gathers, summarizes and analyze information related to the markets we provide
Assumptions to validate
Assumptions to validate
Betting users like to place bets related to their favorites teams or players.
Betting users like to place bets related to their favorites teams or players.
Success metrics
Success metrics
Primary: Increased number of betslips attributed to TSM
Secondary: User downloads of TSB from TSM betslip
Primary: Increased number of betslips attributed to TSM
Secondary: User downloads of TSB from TSM betslip
Later stages
Later stages
Enhance the personalization aspect by surfacing markets based on users' betting history
Increase feature exposure by adding touch points to more areas to increase exposure
Enhance the personalization aspect by surfacing markets based on users' betting history
Increase feature exposure by adding touch points to more areas to increase exposure
Why are these scheduled for later?
Why are these scheduled for later?
Although impactful, these ideas are much more costly and require a new personalization modal to be built.
Although impactful, these ideas are much more costly and require a new personalization modal to be built.
MVP: Quick rollout to test the water
Bring selective markets related to user's favourite players and teams to the bet section (1st level page)
Simple data analyzer that gathers, summarizes and analyze information related to the markets we provide
Succss metrics
Primary: Increased number of betslips attributed to TSM
Secondary: User downloads of TSB from TSM betslip
Later Stages
Enhance the personalization aspect by surfacing markets based on users' betting history
Increase feature exposure by adding touch points to more areas to increase exposure
Design Process
Define interactions, communicate visual concept, refinement, testing.
Step 01
Align on foundational functionalities and user flow with product managers and stakeholders
Step 02
Alignment on market and types and visual representation of data
Step 03
Propose the visual concept with initial feasibility check
Step 04
Making tradeoffs and scope adjustment
Step 05
A/B test and internal usability check; final refinements
Designing
Designing
Define interactions, communicate visual concept, refinement, testing.
Define interactions, communicate visual concept, refinement, testing.
Step 01
Align on the user flow, foundational functionalities and actions
Partners: product managers, stakeholders
Step 02
Define market types and visual representation of data
Partners: data analysts, product managers
Step 03
Propose the visual concept and run initial feasibility check
Scope adjustment
Partners: product managers, developers
Step 04
Partners: product managers, UX writer
Refine visuality and details of interactions
Refine text copies
Step 05
A/B test between different visual options
Internal usability test to validate understanding of design
Final refinement of details.
Partners: product managers, UX researchers
Design Outcome - MVP
Design Outcome - MVP
Quick discovery of markets and easy understanding of data.
Quick discovery of markets and easy understanding of data.
Market cards on first level page
Logic based on users favorites
Betslip creation upon selecting markets
Prop analysis preview helping prediction of result
Insight sheets
Expandable analysis sheet offering more details
Advanced controls
Adjustable markets and insights type
Draggable slider for flexible odds selection
Handoff and Documentation
Handoff and Documentation
In addition to looping in the devs along the process, I also created detailed documentation explaining different case scenarios and resizing rules.
Market Recommendation Cards
Markets snippits based on user favorites
Betslip creation upon selecting markets
Prop analysis preview helping prediction of result
Expandable analysis sheet offering more details and controls
Expandable analysis sheet offering more details and controls
Draggable slider for flexible adjustment of odds and corresponding stats.
Draggable slider for flexible adjustment of odds and corresponding stats.
Learnings
Learnings
Learnings
Mitigate the risk through incremental changes and experimentation
Mitigate the risk through incremental changes and experimentation
Mitigate the risk through incremental changes and experimentation
Starting small allows us to learn by controlled testing and refine out product while facing uncertainties. A product and UX team must have a solid understanding of the users and context to identify the core experience and strategically phase the product.
Starting small allows us to learn by controlled testing and refine out product while facing uncertainties. A product and UX team must have a solid understanding of the users and context to identify the core experience and strategically phase the product.
Starting small allows us to learn by controlled testing and refine out product while facing uncertainties. A product and UX team must have a solid understanding of the users and context to identify the core experience and strategically phase the product.
Embrace unknowns and assumptions
Embrace unknowns and assumptions
Embrace unknowns and assumptions
We can never predict 100% of the outcome of a product before launch. So while it is important to reduce to uncertainties prior to product release, it’s also crucial to embrace ambiguity and make informed assumptions based on research and data. The key is to push forward and continuously iterate based on real user-driven insights.
We can never predict 100% of the outcome of a product before launch. So while it is important to reduce to uncertainties prior to product release, it’s also crucial to embrace ambiguity and make informed assumptions based on research and data. The key is to push forward and continuously iterate based on real user-driven insights.
We can never predict 100% of the outcome of a product before launch. So while it is important to reduce to uncertainties prior to product release, it’s also crucial to embrace ambiguity and make informed assumptions based on research and data. The key is to push forward and continuously iterate based on real user-driven insights.
Website design owned by © Danshi Chen
Website design owned by © Danshi Chen
Website owned by © Danshi Chen