ScratchOdds
By leading user research and usability testing, I helped ScratchOdds refine product-market fit and ship user-driven feature updates — optimizing navigation, UX copy, and in-app strategy to boost retention from 30% to 66% and lift lifetime value beyond $30, driving growth for this mobile app startup.
Designs
The Problem
Valuable scratch-off sales data is updated on each state lottery site including:
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Game meta data
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Prizes in Each Game
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Number already claimed and printed of each prize
However, it's impractical for individuals to aggregate and analyze this constantly changing information to determine the best scratch-off games daily.
Texas State Lottery Website
The Solution
ScratchOdds aggregates and analyzes state lottery data — prize structures, claimed vs. unclaimed tickets, and real-time odds — to surface the best scratch-off games in a clear, mobile-first experience.
When I joined, an MVP existed — but it prioritized visual polish over usability and insight. That left ample space to transform the experience into something more strategic and intuitive:
MVP Views
Game List & Filter Buttons
Game Detail & Statistics
Max Game Price Filter
Goal (List) Selection
Next Steps
After a heuristic evaluation of the MVP and several team ideation sessions, we aligned on key UX gaps and defined the next steps for redesign.
MVP Heuristic Evaluation
V2 Designs
Configure Game List / Select Goal
MVP Problems
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Default Goal Limited Discovery – Pre-set to “Win $100,000+,” preventing users from exploring other ranking options.
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Hidden Toggle Option – Header on game list page was too small, making it easy to miss the ability to change goals.
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Weak Correlation – Connection between the list type header on game list view and ranking results wasn’t clear, leaving users unsure how the two related.
V2 Solutions
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Seamless Onboarding – Integrated goal selection into onboarding, so users could set preferences immediately.
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Reduced Cognitive Load – Limited options to four to minimize mental strain.
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Organized Dropdowns – Grouped detailed prize targets into a dropdown on game list view for cleaner navigation.
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Clearer UX Copy – Improved labeling and added descriptions for better comprehension.
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Informed Decisions – Added risk-level tags to guide users toward the right strategy.
Game Card
MVP Problems
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Weak Visual Hierarchy - Game name didn’t stand out, reducing scannability and quick recognition.
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Image Underutilized - Scratch-off image didn’t fill the card space, missing an opportunity to make the game more engaging and recognizable.
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Thin, Low-Contrast Text - Key information like payout and price was hard to read, hurting accessibility.
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Confusing Metric - Odds line was unclear and not consistently aligned with the metric label, creating ambiguity.
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Inconsistent Layout - List view metrics didn’t follow the same vertical alignment as other stats, breaking rhythm and making comparison harder.
V2 Solutions
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Strengthened Visual Hierarchy - Increased font size and weight of game names so they stand out as the primary identifier.
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Maximized Image Impact - Enlarged game images to fill the card space, boosting visual recognition and engagement.
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Improved Readability & Accessibility - Increased text contrast and bolded key values (e.g., Top Prize Left) for emphasis and legibility.
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Clarified Key Metric - Displayed the primary sort metric in a bold, colored token with consistent labeling to make results easy to scan.
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Standardized Layout - Aligned all list view metrics vertically to improve rhythm, readability, and quick comparison.
Price Filter
MVP Problems
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Too Many Clicks – Multi-select required excessive tapping, slowing down the setup process.
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No Range Option – Users couldn’t set a min/max range, making the filter less flexible.
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Cluttered UI – Price tokens crowded the homepage, creating unnecessary visual noise.
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Generic Defaults – Price was set to “all” by default, leading to a less personalized experience.
V2 Solututions
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Streamlined Setup – Integrated price selection into onboarding so users could set preferences right away.
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Range Sliders – Added min and max selectors, reducing entry points and giving users more control.
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Decluttered Homepage – Removed price tokens to simplify the main screen.
Revisiting the Problem
Even after launching V2, users continued to cancel their subscriptions.
By jumping into design too quickly, we hadn’t fully uncovered the deeper purchasing behaviors, needs, and motivations driving these decisions.
To address this gap, I initiated a structured UX research study combining usability testing and qualitative interviews, aimed at revealing the root causes behind churn.
Research Goals
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Map the end-to-end user journey.
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Analyze purchasing behaviors in depth.
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Identify pain points and areas for improvement.
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Define new features directly tied to user needs.
Research Goals
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Optimize the app for personalization.
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Assess overall user satisfaction.
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Gauge the market value of the app.
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Benchmark against competitors to surface opportunities.
Who
14 participants across diverse demographics and varying levels of scratch-off experience.
What
1:1 interviews (60 minutes)
1:1 moderated usability testing
Tools
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Userinterviews.com
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Otter.ai
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Lookback
User Journey
To better understand how players interact with scratch-offs, I mapped the end-to-end journey from the first moment of motivation through to reflection based off my research data. This revealed emotional highs and lows, key pain points, and opportunities for ScratchOdds to provide value.
1. Trigger & Motivation
Players typically see a scratch-off ticket in-store or on a vending machine, sparking curiosity, excitement, and impulse. The goal is a low-cost thrill — but decisions are often based on assumptions or visual appeal rather than actual odds.
Opportunities
Reinforce excitement with data-backed confidence in game choice
2. Research & Decision
Some players turn to the ScratchOdds app (or state lottery sites) to check odds and explore available games. Emotions shift into curiosity and decision-making. However, limited time and lack of clear odds often lead to shallow research.
Opportunities
Provide streamlined, in-app comparisons that make odds easy to digest.
3. Selection
At the store, players face overwhelming walls of tickets with little guidance. They try to balance their desire for a fun outcome with unclear expectations of prize odds. Excitement mixes with uncertainty.
Opportunities
Offer personalized, odds-based recommendations that cut through the clutter.
4. Purchase
Tickets are purchased at a cashier, machine, or online. Players feel satisfaction and hope — but also worry about wasting money if they picked poorly.
Opportunities
Seamlessly connect odds-based guidance with the purchase flow for more confident decisions.
Research Themes
Through 14 qualitative interviews and usability tests, I uncovered patterns in player behavior, motivations, and perceptions around scratch-off games. These insights directly informed the redesign of ScratchOdds V3.
Scratch-Off Perceptions
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Habitual Play: Players often buy scratch-offs impulsively when they have spare cash. Even after losses, the fun and excitement keep them coming back.
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Confidence in Winning: Many believe they’ll win at least small prizes regularly, fueling continued purchases.
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Convenience: Instant results and wide availability make scratch-offs more appealing than other gambling options.
ScratchOdds Demand & Value
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Interest: Users were eager for a single app to check odds, track winnings, and compare games.
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Trust: Transparent odds and clear prize breakdowns helped players feel more confident in their decisions.
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Competitive Edge: An ad-free, easy-to-use, feature-rich app stood out from existing tools.
Purchasing Behavior
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Budget-Conscious: Most players buy scratch-offs only when they have extra money, with price and card visuals strongly influencing decisions.
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Game Preferences: Users prefer new or seasonal games and often buy multiple tickets within their budget.
Odds Preferences
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Clarity: Players want simple, percentage-based odds to see how likely they are to at least break even.
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Comparisons: Seeing odds across categories and packs was especially valuable.
Beliefs About Odds
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Odds Increase: Users trust games more when high-value prizes are available.
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Odds Decrease: Distrust grows when flashy designs or lack of visible recent wins dominate.
Game Categories
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Preferred Types: Matching games like Bingo or Monopoly were favorites, with requests for second-chance play.
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Seasonal/Charity Games: Games tied to holidays or charities had stronger emotional appeal.
Pricing & Competitors
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Willingness to Pay: Users would pay for an app that combines the best of free competitor sites, valuing reliability and convenience.
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Pricing Preferences: $10–15/month was seen as reasonable for premium, consolidated features.
V3 Designs
After running in-depth user research and usability testing, I translated insights into the V3 redesign, addressing pain points from earlier versions while adding personalization and clarity.
Goal Selection
V2 Problems & Solutions
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Confusing Goals List: Users didn’t understand how goals influenced rankings, and the UX copy didn’t match their motivations.
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Solution
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Split and simplified UX copy for “target prize” → "Jackpot" and "Big Prize," each with different risk levels.
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Changed “Win Any Prize” → “Breakeven” since users didn’t want to loose money.
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Changed “Maximize Avg Returns” → “Best Game Payout”.
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Added a sliding color-coded risk scale for faster recognition and decision-making.
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Price Filter
V2 Problems & Solutions
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Buying Multiple Games: Buyers usually purchase several scratch-offs at once based on how much cash they have, rather than focusing on each ticket’s price.
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Solution
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Replaced the minimum and maximum game price with a single “Budget” slider that calculates the best odds for bulk purchases, making it easier to plan spending and maximize value.
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Game List
V2 Problems & Solutions
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App Value: Some users were entirely sure how impactful this app would be.
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Solution
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Added a card to explain the odds from best to worst performing game, highlighting the app's value.
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Filtering: Discoverability of changing goal/list and price was difficult to find for some users.
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Solution
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Added change goal and budget buttons for better discoverability.
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Game Metadata: Buyers typically like purchasing games that are new or ending soon.
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Solution
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Added additional game tags to reference this.
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Buying Multiple Games: Users wanted to know odds of buying multiple games based off a budget.
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Solution
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Introduced odds calculation for purchasing multiple games based on a budget.
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Risk Level: Users found it tedious to manually compare number odds and determine which games to buy.
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Solution
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Introduced a color scale ranking system for the tokens to clearly show how games perform, making it easy to compare the best and worst options.
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Search
V2 Problems & Solutions
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Search: Buyers often have favorite games, and wanted to know odds of them easily.
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Solution
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Added game search feature.
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Prizes Tab
V2 Problems & Solutions
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Relevancy: Buyers wanted confidence that the data was current.
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Solution
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Added a visible “Last Updated” date to reinforce data freshness.
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Wrong Default Focus: Users cared more about prize rankings than overall stats.
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Solution
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Made “Prizes” the default tab when opening game details.
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Different Player Goals: Some users focused on smaller wins, but couldn’t customize the view.
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Solution
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Added a quick-sort feature to flex the prize list by user goal.
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Misleading Prize Cards: Odds were large and prize amounts small, confusing users.
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Solution
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Reversed visual hierarchy — emphasized prize amount and used color-coded odds tokens for clarity.
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Rankings Tab
V2 Problems & Solutions
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Stats vs Prizes: Users weren’t sure what the “Stats” tab meant, and the difference between the prizes tab.
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Solution
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Renamed “Stats” → “Ranking” for clearer comparison.
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Cross-Game Comparison: Users wanted to see how one game ranks against others without leaving the page.
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Solution
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Added a ranking token showing the game’s position across all results, color-coded for easy scanning.
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Role
UX Designer
Length
Ongoing ownership & iteration
Users
20,000 + Users
Responsibilities
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Product Strategy - Defined product vision, roadmap priorities, and trade-offs to align features with business goals and user needs.
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UX Research - Led user interviews, surveys, and usability testing to uncover pain points and validate product-market fit.
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Experience Design - Created user flows, wireframes, and iterative prototypes; contributed light UI design for feature releases.
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Product Management Collaboration - Partnered closely with founders and engineers to prioritize the backlog, refine requirements, and launch impactful updates.
Impact
Drove product-market fit by leading user research and usability testing that shaped key feature updates.
Lifted subscription retention from 30% → 66% by iterating on core flows based on real user behavior.
Increased lifetime value (LTV) to $30+ through improvements to navigation, UX copy, and in-app purchase strategy.
V3 CSAT
1) How likely are you to recommend this app to a friend or colleague? (1 - 7)
Avg: 6.5
2) How likely are you to purchase this app? (1 - 7)
Avg: 6.1
3) How satisfied are you with the app? (1 - 7)
Avg: 6.3
4) How easy was it to navigate through the app and complete the tasks? (1 - 7)
Avg: 5.9
5) How likely are you to use this over the competitors? (1 - 7)
Avg: 7
Beyond V3
After V3, we identified new opportunities to make ScratchOdds even more powerful — including deeper personalization, predictive recommendations based on user risk appetite, and real-time game tracking as states release new data. The team is currently working on these next-generation features, but the details remain proprietary as the product evolves toward its next public release.
Why Now
Scratch-Offs are Booming
They’re the most profitable lottery product in the U.S., with billions spent annually.
Players Buy on Instinct
Decisions are driven by excitement, colors, and assumptions—not real odds.
Data is Buried
While some state sites publish prize data, it’s fragmented and not mobile-friendly. Players are left manually crunching numbers to compare odds.
Opportunity
ScratchOdds aggregates and analyzes this data daily, delivering clear game rankings in a seamless mobile experience.