Reimagining Fashion Shopping with AI
Exploring How AI Can Reduce Decision Fatigue in Fashion
Mobile App
|
B2B and eCommerce
|
Sept 2024 - Nov 2024
My Role
I was brought in early to help shape the problem, define the MVP, and design core flows that reduce decision fatigue while keeping users in control. I partnered closely with the founder and engineers from concept through MVP.
About the project
Finna is an early-stage fashion platform exploring how AI, personal style, and social context can make shopping feel calmer, more intentional, and enjoyable again.
Tools Used
CONTEXT: how i entered the problem
Framing the problem through initial stakeholder alignment
This project started unexpectedly.
The founder discovered my portfolio by accident while searching for someone else. When we spoke, we didn’t jump into features or roadmaps. We talked about something much more basic:
Why does shopping for clothes feel so draining now?
That conversation set the tone for my role, I wasn’t here to decorate an idea, I was here to help shape it.
Why is it not fun to go shopping?
The PROBLEM
Shopping for clothes is fragmented, inefficient, and mentally exhausting.
In-store experiences are burdened by travel, crowds, limited inventory, and inconsistent service. Online shopping replaces physical friction with cognitive overload, endless catalogs, site hopping, price uncertainty, and long shipping cycles.
Across both channels, shoppers face decision fatigue, logistical frustration, and growing tension with their environmental values—making clothing purchases feel stressful rather than rewarding.
SOLUTION
iTunes but for your closet. One centralized platform to manage your wardrobe, browse new looks, and purchase clothes from all the retailers you love.
Digital Closet: All your clothes in one place regardless of item, style, or retailer in one place
Outfits and collections: User-organized retailer-agnostic combinations of clothes assembled for specific occasions or events, types of weather, or to reflect a specific vibe.
AI-stylist and shopping agent: A one-stop user-friendly experience powered by AI to help users discover clothes and popular new styles, and to purchase individual items or entire outfits regardless of brand or retailer.
Discovery
Visualizing the vision through early wireframes
Before designing high-fidelity screens, I mapped the founder’s vision into a rough, low-fidelity flow. Seeing everything at once made the problem obvious: the experience felt heavy before a user even started shopping.
Fig. Visualizing Founder's Vision
I proposed a reset grounded in user behavior:
✅
Shifted the goal from “show everything” to “help users decide”.
✅
Anchored the experience in personal style and real wardrobes, not abstract inventory.
✅
Designed a phased MVP that proves emotional value and trust before scaling features.
To support this direction, I synthesized research from fashion platforms, behavioral patterns, and user conversations, focusing on how people feel during shopping, not just what they click.
Who are the end users?
Let's get a glimpse of the key users and their behaviors
target audience
Fashionable, vibe-driven subtype
Our demographic comprises adult women 18-35 with high social media and e-commerce engagement. This audience combines low effort with high expectations. They are digital-native, mobile-first, and prioritize ease of use and efficiency.
[WHO THEY ARE]
Values-oriented consumers
Strive for individuality and self-expression
Sociable and open-minded to dabble outside their comfort zone, “try on” something new, and “see how it feels”
Balances fashion idealism with practical/contextual and cost-conscious styling decisions
[WHAT THEY WANT]
To feel good (i.e., be true to themselves and their values, and to make smarter purchasing decisions) while looking good, no matter the environment or occasion.
[WHAT THEY NEED]
An easy, pleasurable way to look stylish without spending an excessive amount of time hopping from website to website and scrolling through product grids.
PHASE 1 (MVP)
To solve these challenges, we need to focus on doing a few things well…
FLOW 1 - Onboarding
Reducing Time-to-Value Through Smart Onboarding
I designed onboarding to reduce setup friction by using existing photos to instantly populate a user’s digital closet.
Decision: Use Instagram/Google photos during onboarding to recognize existing outfits
Impact: Reduced manual input, personalized the experience immediately, and shortened time-to-value
Fig. Onboarding pages
FLOW 2 - DISCOVERY
Reducing Choice Overload Through Social Discovery
I designed discovery to shift inspiration from endless product grids to real people and shared closets, making style exploration feel curated, relevant, and human.
Decision: Organize discovery around following people and shared closets rather than traditional category browsing.
Impact: Reduced cognitive load, increased relevance of recommendations, and made outfit discovery feel more confident and intentional.
Fig. Discovery pages
FLOW 3 – OUTFIT GENERATION & PURCHASE
From Intent to Outfit in a Single Flow
I designed this flow to help users move from vague intent (“I’ll know it when I see it”) to a complete outfit without manual searching or filtering.
Instead of starting with categories, users begin by selecting presets (occasion, weather, vibe) that translate abstract preferences into clear styling constraints. Finna then generates full outfits, allowing users to preview, refine, and move directly into purchase.
Decision: Use preset-based intent (occasion, weather, vibe) to generate complete outfits rather than item-by-item browsing.
Impact: Reduced decision fatigue, shortened path to purchase, and increased confidence by presenting cohesive outfits instead of isolated products.
Fig. Outfit generation pages
The Journey Behind the Design
Design is messgy
The final screens might look simple, but getting there was a process of trial and error. I didn't get it right on the first try; it took many versions and several pivots to find the right path.
Because I have a background in fashion, I already understood the specific "headaches" users face when putting an outfit together. Combining my industry knowledge with feedback from the founders, I was able to cut out the clutter and build a smooth, one-way flow from the user’s first thought to a finished look.
VALIDATION
From Intent to Outfit in a Single Flow
After shaping the core flows, I tested each touchpoint with real users to ensure it felt intuitive, helpful, and worth coming back to.
What if your wardrobe powered your shopping experience?
"I loved that the app already knew my style. I didn’t have to manually upload everything, and that alone saved me hours. It felt like I could actually start using the app right away.”
Rishanki Jain
32, Professional
"I loved that the app already knew my style. I didn’t have to manually upload everything, and that alone saved me hours. It felt like I could actually start using the app right away.”
Rishanki Jain
32, Professional
"I loved that the app already knew my style. I didn’t have to manually upload everything, and that alone saved me hours. It felt like I could actually start using the app right away.”
Rishanki Jain
32, Professional
Impact:
✅
Immediate Gratification
Users see a populated closet within seconds instead of an empty screen.
✅
Higher Retention
By removing the "work" of manual entry, users are more likely to reach the core shopping experience.
What happens when real people replace endless product grids?
"Shopping usually feels like a chore when I have to filter through thousands of items. Following people with similar taste makes the best outfits find me instead."
Rebecca Hofmann
29, Student
"Shopping usually feels like a chore when I have to filter through thousands of items. Following people with similar taste makes the best outfits find me instead."
Rebecca Hofmann
29, Student
"Shopping usually feels like a chore when I have to filter through thousands of items. Following people with similar taste makes the best outfits find me instead."
Rebecca Hofmann
29, Student
Impact:
✅
Reduced Choice Overload
Users skip the "infinite grid" and go straight to styles that match their taste.
✅
Confident Discovery
Following real closets makes fashion feel more human and intentional than a standard shop.
What happens when intent generates the entire outfit?
I used to spend forever trying to match pieces together. By picking a 'vibe' or the 'weather' instead of just browsing, I didn't have to think, the app just showed me what worked.
Melissa Eis Dominguez
35, Business Owner
I used to spend forever trying to match pieces together. By picking a 'vibe' or the 'weather' instead of just browsing, I didn't have to think, the app just showed me what worked.
Melissa Eis Dominguez
35, Business Owner
I used to spend forever trying to match pieces together. By picking a 'vibe' or the 'weather' instead of just browsing, I didn't have to think, the app just showed me what worked.
Melissa Eis Dominguez
35, Business Owner
Impact:
✅
Confidence at Checkout
Presenting full outfits instead of single items removes the "Will this look good?" doubt.
✅
Context-Driven Styling
By categorizing by vibe, weather, and occasion, the app provides relevant solutions immediately.
SHIPPING THE MVP
Working closely as a team
PHASE 2
Building with Restraint and Foresight
With the core experience validated around clarity and decision confidence, Phase 2 focused on how Finna could scale without compromising its principles. Rather than adding features, the focus shifted to extending value beyond the screen—connecting digital intent to real-world action.
Phase 2 balanced restraint in what we shipped with ambition in how the system could evolve.
MVP Focus —
Designing by Subtraction
To protect the experience, I helped define what stayed out of the MVP:
No infinite scrolling feeds
No complex social mechanics
No dark patterns or aggressive conversion nudges
The MVP had one goal:
Does this make shopping feel less overwhelming?
Systems Thinking — Designing beyond screens
Beyond UI, I explored how design could influence real-world behavior:
Local inventory discovery
Same-day delivery from nearby stores
Incentives for in-store pickup
These concepts extended the UX beyond the screen—supporting sustainability, local retail, and more intentional shopping behavior.
Key Lessons
Doing less made the product better
As a founder designer, I learned how tempting it is to keep adding ideas—especially with AI. This project taught me that the hardest and most important work was deciding what to leave out. The product became clearer and more useful once I focused on doing a few things really well.
Doing less made the product better
As a founder designer, I learned how tempting it is to keep adding ideas—especially with AI. This project taught me that the hardest and most important work was deciding what to leave out. The product became clearer and more useful once I focused on doing a few things really well.
Doing less made the product better
As a founder designer, I learned how tempting it is to keep adding ideas—especially with AI. This project taught me that the hardest and most important work was deciding what to leave out. The product became clearer and more useful once I focused on doing a few things really well.
Trust matters more than intelligence
Trust matters more than intelligence
Trust matters more than intelligence
Building the product meant holding everything together
Building the product meant holding everything together
Building the product meant holding everything together
Thank you for reading! 🤍
More Projects
More Projects
See more prjects
Reimagining Fashion Shopping with AI
Exploring How AI Can Reduce Decision Fatigue in Fashion
Mobile App
|
B2B and eCommerce
|
Sept 2024 - Nov 2024
My Role
I was brought in early to help shape the problem, define the MVP, and design core flows that reduce decision fatigue while keeping users in control. I partnered closely with the founder and engineers from concept through MVP.
About the project
Finna is an early-stage fashion platform exploring how AI, personal style, and social context can make shopping feel calmer, more intentional, and enjoyable again.
Tools Used
CONTEXT: how i entered the problem
Framing the problem through initial stakeholder alignment
This project started unexpectedly.
The founder discovered my portfolio by accident while searching for someone else. When we spoke, we didn’t jump into features or roadmaps. We talked about something much more basic:
Why does shopping for clothes feel so draining now?
That conversation set the tone for my role, I wasn’t here to decorate an idea, I was here to help shape it.
Why is it not fun to go shopping?
The PROBLEM
Shopping for clothes is fragmented, inefficient, and mentally exhausting.
In-store experiences are burdened by travel, crowds, limited inventory, and inconsistent service. Online shopping replaces physical friction with cognitive overload, endless catalogs, site hopping, price uncertainty, and long shipping cycles.
Across both channels, shoppers face decision fatigue, logistical frustration, and growing tension with their environmental values—making clothing purchases feel stressful rather than rewarding.
SOLUTION
iTunes but for your closet. One centralized platform to manage your wardrobe, browse new looks, and purchase clothes from all the retailers you love.
Digital Closet: All your clothes in one place regardless of item, style, or retailer in one place
Outfits and collections: User-organized retailer-agnostic combinations of clothes assembled for specific occasions or events, types of weather, or to reflect a specific vibe.
AI-stylist and shopping agent: A one-stop user-friendly experience powered by AI to help users discover clothes and popular new styles, and to purchase individual items or entire outfits regardless of brand or retailer.
Discovery
Visualizing the vision through early wireframes
Before designing high-fidelity screens, I mapped the founder’s vision into a rough, low-fidelity flow. Seeing everything at once made the problem obvious: the experience felt heavy before a user even started shopping.
Fig. Visualizing Founder's Vision
I proposed a reset grounded in user behavior:
✅
Shifted the goal from “show everything” to “help users decide”.
✅
Anchored the experience in personal style and real wardrobes, not abstract inventory.
✅
Designed a phased MVP that proves emotional value and trust before scaling features.
To support this direction, I synthesized research from fashion platforms, behavioral patterns, and user conversations, focusing on how people feel during shopping, not just what they click.
Who are the end users?
Let's get a glimpse of the key users and their behaviors
target audience
Fashionable, vibe-driven subtype
Our demographic comprises adult women 18-35 with high social media and e-commerce engagement. This audience combines low effort with high expectations. They are digital-native, mobile-first, and prioritize ease of use and efficiency.
[WHO THEY ARE]
Values-oriented consumers
Strive for individuality and self-expression
Sociable and open-minded to dabble outside their comfort zone, “try on” something new, and “see how it feels”
Balances fashion idealism with practical/contextual and cost-conscious styling decisions
[WHAT THEY WANT]
To feel good (i.e., be true to themselves and their values, and to make smarter purchasing decisions) while looking good, no matter the environment or occasion.
[WHAT THEY NEED]
An easy, pleasurable way to look stylish without spending an excessive amount of time hopping from website to website and scrolling through product grids.
PHASE 1 (MVP)
To solve these challenges, we need to focus on doing a few things well…
FLOW 1 - Onboarding
Reducing Time-to-Value Through Smart Onboarding
I designed onboarding to reduce setup friction by using existing photos to instantly populate a user’s digital closet.
Decision: Use Instagram/Google photos during onboarding to recognize existing outfits
Impact: Reduced manual input, personalized the experience immediately, and shortened time-to-value
Fig. Onboarding pages
FLOW 2 - DISCOVERY
Reducing Choice Overload Through Social Discovery
I designed discovery to shift inspiration from endless product grids to real people and shared closets, making style exploration feel curated, relevant, and human.
Decision: Organize discovery around following people and shared closets rather than traditional category browsing.
Impact: Reduced cognitive load, increased relevance of recommendations, and made outfit discovery feel more confident and intentional.
Fig. Discovery pages
FLOW 3 – OUTFIT GENERATION & PURCHASE
From Intent to Outfit in a Single Flow
I designed this flow to help users move from vague intent (“I’ll know it when I see it”) to a complete outfit without manual searching or filtering.
Instead of starting with categories, users begin by selecting presets (occasion, weather, vibe) that translate abstract preferences into clear styling constraints. Finna then generates full outfits, allowing users to preview, refine, and move directly into purchase.
Decision: Use preset-based intent (occasion, weather, vibe) to generate complete outfits rather than item-by-item browsing.
Impact: Reduced decision fatigue, shortened path to purchase, and increased confidence by presenting cohesive outfits instead of isolated products.
Fig. Outfit generation pages
The Journey Behind the Design
Design is messgy
The final screens might look simple, but getting there was a process of trial and error. I didn't get it right on the first try; it took many versions and several pivots to find the right path.
Because I have a background in fashion, I already understood the specific "headaches" users face when putting an outfit together. Combining my industry knowledge with feedback from the founders, I was able to cut out the clutter and build a smooth, one-way flow from the user’s first thought to a finished look.
VALIDATION
From Intent to Outfit in a Single Flow
After shaping the core flows, I tested each touchpoint with real users to ensure it felt intuitive, helpful, and worth coming back to.
What if your wardrobe powered your shopping experience?
"I loved that the app already knew my style. I didn’t have to manually upload everything, and that alone saved me hours. It felt like I could actually start using the app right away.”
Rishanki Jain
32, Professional
"I loved that the app already knew my style. I didn’t have to manually upload everything, and that alone saved me hours. It felt like I could actually start using the app right away.”
Rishanki Jain
32, Professional
"I loved that the app already knew my style. I didn’t have to manually upload everything, and that alone saved me hours. It felt like I could actually start using the app right away.”
Rishanki Jain
32, Professional
Impact:
✅
Immediate Gratification
Users see a populated closet within seconds instead of an empty screen.
✅
Higher Retention
By removing the "work" of manual entry, users are more likely to reach the core shopping experience.
What happens when real people replace endless product grids?
"Shopping usually feels like a chore when I have to filter through thousands of items. Following people with similar taste makes the best outfits find me instead."
Rebecca Hofmann
29, Student
"Shopping usually feels like a chore when I have to filter through thousands of items. Following people with similar taste makes the best outfits find me instead."
Rebecca Hofmann
29, Student
"Shopping usually feels like a chore when I have to filter through thousands of items. Following people with similar taste makes the best outfits find me instead."
Rebecca Hofmann
29, Student
Impact:
✅
Reduced Choice Overload
Users skip the "infinite grid" and go straight to styles that match their taste.
✅
Confident Discovery
Following real closets makes fashion feel more human and intentional than a standard shop.
What happens when intent generates the entire outfit?
I used to spend forever trying to match pieces together. By picking a 'vibe' or the 'weather' instead of just browsing, I didn't have to think, the app just showed me what worked.
Melissa Eis Dominguez
35, Business Owner
I used to spend forever trying to match pieces together. By picking a 'vibe' or the 'weather' instead of just browsing, I didn't have to think, the app just showed me what worked.
Melissa Eis Dominguez
35, Business Owner
I used to spend forever trying to match pieces together. By picking a 'vibe' or the 'weather' instead of just browsing, I didn't have to think, the app just showed me what worked.
Melissa Eis Dominguez
35, Business Owner
Impact:
✅
Confidence at Checkout
Presenting full outfits instead of single items removes the "Will this look good?" doubt.
✅
Context-Driven Styling
By categorizing by vibe, weather, and occasion, the app provides relevant solutions immediately.
SHIPPING THE MVP
Working closely as a team
PHASE 2
Building with Restraint and Foresight
With the core experience validated around clarity and decision confidence, Phase 2 focused on how Finna could scale without compromising its principles. Rather than adding features, the focus shifted to extending value beyond the screen—connecting digital intent to real-world action.
Phase 2 balanced restraint in what we shipped with ambition in how the system could evolve.
MVP Focus —
Designing by Subtraction
To protect the experience, I helped define what stayed out of the MVP:
No infinite scrolling feeds
No complex social mechanics
No dark patterns or aggressive conversion nudges
The MVP had one goal:
Does this make shopping feel less overwhelming?
Systems Thinking — Designing beyond screens
Beyond UI, I explored how design could influence real-world behavior:
Local inventory discovery
Same-day delivery from nearby stores
Incentives for in-store pickup
These concepts extended the UX beyond the screen—supporting sustainability, local retail, and more intentional shopping behavior.
Key Lessons
Doing less made the product better
As a founder designer, I learned how tempting it is to keep adding ideas—especially with AI. This project taught me that the hardest and most important work was deciding what to leave out. The product became clearer and more useful once I focused on doing a few things really well.
Doing less made the product better
As a founder designer, I learned how tempting it is to keep adding ideas—especially with AI. This project taught me that the hardest and most important work was deciding what to leave out. The product became clearer and more useful once I focused on doing a few things really well.
Doing less made the product better
As a founder designer, I learned how tempting it is to keep adding ideas—especially with AI. This project taught me that the hardest and most important work was deciding what to leave out. The product became clearer and more useful once I focused on doing a few things really well.
Trust matters more than intelligence
Trust matters more than intelligence
Trust matters more than intelligence
Building the product meant holding everything together
Building the product meant holding everything together
Building the product meant holding everything together
Thank you for reading! 🤍
More Projects
More Projects
See more prjects
Reimagining Fashion Shopping with AI
Exploring How AI Can Reduce Decision Fatigue in Fashion
Mobile App
|
B2B and eCommerce
|
Sept 2024 - Nov 2024
My Role
I was brought in early to help shape the problem, define the MVP, and design core flows that reduce decision fatigue while keeping users in control. I partnered closely with the founder and engineers from concept through MVP.
About the project
Finna is an early-stage fashion platform exploring how AI, personal style, and social context can make shopping feel calmer, more intentional, and enjoyable again.
Tools Used
CONTEXT: how i entered the problem
Framing the problem through initial stakeholder alignment
This project started unexpectedly.
The founder discovered my portfolio by accident while searching for someone else. When we spoke, we didn’t jump into features or roadmaps. We talked about something much more basic:
Why does shopping for clothes feel so draining now?
That conversation set the tone for my role, I wasn’t here to decorate an idea, I was here to help shape it.
Why is it not fun to go shopping?
The PROBLEM
Shopping for clothes is fragmented, inefficient, and mentally exhausting.
In-store experiences are burdened by travel, crowds, limited inventory, and inconsistent service. Online shopping replaces physical friction with cognitive overload, endless catalogs, site hopping, price uncertainty, and long shipping cycles.
Across both channels, shoppers face decision fatigue, logistical frustration, and growing tension with their environmental values—making clothing purchases feel stressful rather than rewarding.
SOLUTION
iTunes but for your closet. One centralized platform to manage your wardrobe, browse new looks, and purchase clothes from all the retailers you love.
Digital Closet: All your clothes in one place regardless of item, style, or retailer in one place
Outfits and collections: User-organized retailer-agnostic combinations of clothes assembled for specific occasions or events, types of weather, or to reflect a specific vibe.
AI-stylist and shopping agent: A one-stop user-friendly experience powered by AI to help users discover clothes and popular new styles, and to purchase individual items or entire outfits regardless of brand or retailer.
Discovery
Visualizing the vision through early wireframes
Before designing high-fidelity screens, I mapped the founder’s vision into a rough, low-fidelity flow. Seeing everything at once made the problem obvious: the experience felt heavy before a user even started shopping.
Fig. Visualizing Founder's Vision
I proposed a reset grounded in user behavior:
✅
Shifted the goal from “show everything” to “help users decide”.
✅
Anchored the experience in personal style and real wardrobes, not abstract inventory.
✅
Designed a phased MVP that proves emotional value and trust before scaling features.
To support this direction, I synthesized research from fashion platforms, behavioral patterns, and user conversations, focusing on how people feel during shopping, not just what they click.
Who are the end users?
Let's get a glimpse of the key users and their behaviors
target audience
Fashionable, vibe-driven subtype
Our demographic comprises adult women 18-35 with high social media and e-commerce engagement. This audience combines low effort with high expectations. They are digital-native, mobile-first, and prioritize ease of use and efficiency.
[WHO THEY ARE]
Values-oriented consumers
Strive for individuality and self-expression
Sociable and open-minded to dabble outside their comfort zone, “try on” something new, and “see how it feels”
Balances fashion idealism with practical/contextual and cost-conscious styling decisions
[WHAT THEY WANT]
To feel good (i.e., be true to themselves and their values, and to make smarter purchasing decisions) while looking good, no matter the environment or occasion.
[WHAT THEY NEED]
An easy, pleasurable way to look stylish without spending an excessive amount of time hopping from website to website and scrolling through product grids.
PHASE 1 (MVP)
To solve these challenges, we need to focus on doing a few things well…
FLOW 1 - Onboarding
Reducing Time-to-Value Through Smart Onboarding
I designed onboarding to reduce setup friction by using existing photos to instantly populate a user’s digital closet.
Decision: Use Instagram/Google photos during onboarding to recognize existing outfits
Impact: Reduced manual input, personalized the experience immediately, and shortened time-to-value
Fig. Onboarding pages
FLOW 2 - DISCOVERY
Reducing Choice Overload Through Social Discovery
I designed discovery to shift inspiration from endless product grids to real people and shared closets, making style exploration feel curated, relevant, and human.
Decision: Organize discovery around following people and shared closets rather than traditional category browsing.
Impact: Reduced cognitive load, increased relevance of recommendations, and made outfit discovery feel more confident and intentional.
Fig. Discovery pages
FLOW 3 – OUTFIT GENERATION & PURCHASE
From Intent to Outfit in a Single Flow
I designed this flow to help users move from vague intent (“I’ll know it when I see it”) to a complete outfit without manual searching or filtering.
Instead of starting with categories, users begin by selecting presets (occasion, weather, vibe) that translate abstract preferences into clear styling constraints. Finna then generates full outfits, allowing users to preview, refine, and move directly into purchase.
Decision: Use preset-based intent (occasion, weather, vibe) to generate complete outfits rather than item-by-item browsing.
Impact: Reduced decision fatigue, shortened path to purchase, and increased confidence by presenting cohesive outfits instead of isolated products.
Fig. Outfit generation pages
The Journey Behind the Design
Design is messgy
The final screens might look simple, but getting there was a process of trial and error. I didn't get it right on the first try; it took many versions and several pivots to find the right path.
Because I have a background in fashion, I already understood the specific "headaches" users face when putting an outfit together. Combining my industry knowledge with feedback from the founders, I was able to cut out the clutter and build a smooth, one-way flow from the user’s first thought to a finished look.
VALIDATION
From Intent to Outfit in a Single Flow
After shaping the core flows, I tested each touchpoint with real users to ensure it felt intuitive, helpful, and worth coming back to.
What if your wardrobe powered your shopping experience?
"I loved that the app already knew my style. I didn’t have to manually upload everything, and that alone saved me hours. It felt like I could actually start using the app right away.”
Rishanki Jain
32, Professional
"I loved that the app already knew my style. I didn’t have to manually upload everything, and that alone saved me hours. It felt like I could actually start using the app right away.”
Rishanki Jain
32, Professional
"I loved that the app already knew my style. I didn’t have to manually upload everything, and that alone saved me hours. It felt like I could actually start using the app right away.”
Rishanki Jain
32, Professional
Impact:
✅
Immediate Gratification
Users see a populated closet within seconds instead of an empty screen.
✅
Higher Retention
By removing the "work" of manual entry, users are more likely to reach the core shopping experience.
What happens when real people replace endless product grids?
"Shopping usually feels like a chore when I have to filter through thousands of items. Following people with similar taste makes the best outfits find me instead."
Rebecca Hofmann
29, Student
"Shopping usually feels like a chore when I have to filter through thousands of items. Following people with similar taste makes the best outfits find me instead."
Rebecca Hofmann
29, Student
"Shopping usually feels like a chore when I have to filter through thousands of items. Following people with similar taste makes the best outfits find me instead."
Rebecca Hofmann
29, Student
Impact:
✅
Reduced Choice Overload
Users skip the "infinite grid" and go straight to styles that match their taste.
✅
Confident Discovery
Following real closets makes fashion feel more human and intentional than a standard shop.
What happens when intent generates the entire outfit?
I used to spend forever trying to match pieces together. By picking a 'vibe' or the 'weather' instead of just browsing, I didn't have to think, the app just showed me what worked.
Melissa Eis Dominguez
35, Business Owner
I used to spend forever trying to match pieces together. By picking a 'vibe' or the 'weather' instead of just browsing, I didn't have to think, the app just showed me what worked.
Melissa Eis Dominguez
35, Business Owner
I used to spend forever trying to match pieces together. By picking a 'vibe' or the 'weather' instead of just browsing, I didn't have to think, the app just showed me what worked.
Melissa Eis Dominguez
35, Business Owner
Impact:
✅
Confidence at Checkout
Presenting full outfits instead of single items removes the "Will this look good?" doubt.
✅
Context-Driven Styling
By categorizing by vibe, weather, and occasion, the app provides relevant solutions immediately.
SHIPPING THE MVP
Working closely as a team
PHASE 2
Building with Restraint and Foresight
With the core experience validated around clarity and decision confidence, Phase 2 focused on how Finna could scale without compromising its principles. Rather than adding features, the focus shifted to extending value beyond the screen—connecting digital intent to real-world action.
Phase 2 balanced restraint in what we shipped with ambition in how the system could evolve.
MVP Focus —
Designing by Subtraction
To protect the experience, I helped define what stayed out of the MVP:
No infinite scrolling feeds
No complex social mechanics
No dark patterns or aggressive conversion nudges
The MVP had one goal:
Does this make shopping feel less overwhelming?
Systems Thinking — Designing beyond screens
Beyond UI, I explored how design could influence real-world behavior:
Local inventory discovery
Same-day delivery from nearby stores
Incentives for in-store pickup
These concepts extended the UX beyond the screen—supporting sustainability, local retail, and more intentional shopping behavior.
Key Lessons
Doing less made the product better
As a founder designer, I learned how tempting it is to keep adding ideas—especially with AI. This project taught me that the hardest and most important work was deciding what to leave out. The product became clearer and more useful once I focused on doing a few things really well.
Doing less made the product better
As a founder designer, I learned how tempting it is to keep adding ideas—especially with AI. This project taught me that the hardest and most important work was deciding what to leave out. The product became clearer and more useful once I focused on doing a few things really well.
Doing less made the product better
As a founder designer, I learned how tempting it is to keep adding ideas—especially with AI. This project taught me that the hardest and most important work was deciding what to leave out. The product became clearer and more useful once I focused on doing a few things really well.
Trust matters more than intelligence
Trust matters more than intelligence
Trust matters more than intelligence
Building the product meant holding everything together
Building the product meant holding everything together
Building the product meant holding everything together
Thank you for reading! 🤍
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