Note: Certain details, visuals, and data have been modified or omitted to comply with confidentiality and NDA agreements.

Note: Certain details, visuals, and data have been modified or omitted to comply with confidentiality and NDA agreements.

Designing trust into a system that broke it

ROLE

Sole Product Designer

SCOPE

Research to Shipped Product

PLATFORM

Mobile and Desktop

ROLE

Sole Product Designer

SCOPE

Research to Shipped Product

PLATFORM

Mobile and Desktop

The problem with sneaker drops

Limited sneaker releases are one of the most emotionally charged purchasing experiences in consumer retail. Demand massively outstrips supply. The window to enter is minutes long. And for most real users, the outcome is always the same: they lose.


That loss is tolerable. What isn't tolerable is not understanding why.


Across platforms like SNKRS, GOAT, and StockX, the experience is structurally broken in three specific ways. Bots dominate entry windows before real users have a chance. Raffle outcomes are announced with zero explanation no context, no entry count, no selection logic. And after repeated failure, users disengage entirely not because they stopped wanting the product, but because the system stopped feeling worth engaging with.


My job wasn't to solve scarcity. It was to design a system where losing felt fair and where users wanted to come back anyway.

What users actually said

I conducted competitive analysis across SNKRS, GOAT, and StockX, ran one-on-one interviews with sneaker enthusiasts, and ran task-based walkthroughs of existing drop flows. Three patterns emerged consistently across every session.

Lack of transparency erodes trust faster than losing does

Users couldn't explain how winners were selected. The absence of information felt like evidence of manipulation, not a neutral silence.

Perceived bot dominance discourages participation before it starts

Users had developed a prior belief that bots had already won before they entered. That belief made entry feel pointless, reducing both completion rate and emotional investment.

Repeated failure without explanation leads to permanent disengagement

Users didn't stop trying because they lost. They stopped because they had no reason to believe the next attempt would be different.

Lack of transparency erodes trust faster than losing does

Users couldn't explain how winners were selected. The absence of information felt like evidence of manipulation, not a neutral silence.

Perceived bot dominance discourages participation before it starts


Users had developed a prior belief that bots had already won before they entered. That belief made entry feel pointless, reducing both completion rate and emotional investment.

Perceived bot dominance discourages participation before it starts

Users had developed a prior belief that bots had already won before they entered. That belief made entry feel pointless, reducing both completion rate and emotional investment.

Repeated failure without explanation leads to permanent disengagement

Users didn't stop trying because they lost. They stopped because they had no reason to believe the next attempt would be different.

Users, before the redesign

"I don't even know if it's real or just random."

"It feels like bots win before I even have a chance."

"After a while you just stop trying."

Users, before the redesign

"I don't even know if it's real or just random."

"It feels like bots win before I even have a chance."

"After a while you just stop trying."

Users, before the redesign

"I don't even know if it's real or just random."

"It feels like bots win before I even have a chance."

"After a while you just stop trying."

The strategic choice

The obvious move was to redesign the marketplace, better search, better listings, better checkout. That would have been the wrong call.


Every trust problem in the research pointed to one specific moment: the raffle. That was where users felt manipulated. That was where disengagement began. That was where the product was failing them most severely.


Instead of spreading across the entire platform, I focused entirely on rebuilding the raffle system as the core trust mechanism. Fix the raffle, and everything downstream engagement, retention, brand loyalty, follows.

Trust is not a byproduct of good design. At Snix, it had to be designed as a feature.

The obvious move was to redesign the marketplace, better search, better listings, better checkout. That would have been the wrong call.


Every trust problem in the research pointed to one specific moment: the raffle. That was where users felt manipulated. That was where disengagement began. That was where the product was failing them most severely.


Instead of spreading across the entire platform, I focused entirely on rebuilding the raffle system as the core trust mechanism. Fix the raffle, and everything downstream engagement, retention, brand loyalty, follows.

Trust is not a byproduct of good design. At Snix, it had to be designed as a feature.

Rebuilding the raffle system

Reducing entry friction. The original entry flow required five steps and averaged 18 seconds to complete. I stripped it to two steps, size selection and confirmation reducing completion time to approximately 7 seconds. Fewer inputs meant fewer drop-offs, and a faster flow meant users could enter with confidence during tight release windows.

Anti-bot infrastructure. Time-bound entry windows, account verification layers, and single-entry enforcement reduced the structural advantage bots had over real users. This came with a tradeoff, slightly increased friction for legitimate users but the fairness gain was non-negotiable. I made that tradeoff explicitly and documented it for the team.

Reducing entry friction. The original entry flow required five steps and averaged 18 seconds to complete. I stripped it to two steps, size selection and confirmation reducing completion time to approximately 7 seconds. Fewer inputs meant fewer drop-offs, and a faster flow meant users could enter with confidence during tight release windows.

Anti-bot infrastructure. Time-bound entry windows, account verification layers, and single-entry enforcement reduced the structural advantage bots had over real users. This came with a tradeoff, slightly increased friction for legitimate users but the fairness gain was non-negotiable. I made that tradeoff explicitly and documented it for the team.

The transparency layer. This was the most significant innovation in the redesign. For the first time, users could see their entry confirmation, live raffle status open, closed, selecting and a plain-language explanation of how the outcome was determined.

When a raffle closed, instead of a binary win or lose notification, users saw: "Selected randomly from 12,482 verified entries." That single sentence answered every question users had been asking for years. It confirmed their entry was real. It confirmed the pool was large and competitive. And it confirmed the selection was random, not rigged.


The post-raffle experience. Previously, losing a raffle was a dead end. A notification, a closed door, nothing else. The redesign turned the loss state into an active moment: recommended alternatives surfaced based on style and size, upcoming drops relevant to the user's history, and a direct path to the secondary market for that specific shoe.

Winning was equally intentional, a direct purchase flow with the user's size pre-selected, minimal steps to checkout, and a clear countdown on the purchase window. The win state was designed to convert, not just celebrate.

The tradeoffs I made

Every meaningful design decision in this project involved a real tradeoff. I made these explicitly, not as compromises, but as intentional choices with documented reasoning.

Higher perceived fairness

No loyalty incentive for returning users

User trust through transparency

More complex system communication required

Bot resistance, real user priority

Slightly increased friction for all users

Faster entry, fewer drop-offs

Less customization per entry

Higher perceived fairness

No loyalty incentive for returning users

User trust through transparency

More complex system communication required

Bot resistance, real user priority

Slightly increased friction for all users

Faster entry, fewer drop-offs

Less customization per entry

Faster entry, fewer drop-offs

Less customization per entry

Bot resistance, real user priority

Slightly increased friction for all users

User trust through transparency

More complex system communication required

The most contested was the equal weight raffle versus a loyalty-based priority system. A loyalty model would reward returning users and incentivize engagement but it would also mean that users with more history had a statistically better chance of winning.


That directly contradicted the core trust argument. I chose fairness over loyalty, with full awareness that it left engagement incentives on the table.

60%

Reduction in entry friction, 5 steps to 2, 18s to 7s

95%

Task completion rate, up from 72% baseline

35%

Improvement in perceived fairness score

40%

Reduction in raffle entry drop-off rate

25%

Increase in post-loss engagement with alternatives

95%
Task completion rate, up from 72% baseline

35%

Improvement in perceived fairness score

40%
Reduction in raffle entry drop-off rate

25%

Increase in post-loss engagement with alternatives

users, after the redesign

"At least now I understand what's going on. It feels more legit."

"Seeing how many people entered makes it feel fair, even if I lose."

"I didn't win, but I didn't feel frustrated like before."

What changed

Outcomes were validated through moderated usability testing with 8 participants and directionally confirmed after launch with real users on the platform.

What changed

Outcomes were validated through moderated usability testing with 8 participants and directionally confirmed after launch with real users on the platform.

60%

Reduction in entry friction, 5 steps to 2, 18s to 7s

95%

Task completion rate, up from 72% baseline

35%

Improvement in perceived fairness score

40%

Reduction in raffle entry drop-off rate

25%

Increase in post-loss engagement with alternatives

60%

Reduction in entry friction, 5 steps to 2, 18s to 7s

95%

Task completion rate, up from 72% baseline

35%

Improvement in perceived fairness score

40%

Reduction in raffle entry drop-off rate

25%

Increase in post-loss engagement with alternatives

users, after the redesign

"At least now I understand what's going on. It feels more legit."

"Seeing how many people entered makes it feel fair, even if I lose."

"I didn't win, but I didn't feel frustrated like before."

users, after the redesign

"At least now I understand what's going on. It feels more legit."

"Seeing how many people entered makes it feel fair, even if I lose."

"I didn't win, but I didn't feel frustrated like before."

What I learned

"Systems drive impact. Screens just make it visible."


The biggest gains in this project came from selection logic, flow architecture, and feedback loops not visual polish. The transparency layer is a single sentence on a screen. But that sentence required designing the entire raffle system behind it: how entries are counted, how status is communicated in real time, how outcomes are explained at scale.


The second thing I learned: users tolerate loss when they understand why. Confusion is more damaging than disappointment. If you can design a system where losing still makes sense, where the user feels the outcome was legitimate andyou retain them for the next drop. That's the product lever most consumer platforms are missing.


And the third: the most important design decisions aren't interface decisions. Choosing equal weight raffle over loyalty priority was a product strategy call. I made it as the designer, brought it to the team with evidence, and owned the tradeoff. That's what senior product design actually looks like.

What I learned

"Systems drive impact. Screens just make it visible."

The biggest gains in this project came from selection logic, flow architecture, and feedback loops not visual polish. The transparency layer is a single sentence on a screen. But that sentence required designing the entire raffle system behind it: how entries are counted, how status is communicated in real time, how outcomes are explained at scale.

The second thing I learned: users tolerate loss when they understand why. Confusion is more damaging than disappointment. If you can design a system where losing still makes sense, where the user feels the outcome was legitimate andyou retain them for the next drop. That's the product lever most consumer platforms are missing.

And the third: the most important design decisions aren't interface decisions. Choosing equal weight raffle over loyalty priority was a product strategy call. I made it as the designer, brought it to the team with evidence, and owned the tradeoff. That's what senior product design actually looks like.

What I learned

"Systems drive impact. Screens just make it visible."

The biggest gains in this project came from selection logic, flow architecture, and feedback loops not visual polish. The transparency layer is a single sentence on a screen. But that sentence required designing the entire raffle system behind it: how entries are counted, how status is communicated in real time, how outcomes are explained at scale.

The second thing I learned: users tolerate loss when they understand why. Confusion is more damaging than disappointment. If you can design a system where losing still makes sense where the user feels the outcome was legitimate , you retain them for the next drop. That's the product lever most consumer platforms are missing.

And the third: the most important design decisions aren't interface decisions. Choosing equal-weight raffle over loyalty priority was a product strategy call. I made it as the designer, brought it to the team with evidence, and owned the tradeoff. That's what senior product design actually looks like.

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