AuthenIQ
AuthenIQ
AuthenIQ
iOS & Android Mobile App
iOS & Android Mobile App
iOS & Android Mobile App
Overview
Overview
AuthenIQ tells resellers, small shops and collectors whether a luxury item is real, in seconds. Before it existed, the options were shipping the bag to a facility and waiting a day or two, or guessing. Neither of those works when you have five minutes to decide whether to buy something.
AuthenIQ tells resellers, small shops and collectors whether a luxury item is real, in seconds. Before it existed, the options were shipping the bag to a facility and waiting a day or two, or guessing. Neither of those works when you have five minutes to decide whether to buy something.
I designed the mobile experience end to end. Time to a first scan dropped from eight minutes to under 60 seconds, the new features tripled projected daily use, and the free tier finally has an honest reason to upgrade, with a path to 10% or better conversion.
I designed the mobile experience end to end. Time to a first scan dropped from eight minutes to under 60 seconds, the new features tripled projected daily use, and the free tier finally has an honest reason to upgrade, with a path to 10% or better conversion.
Tech Stack
Figma
Design Tool
Notion
Documentation
Maze
Testing
Miro
Mapping
Tech Stack
Figma
Design Tool
Notion
Documentation
Maze
Testing
Miro
Mapping
Tech Stack
Figma
Design Tool
Notion
Documentation
Maze
Testing
Miro
Mapping
ROLE
ROLE
Lead Product Designer
DURATION
DURATION
8 weeks
PLATFORM
PLATFORM
Authentication App
How I worked
The work behind AuthenIQ was iterative and grounded in how resellers actually operate. I started with research into how people handle authentication and market data, and where the information overload sets in. That fed wireframes built around simplicity, guided actions and clear hierarchy. Several rounds of prototyping and testing later, onboarding and the dashboard felt obvious rather than clever.
How I worked
The work behind AuthenIQ was iterative and grounded in how resellers actually operate. I started with research into how people handle authentication and market data, and where the information overload sets in. That fed wireframes built around simplicity, guided actions and clear hierarchy. Several rounds of prototyping and testing later, onboarding and the dashboard felt obvious rather than clever.
The problem
The luxury resale market is exploding. We’re talking about a $50B+ industry by 2025, growing 15% year over year. But here’s the thing: counterfeit goods are increasing just as fast. For every authentic Louis Vuitton Neverfull on the market, there are three fakes.
This creates a massive problem for resellers. They’re the middle people between individual sellers and buyers, and their entire business depends on trust. One fake item can destroy their reputation, cost them thousands in chargebacks, or even get them banned from platforms like eBay and Poshmark.
The existing solution wasn’t working
When we started this project, the authentication landscape looked like this: Manual authentication services
Ship your item to a facility
Wait 24-48 hours for results
Pay $20-50 per item
Get a certificate back
Early digital solutions
Take photos yourself
Upload to an app
Wait 2-6 hours for “expert review”
Get a yes/no answer with no context
Both approaches had the same fundamental problem: they were too slow for the pace of reselling. One person we interviewed put it perfectly.
“I’m at an estate sale. I found a Chanel bag for $300. I need to know RIGHT NOW if it’s real, because three other people are looking at it. If I have to wait 24 hours, I’ve already lost the opportunity.”
The problem
The luxury resale market is exploding. We’re talking about a $50B+ industry by 2025, growing 15% year over year. But here’s the thing: counterfeit goods are increasing just as fast. For every authentic Louis Vuitton Neverfull on the market, there are three fakes.
This creates a massive problem for resellers. They’re the middle people between individual sellers and buyers, and their entire business depends on trust. One fake item can destroy their reputation, cost them thousands in chargebacks, or even get them banned from platforms like eBay and Poshmark.
The existing solution wasn’t working
When we started this project, the authentication landscape looked like this: Manual authentication services
Ship your item to a facility
Wait 24-48 hours for results
Pay $20-50 per item
Get a certificate back
Early digital solutions
Take photos yourself
Upload to an app
Wait 2-6 hours for “expert review”
Get a yes/no answer with no context
Both approaches had the same fundamental problem: they were too slow for the pace of reselling. One person we interviewed put it perfectly.
“I’m at an estate sale. I found a Chanel bag for $300. I need to know RIGHT NOW if it’s real, because three other people are looking at it. If I have to wait 24 hours, I’ve already lost the opportunity.”
The problem
The luxury resale market is exploding. We’re talking about a $50B+ industry by 2025, growing 15% year over year. But here’s the thing: counterfeit goods are increasing just as fast. For every authentic Louis Vuitton Neverfull on the market, there are three fakes.
This creates a massive problem for resellers. They’re the middle people between individual sellers and buyers, and their entire business depends on trust. One fake item can destroy their reputation, cost them thousands in chargebacks, or even get them banned from platforms like eBay and Poshmark.
The existing solution wasn’t working
When we started this project, the authentication landscape looked like this: Manual authentication services
Ship your item to a facility
Wait 24-48 hours for results
Pay $20-50 per item
Get a certificate back
Early digital solutions
Take photos yourself
Upload to an app
Wait 2-6 hours for “expert review”
Get a yes/no answer with no context
Both approaches had the same fundamental problem: they were too slow for the pace of reselling. One person we interviewed put it perfectly.
“I’m at an estate sale. I found a Chanel bag for $300. I need to know RIGHT NOW if it’s real, because three other people are looking at it. If I have to wait 24 hours, I’ve already lost the opportunity.”
Who we were designing for
Through our initial research, we identified three core user types:
The Hustler (40% of market)
Reselling as a side income
Scanning 5-15 items per week
Learning as they go
Price-sensitive but willing to pay for proven value
The Pro (35% of market)
Full-time reseller
Scanning 20-50 items per week
Highly knowledgeable
Needs speed and bulk features
The Store Owner (25% of market)
Running a small business or online shop
Scanning 50+ items per week
Needs inventory management
Willing to pay a premium for B2B features
Each group had different needs, but they all shared one thing: they needed speed, confidence, and context.
Who we were designing for
Through our initial research, we identified three core user types:
The Hustler (40% of market)
Reselling as a side income
Scanning 5-15 items per week
Learning as they go
Price-sensitive but willing to pay for proven value
The Pro (35% of market)
Full-time reseller
Scanning 20-50 items per week
Highly knowledgeable
Needs speed and bulk features
The Store Owner (25% of market)
Running a small business or online shop
Scanning 50+ items per week
Needs inventory management
Willing to pay a premium for B2B features
Each group had different needs, but they all shared one thing: they needed speed, confidence, and context.
Discovery & Research
How we approached the problem
Before opening Figma, I wanted to understand what reselling actually looks like in real life how people decide, how fast they move, and where things break. So the first two weeks were spent talking to users, watching their workflows, and validating what really matters to them.
Talking to real resellers
We interviewed 12 resellers of different experience levels. The conversations were simple and honest we asked them to walk us through how they pick items, how they verify authenticity, and what stresses them the most.
A few themes came up again and again:
Speed is everything.
If they don’t act fast, someone else grabs the item.Nobody fully trusts themselves or one app.
They cross-check with friends, Facebook groups, Reddit, or past screenshots.Profit decides whether they even care to authenticate.
“If I won’t make money on it, why waste time scanning?”Learning is part of the fun.
Many take pride in “spotting fakes” with their own eyes.Status actually matters.
Big profits, rare finds, and high accuracy become social proof.
These insights later shaped our design principles around speed, confidence, and community.
Watching them in action
We also did 3 “ride-alongs” following resellers during thrift trips and at-home sorting sessions.
This is where everything clicked:
In thrift stores, they move fast—checking prices and scanning items in seconds.
At home, the process becomes slower but fragmented across apps, Google, and chats.
No single tool supported the whole journey from spot → check → decide → sell.
This told us exactly where the new experience needed to fit.
A quick survey to validate
To make sure our interviews weren’t outliers, we ran a short survey in Facebook reselling groups (82 responses).
Most authenticate 5+ items per week
90% said existing tools are too slow
Many were willing to pay monthly for faster, unlimited scans
Price checking and community advice were just as common as scanning
Discovery & Research
How we approached the problem
Before opening Figma, I wanted to understand what reselling actually looks like in real life how people decide, how fast they move, and where things break. So the first two weeks were spent talking to users, watching their workflows, and validating what really matters to them.
Talking to real resellers
We interviewed 12 resellers of different experience levels. The conversations were simple and honest we asked them to walk us through how they pick items, how they verify authenticity, and what stresses them the most.
A few themes came up again and again:
Speed is everything.
If they don’t act fast, someone else grabs the item.Nobody fully trusts themselves or one app.
They cross-check with friends, Facebook groups, Reddit, or past screenshots.Profit decides whether they even care to authenticate.
“If I won’t make money on it, why waste time scanning?”Learning is part of the fun.
Many take pride in “spotting fakes” with their own eyes.Status actually matters.
Big profits, rare finds, and high accuracy become social proof.
These insights later shaped our design principles around speed, confidence, and community.
Watching them in action
We also did 3 “ride-alongs” following resellers during thrift trips and at-home sorting sessions.
This is where everything clicked:
In thrift stores, they move fast—checking prices and scanning items in seconds.
At home, the process becomes slower but fragmented across apps, Google, and chats.
No single tool supported the whole journey from spot → check → decide → sell.
This told us exactly where the new experience needed to fit.
A quick survey to validate
To make sure our interviews weren’t outliers, we ran a short survey in Facebook reselling groups (82 responses).
Most authenticate 5+ items per week
90% said existing tools are too slow
Many were willing to pay monthly for faster, unlimited scans
Price checking and community advice were just as common as scanning
Discovery & Research
How we approached the problem
Before opening Figma, I wanted to understand what reselling actually looks like in real life how people decide, how fast they move, and where things break. So the first two weeks were spent talking to users, watching their workflows, and validating what really matters to them.
Talking to real resellers
We interviewed 12 resellers of different experience levels. The conversations were simple and honest we asked them to walk us through how they pick items, how they verify authenticity, and what stresses them the most.
A few themes came up again and again:
Speed is everything.
If they don’t act fast, someone else grabs the item.Nobody fully trusts themselves or one app.
They cross-check with friends, Facebook groups, Reddit, or past screenshots.Profit decides whether they even care to authenticate.
“If I won’t make money on it, why waste time scanning?”Learning is part of the fun.
Many take pride in “spotting fakes” with their own eyes.Status actually matters.
Big profits, rare finds, and high accuracy become social proof.
These insights later shaped our design principles around speed, confidence, and community.
Watching them in action
We also did 3 “ride-alongs” following resellers during thrift trips and at-home sorting sessions.
This is where everything clicked:
In thrift stores, they move fast—checking prices and scanning items in seconds.
At home, the process becomes slower but fragmented across apps, Google, and chats.
No single tool supported the whole journey from spot → check → decide → sell.
This told us exactly where the new experience needed to fit.
A quick survey to validate
To make sure our interviews weren’t outliers, we ran a short survey in Facebook reselling groups (82 responses).
Most authenticate 5+ items per week
90% said existing tools are too slow
Many were willing to pay monthly for faster, unlimited scans
Price checking and community advice were just as common as scanning
Competitive Analysis
Understanding the landscape before defining our opportunity
I looked at eight platforms: five direct authentication tools and three adjacent resale marketplaces. Less about comparing feature lists, more about what users had come to expect, where nobody was serving them, and where AuthenIQ could be genuinely different.
Competitive Analysis
Understanding the landscape before defining our opportunity
I looked at eight platforms: five direct authentication tools and three adjacent resale marketplaces. Less about comparing feature lists, more about what users had come to expect, where nobody was serving them, and where AuthenIQ could be genuinely different.
Information Architecture
Before jumping into wireframes, I mapped out the entire information architecture. With a small team and a tight timeline, I had to be strategic about where resources were allocated.
Information Architecture
Before jumping into wireframes, I mapped out the entire information architecture. With a small team and a tight timeline, I had to be strategic about where resources were allocated.
Design Principles
The guidelines that shaped every decision
After our research, it became clear that users weren’t just looking for an authentication tool, they were trying to make fast, informed, confident business decisions. To keep us aligned, I defined three design principles that served as our compass throughout the project.
Each principle acted as a guardrail whenever we had to make tradeoffs, ensuring the final product supported how resellers actually work.
Onboarding That Builds Confidence
The three-step onboarding flow introduces features progressively, starting with authentication basics and revealing market intelligence capabilities as users gain confidence with the core functionality.
92% Completion | 2.3min Avg Time | 3 steps To Active
Market Intelligence Drives Action
Critical market data appears immediately upon scanning, with profit margins and market values prominently displayed before authentication details. This hierarchy ensures users understand the financial opportunity first.
$450 Avg Profi | 1.8s To Value | 78% Convert
Every Step Visible, Every Result Verified
The authentication process shows real-time progress with detailed confidence scores and verification steps. Community validation and transparent scoring build trust in the results.
98% Accuracy | 4.8★ Trust Score | 12k+ Verified
Design Principles
The guidelines that shaped every decision
After our research, it became clear that users weren’t just looking for an authentication tool, they were trying to make fast, informed, confident business decisions. To keep us aligned, I defined three design principles that served as our compass throughout the project.
Each principle acted as a guardrail whenever we had to make tradeoffs, ensuring the final product supported how resellers actually work.
Onboarding That Builds Confidence
The three-step onboarding flow introduces features progressively, starting with authentication basics and revealing market intelligence capabilities as users gain confidence with the core functionality.
92% Completion | 2.3min Avg Time | 3 steps To Active
Market Intelligence Drives Action
Critical market data appears immediately upon scanning, with profit margins and market values prominently displayed before authentication details. This hierarchy ensures users understand the financial opportunity first.
$450 Avg Profi | 1.8s To Value | 78% Convert
Every Step Visible, Every Result Verified
The authentication process shows real-time progress with detailed confidence scores and verification steps. Community validation and transparent scoring build trust in the results.
98% Accuracy | 4.8★ Trust Score | 12k+ Verified
Design Principles
The guidelines that shaped every decision
After our research, it became clear that users weren’t just looking for an authentication tool, they were trying to make fast, informed, confident business decisions. To keep us aligned, I defined three design principles that served as our compass throughout the project.
Each principle acted as a guardrail whenever we had to make tradeoffs, ensuring the final product supported how resellers actually work.
Onboarding That Builds Confidence
The three-step onboarding flow introduces features progressively, starting with authentication basics and revealing market intelligence capabilities as users gain confidence with the core functionality.
92% Completion | 2.3min Avg Time | 3 steps To Active
Market Intelligence Drives Action
Critical market data appears immediately upon scanning, with profit margins and market values prominently displayed before authentication details. This hierarchy ensures users understand the financial opportunity first.
$450 Avg Profi | 1.8s To Value | 78% Convert
Every Step Visible, Every Result Verified
The authentication process shows real-time progress with detailed confidence scores and verification steps. Community validation and transparent scoring build trust in the results.
98% Accuracy | 4.8★ Trust Score | 12k+ Verified
Wireframes
The wireframes set structure before style: navigation, dashboard metrics and onboarding steps, so we could test whether the flow held up before anyone argued about colour. It let the team validate usability and tighten interactions early, while changes were still cheap.
Wireframes
The wireframes set structure before style: navigation, dashboard metrics and onboarding steps, so we could test whether the flow held up before anyone argued about colour. It let the team validate usability and tighten interactions early, while changes were still cheap.
The home screen
Home is a quick read on how the business is doing: total profit, how many items you have authenticated, and how accurate you have been. Streaks, rank and tier sit alongside that, because the resellers we spoke to are competitive people and it turns out that helps. Underneath, Quick Scan, Bulk Mode and the Profit Calculator are one tap away, and the Live Feed and Trending Now show what is actually moving right now.
The home screen
Home is a quick read on how the business is doing: total profit, how many items you have authenticated, and how accurate you have been. Streaks, rank and tier sit alongside that, because the resellers we spoke to are competitive people and it turns out that helps. Underneath, Quick Scan, Bulk Mode and the Profit Calculator are one tap away, and the Live Feed and Trending Now show what is actually moving right now.
What happened after launch
After launch, more people finished onboarding, got to their first scan faster, and hit fewer errors. The new features made it easier to make decisions on real data rather than instinct, and community participation and weekly activity both grew steadily. Onboarding completion rose 85%, time to first action fell 40%, error rate in bulk authentications dropped 15%, and weekly active users climbed 70%. Free-to-paid conversion lifted 28%.
What happened after launch
After launch, more people finished onboarding, got to their first scan faster, and hit fewer errors. The new features made it easier to make decisions on real data rather than instinct, and community participation and weekly activity both grew steadily. Onboarding completion rose 85%, time to first action fell 40%, error rate in bulk authentications dropped 15%, and weekly active users climbed 70%. Free-to-paid conversion lifted 28%.
