What went well
As a larger team we interviewed a large group of people giving us better results
We pinpointed key focus areas and identified others needing more research.
We built upon the Stakeholders' initial research, pinpointing the target audience and providing suggestions to broaden it across different age groups.
What could have gone better
Due to company being a startup we had little to work from. Had we had more idea about the companies values, tone etc we could have applied this to our research.
Next steps
Continue research Into target audience
Leverage unique brand attributes to differentiate from competitors and create a memorable brand identity.
Encourage customer feedback and community building
to create a loyal customer base and improve product offeringsStrengthen partnerships and collaborations to expand
brand visibility and tap into new markets
© Robert Beeton 2024
Conclusions
Next Steps
Red appears weak
Green appears weak
Colours appears weak
It is important to remember that users may have visual impairments where they see colours in different ways. I ran colour blindness tests to identify how designs would look to people with red, green and monochromatic colour blindness
Colour Blindness Testing
I chose colours that felt modern and thought would fit well with the brand but also were WCAG AA compliant. This takes into consideration people with accessible needs.
h
1
h
2
Button
1
Image
Link
1
Input
1
Text sizing for the app concept screens maintained a minimal pixel size of 16px to meet WCAG compliance.
Text Sizing
Concept: Even though a design had not been created, I wanted to add a little colour to my end process to demonstrate what the app could look like. I also tested the colours to make sure they met WCAG AA compliant.
Colour Contrast Testing
Concept
Accessibility
Tests Revealed
Extra postage costs when redirected to third-party sites for purchases
I Identified
Preferred end process
Tests Revealed
Necessity for an offline viewing version of the shopping list
I Identified
Areas for improvement
Tests Revealed
Extra postage costs when redirected to third-party sites for purchases
I Identified
I adjusted the layout placement, added extra info, and enhanced usability.
Key findings from Usability Testing
I built upon previously added products in the saved list and used feedback to inform the transition to wireframing. I transformed sketches into Figma wireframes, refining designs and gathering feedback to improve usability. I also created high-fidelity versions to demonstrate what the final design could look like.
Paper Sketches, Low & High Fidelity Wireframes
Privacy
Concerns about privacy and how the app uses data
Customisation
Opportunity to add the ability to input measurements
Experience
Hopes the app is intuitive and has a glitch free try- on experience
Personalised
User wants a wide range of clothes, specifically brands he likes
Monetise
Utilise to ability to monetise purchase links
Seemless Experience
Provide the ability to purchase products in app
User research revealed focus areas for usability testing, notably the app's limitation to try-on experiences without in-app purchasing options. Two processes below were tested:
User Testing
User Testing - End Process
Key findings from Experience Map
Research & Planning
Experience Mapping
Research & Planning
User Personas & User Stories
Measurements
Users emphasized the importance of adding personal measurements like height, waist, and bust to improve the AI's accuracy in mapping clothing onto the body. They were unsure if the accuracy would be sufficient without this option.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Push Notifcations
The majority of users explained that they would prefer to receive emails rather then push notifications. They feel that it is a more controllable method to receive information from the app and less intrusive.
Multiple Photo Angles
Users want to upload multiple photos from various angles to improve AI's clothing mapping. They believe this will enhance the experience, aiding in better fitting and appearance assessment.
Shopping Habits
Most users shop online for ease and like sites with accurate sizing guides. Most users shopped from their phone had no issues with site interfaces.Typically users shopped online once every one to two months for clothes.
Key Takeaways From User Interviews (20 + People Interviewed By Our Team)
Application
Offering diverse brand clothing for try-on, using AI to virtually model clothes on user pictures. Operating solely as a try-on app, aiming for investor and Google app launch by August 2024.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Security & Privacy
Uploaded photos aren't stored on the device. Location data is only used for store localization, not shared otherwise.
Monetisation
The app relies heavily on Google Ads for advertising. Clients pay for visibility.
Research & Planning
Stakeholder & User Research Summary
Key Findings from the Stakeholder Interview
Competitor Analysis
U.S.P
Advantages
Disadvantages
Designer Clothes
Digital try on in realtime
Connected to some big brands like John Lewis and French Connection
Plug in options for enterprises
Privacy and security includes 2 way encryption
Accessories try on app
None discovered
Free
Iphone
On social media
Add sizes for shopping
Free
On social media
Good selection of brands
You can add your waist, bust, leg length etc
Free
Iphone, Android
On social media
Can add height and weight for accuracy
Share photos on social
Free
On social media
Shop on platform
Real time face photo
Free
On social media
Shop on platform
Can add sizes etc
Limited range of designer brands
Can not add sizes for try on
No mobile app
Purchase clothes on 3rd party platform
No outfit/photo storage / no account feature
Purchase clothes on 3rd party platform
They use some advertising
Web based try on/ use of mannequin
Just Prada accessories not clothes
Own brand only for clothing choices
Web based only
All apps are free to use
All on companies are on social media
Some give you the ability to add your measurements
Some send you to 3rd party platforms to make purchases
Key findings from Competitor Analysis
Research & Planning
Competitor Analysis
User Research
Conducted 8 Interviews which helped establish user painpoints & needs
Data Analysis
Helped with decision making to speed up process
Team In Mind
Organise and label my design system for ease of navigation and use
Helped Redefine Design Strategy
Challenged ideas with insights from user research.
End Results
With my team we put together a design strategy for brand positioning
Research & Planning
Impact and Value Added
Concept*
Solution
Researched T.I.O's target audience to grasp their needs. Analysed findings to identify audience, needs, opportunities, and pain points. Presented design strategy for brand positioning.
Problem
Startup with no brand presence exploring virtual try-on app market. Basic audience and design research done, but more needed to confirm audience. Insufficient evidence for app's alignment with user needs.
T.I.O. aims to dominate virtual try-on with its user-friendly mobile app, lifelike 2D representations from user photos, precise attire suggestions, and extensive clothing options from various stores.
We Conducted and Analysed
UX Research for a Virtual Try-On Experience App
Project Overview
Overview - Try It On (T.I.O London)
Project Timeline: January - March 2024
Tools Used: Figma
Roles: UX Researcher, UX & UI Designer
We constructed a number of user personas to reflect the apps target audience and show the kind of goals, frustrations needs and motivations that users may have.
Below are user stories for each of our personas. Each user story reflects on the personas lifestyle, what they need from the try on app and what needs to be implemented to meet their requirements
What went well
As a larger team we interviewed a large group of people giving us better results
We pinpointed key focus areas and identified others needing more research.
We built upon the Stakeholders' initial research, pinpointing the target audience and providing suggestions to broaden it across different age groups.
What could have gone better
Due to company being a startup we had little to work from. Had we had more idea about the companies values, tone etc we could have applied this to our research.
Next steps
Continue research Into target audience
Leverage unique brand attributes to differentiate from competitors and create a memorable brand identity.
Encourage customer feedback and community building
to create a loyal customer base and improve product offeringsStrengthen partnerships and collaborations to expand
brand visibility and tap into new markets
Conclusions
Next Steps
Red appears weak
Green appears weak
Colours appears weak
Colour Blindness Testing
It is important to remember that users may have visual impairments where they see colours in different ways. I ran colour blindness tests to identify how designs would look to people with red, green and monochromatic colour blindness
I chose colours that felt modern and thought would fit well with the brand but also were WCAG AA compliant. This takes into consideration people with accessible needs.
h
1
h
2
Button
1
Image
Link
1
Input
1
h
1
h
2
Button
1
Image
Link
1
Input
1
Text sizing for the app concept screens maintained a minimal pixel size of 16px to meet WCAG compliance.
Text Sizing
Concept: Even though a design had not been created, I wanted to add a little colour to my end process to demonstrate what the app could look like. I also tested the colours to make sure they met WCAG AA compliant.
Colour Contrast Testing
Concept
Accessibility
Concept
Accessibility
Tests Revealed
Extra postage costs when redirected to third-party sites for purchases
I Identified
Preferred end process
Tests Revealed
Necessity for an offline viewing version of the shopping list
I Identified
Areas for improvement
Tests Revealed
Extra postage costs when redirected to third-party sites for purchases
I Identified
I adjusted the layout placement, added extra info, and enhanced usability.
Key findings from Usability Testing
User Testing
User Testing - End Process
User Testing
User Testing - End Process
User research revealed focus areas for usability testing, notably the app's limitation to try-on experiences without in-app purchasing options. Two processes below were tested:
Research & Planning
Experience Mapping
Research & Planning
Experience Mapping
Privacy
Concerns about privacy and how the app uses data
Customisation
Opportunity to add the ability to input measurements
Experience
Hopes the app is intuitive and has a glitch free try- on experience
Personalised
User wants a wide range of clothes, specifically brands he likes
Monetise
Utilise to ability to monetise purchase links
Seemless Experience
Provide the ability to purchase products in app
Key findings from Experience Map
Below are user stories for each of our personas. Each user story reflects on the personas lifestyle, what they need from the try on app and what needs to be implemented to meet their requirements
Research & Planning
User Personas & User Stories
Research & Planning
User Personas & User Stories
Measurements
Users emphasized the importance of adding personal measurements like height, waist, and bust to improve the AI's accuracy in mapping clothing onto the body. They were unsure if the accuracy would be sufficient without this option.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Push Notifcations
The majority of users explained that they would prefer to receive emails rather then push notifications. They feel that it is a more controllable method to receive information from the app and less intrusive.
Multiple Photo Angles
Users want to upload multiple photos from various angles to improve AI's clothing mapping. They believe this will enhance the experience, aiding in better fitting and appearance assessment.
Shopping Habits
Most users shop online for ease and like sites with accurate sizing guides. Most users shopped from their phone had no issues with site interfaces.Typically users shopped online once every one to two months for clothes.
Measurements
Users emphasized the importance of adding personal measurements like height, waist, and bust to improve the AI's accuracy in mapping clothing onto the body. They were unsure if the accuracy would be sufficient without this option.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Push Notifcations
The majority of users explained that they would prefer to receive emails rather then push notifications. They feel that it is a more controllable method to receive information from the app and less intrusive.
Multiple Photo Angles
Users want to upload multiple photos from various angles to improve AI's clothing mapping. They believe this will enhance the experience, aiding in better fitting and appearance assessment.
Shopping Habits
Most users shop online for ease and like sites with accurate sizing guides. Most users shopped from their phone had no issues with site interfaces.Typically users shopped online once every one to two months for clothes.
Application
Offering diverse brand clothing for try-on, using AI to virtually model clothes on user pictures. Operating solely as a try-on app, aiming for investor and Google app launch by August 2024.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Security & Privacy
Uploaded photos aren't stored on the device. Location data is only used for store localization, not shared otherwise.
Monetisation
The app relies heavily on Google Ads for advertising. Clients pay for visibility.
Application
Offering diverse brand clothing for try-on, using AI to virtually model clothes on user pictures. Operating solely as a try-on app, aiming for investor and Google app launch by August 2024.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Security & Privacy
Uploaded photos aren't stored on the device. Location data is only used for store localization, not shared otherwise.
Monetisation
The app relies heavily on Google Ads for advertising. Clients pay for visibility.
Research & Planning
Stakeholder & User Research Summary
Research & Planning
Stakeholder & User Research Summary
Key Findings from the Stakeholder Interview
Key Takeaways From User Interviews (20 + People Interviewed By Our Team)
Competitor Analysis
U.S.P
Advantages
Disadvantages
Designer Clothes
Digital try on in realtime
Connected to some big brands like John Lewis and French Connection
Plug in options for enterprises
Privacy and security includes 2 way encryption
Accessories try on app
None discovered
Free
Iphone
On social media
Add sizes for shopping
Free
On social media
Good selection of brands
You can add your waist, bust, leg length etc
Free
Iphone, Android
On social media
Can add height and weight for accuracy
Share photos on social
Free
On social media
Shop on platform
Real time face photo
Free
On social media
Shop on platform
Can add sizes etc
Limited range of designer brands
Can not add sizes for try on
No mobile app
Purchase clothes on 3rd party platform
No outfit/photo storage / no account feature
Purchase clothes on 3rd party platform
They use some advertising
Web based try on/ use of mannequin
Just Prada accessories not clothes
Own brand only for clothing choices
Web based only
Competitor Analysis
U.S.P
Advantages
Disadvantages
Designer Clothes
Digital try on in realtime
Connected to some big brands like John Lewis and French Connection
Plug in options for enterprises
Privacy and security includes 2 way encryption
Accessories try on app
None discovered
Free
Iphone
On social media
Add sizes for shopping
Free
On social media
Good selection of brands
You can add your waist, bust, leg length etc
Free
Iphone, Android
On social media
Can add height and weight for accuracy
Share photos on social
Free
On social media
Shop on platform
Real time face photo
Free
On social media
Shop on platform
Can add sizes etc
Limited range of designer brands
Can not add sizes for try on
No mobile app
Purchase clothes on 3rd party platform
No outfit/photo storage / no account feature
Purchase clothes on 3rd party platform
They use some advertising
Web based try on/ use of mannequin
Just Prada accessories not clothes
Own brand only for clothing choices
Web based only
All apps are free to use
All on companies are on social media
Some give you the ability to add your measurements
Some send you to 3rd party platforms to make purchases
Key findings from Competitor Analysis
All apps are free to use
All on companies are on social media
Some give you the ability to add your measurements
Some send you to 3rd party platforms to make purchases
Key findings from Competitor Analysis
Research & Planning
Competitor Analysis
Research & Planning
Competitor Analysis
User Research
Conducted 8 Interviews which helped establish user painpoints & needs
Data Analysis
Helped with decision making to speed up process
Team In Mind
Organise and label my design system for ease of navigation and use
Helped Redefine Design Strategy
Challenged ideas with insights from user research.
End Results
With my team we put together a design strategy for brand positioning
User Research
Conducted 8 Interviews which helped establish user painpoints & needs
Data Analysis
Helped with decision making to speed up process
Team In Mind
Organise and label my design system for ease of navigation and use
Helped Redefine Design Strategy
Challenged ideas with insights from user research.
End Results
With my team we put together a design strategy for brand positioning
Research & Planning
Impact and Value Added
Research & Planning
Impact and Value Added
Concept*
Concept*
Solution
Researched T.I.O's target audience to grasp their needs. Analysed findings to identify audience, needs, opportunities, and pain points. Presented design strategy for brand positioning.
Solution
Researched T.I.O's target audience to grasp their needs. Analysed findings to identify audience, needs, opportunities, and pain points. Presented design strategy for brand positioning.
Problem
Startup with no brand presence exploring virtual try-on app market. Basic audience and design research done, but more needed to confirm audience. Insufficient evidence for app's alignment with user needs.
Problem
Startup with no brand presence exploring virtual try-on app market. Basic audience and design research done, but more needed to confirm audience. Insufficient evidence for app's alignment with user needs.
T.I.O. aims to dominate virtual try-on with its user-friendly mobile app, lifelike 2D representations from user photos, precise attire suggestions, and extensive clothing options from various stores.
T.I.O. aims to dominate virtual try-on with its user-friendly mobile app, lifelike 2D representations from user photos, precise attire suggestions, and extensive clothing options from various stores.
We Conducted and Analysed
UX Research for a Virtual Try-On Experience App
Project Overview
Overview - Try It On (T.I.O London)
Project Overview
Overview - Try It On (T.I.O London)
Project Timeline: January - March 2024
Tools Used: Figma
Roles: UX Researcher, UX & UI Designer
Project Timeline: January - March 2024
Tools Used: Figma
Roles: UX Researcher, UX & UI Designer
We constructed a number of user personas to reflect the apps target audience and show the kind of goals, frustrations needs and motivations that users may have.
I built upon previously added products in the saved list and used feedback to inform the transition to wireframing. I transformed sketches into Figma wireframes, refining designs and gathering feedback to improve usability. I also created high-fidelity versions to demonstrate what the final design could look like.
Paper Sketches, Low & High Fidelity Wireframes
© Robert Beeton 2024
Concept
Accessibility
Concept
Accessibility
Tests Revealed
Extra postage costs when redirected to third-party sites for purchases
I Identified
Preferred end process
Tests Revealed
Necessity for an offline viewing version of the shopping list
I Identified
Areas for improvement
Tests Revealed
Extra postage costs when redirected to third-party sites for purchases
I Identified
I adjusted the layout placement, added extra info, and enhanced usability.
Key findings from Usability Testing
We constructed a number of user personas to reflect the apps target audience and show the kind of goals, frustrations needs and motivations that users may have.
User Testing
User Testing - End Process
User Testing
User Testing - End Process
User research revealed focus areas for usability testing, notably the app's limitation to try-on experiences without in-app purchasing options. Two processes below were tested:
Research & Planning
Experience Mapping
Research & Planning
Experience Mapping
Privacy
Concerns about privacy and how the app uses data
Customisation
Opportunity to add the ability to input measurements
Experience
Hopes the app is intuitive and has a glitch free try- on experience
Personalised
User wants a wide range of clothes, specifically brands he likes
Monetise
Utilise to ability to monetise purchase links
Seemless Experience
Provide the ability to purchase products in app
Privacy
Concerns about privacy and how the app uses data
Customisation
Opportunity to add the ability to input measurements
Experience
Hopes the app is intuitive and has a glitch free try- on experience
Personalised
User wants a wide range of clothes, specifically brands he likes
Monetise
Utilise to ability to monetise purchase links
Seemless Experience
Provide the ability to purchase products in app
Key findings from Experience Map
Below are user stories for each of our personas. Each user story reflects on the personas lifestyle, what they need from the try on app and what needs to be implemented to meet their requirements
Research & Planning
User Personas & User Stories
Research & Planning
User Personas & User Stories
Measurements
Users emphasized the importance of adding personal measurements like height, waist, and bust to improve the AI's accuracy in mapping clothing onto the body. They were unsure if the accuracy would be sufficient without this option.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Push Notifcations
The majority of users explained that they would prefer to receive emails rather then push notifications. They feel that it is a more controllable method to receive information from the app and less intrusive.
Multiple Photo Angles
Users want to upload multiple photos from various angles to improve AI's clothing mapping. They believe this will enhance the experience, aiding in better fitting and appearance assessment.
Shopping Habits
Most users shop online for ease and like sites with accurate sizing guides. Most users shopped from their phone had no issues with site interfaces.Typically users shopped online once every one to two months for clothes.
Measurements
Users emphasized the importance of adding personal measurements like height, waist, and bust to improve the AI's accuracy in mapping clothing onto the body. They were unsure if the accuracy would be sufficient without this option.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Push Notifcations
The majority of users explained that they would prefer to receive emails rather then push notifications. They feel that it is a more controllable method to receive information from the app and less intrusive.
Multiple Photo Angles
Users want to upload multiple photos from various angles to improve AI's clothing mapping. They believe this will enhance the experience, aiding in better fitting and appearance assessment.
Shopping Habits
Most users shop online for ease and like sites with accurate sizing guides. Most users shopped from their phone had no issues with site interfaces.Typically users shopped online once every one to two months for clothes.
Application
Offering diverse brand clothing for try-on, using AI to virtually model clothes on user pictures. Operating solely as a try-on app, aiming for investor and Google app launch by August 2024.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Security & Privacy
Uploaded photos aren't stored on the device. Location data is only used for store localization, not shared otherwise.
Monetisation
The app relies heavily on Google Ads for advertising. Clients pay for visibility.
Application
Offering diverse brand clothing for try-on, using AI to virtually model clothes on user pictures. Operating solely as a try-on app, aiming for investor and Google app launch by August 2024.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Security & Privacy
Uploaded photos aren't stored on the device. Location data is only used for store localization, not shared otherwise.
Monetisation
The app relies heavily on Google Ads for advertising. Clients pay for visibility.
Key Findings from the Stakeholder Interview
Key Takeaways From User Interviews (20 + People Interviewed By Our Team)
Research & Planning
Competitor Analysis
Research & Planning
Competitor Analysis
Research & Planning
Impact and Value Added
Research & Planning
Impact and Value Added
Concept*
Concept*
T.I.O. aims to dominate virtual try-on with its user-friendly mobile app, lifelike 2D representations from user photos, precise attire suggestions, and extensive clothing options from various stores.
T.I.O. aims to dominate virtual try-on with its user-friendly mobile app, lifelike 2D representations from user photos, precise attire suggestions, and extensive clothing options from various stores.
Project Timeline: January - March 2024
Tools Used: Figma
Roles: UX Researcher, UX & UI Designer
Project Timeline: January - March 2024
Tools Used: Figma
Roles: UX Researcher, UX & UI Designer
Project Overview
Overview - Try It On
(T.I.O London)
Project Overview
Overview - Try It On
(T.I.O London)
Startup with no brand presence exploring virtual try-on app market. Basic audience and design research done, but more needed to confirm audience. Insufficient evidence for app's alignment with user needs.
Problem
Startup with no brand presence exploring virtual try-on app market. Basic audience and design research done, but more needed to confirm audience. Insufficient evidence for app's alignment with user needs.
Problem
Researched T.I.O's target audience to grasp their needs. Analysed findings to identify audience, needs, opportunities, and pain points. Presented design strategy for brand positioning.
Solution
Researched T.I.O's target audience to grasp their needs. Analysed findings to identify audience, needs, opportunities, and pain points. Presented design strategy for brand positioning.
Solution
We Conducted and Analysed UX Research for a Virtual Try-On Experience App
User Research
Conducted 8 Interviews which helped establish user painpoints & needs
Data Analysis
Helped with decision making to speed up process
Team In Mind
Organise and label my design system for ease of navigation and use
Helped Redefine Design Strategy
Challenged ideas with insights from user research.
End Results
With my team we put together a design strategy for brand positioning
User Research
Conducted 8 Interviews which helped establish user painpoints & needs
Data Analysis
Helped with decision making to speed up process
Team In Mind
Organise and label my design system for ease of navigation and use
Helped Redefine Design Strategy
Challenged ideas with insights from user research.
End Results
With my team we put together a design strategy for brand positioning
All apps are free to use
All on companies are on social media
Some give you the ability to add your measurements
Some send you to 3rd party platforms to make purchases
Key findings from Competitor Analysis
All apps are free to use
All on companies are on social media
Some give you the ability to add your measurements
Some send you to 3rd party platforms to make purchases
Key findings from Competitor Analysis
Research & Planning
Stakeholder & User Research Summary
Research & Planning
Stakeholder & User Research Summary
I built upon previously added products in the saved list and used feedback to inform the transition to wireframing. I transformed sketches into Figma wireframes, refining designs and gathering feedback to improve usability. I also created high-fidelity versions to demonstrate what the final design could look like.
Paper Sketches, Low & High Fidelity Wireframes
Concept: Even though a design had not been created, I wanted to add a little colour to my end process to demonstrate what the app could look like. I also tested the colours to make sure they met WCAG AA compliant.
Text sizing for the app concept screens maintained a minimal pixel size of 16px to meet WCAG compliance.
Text Sizing
Colour Contrast Testing
I chose colours that felt modern and thought would fit well with the brand but also were WCAG AA compliant. This takes into consideration people with accessible needs.
Red appears weak
Green appears weak
Colours appears weak
Colour Blindness Testing
It is important to remember that users may have visual impairments where they see colours in different ways. I ran colour blindness tests to identify how designs would look to people with red, green and monochromatic colour blindness
What went well
As a larger team we interviewed a large group of people giving us better results
We pinpointed key focus areas and identified others needing more research.
We built upon the Stakeholders' initial research, pinpointing the target audience and providing suggestions to broaden it across different age groups.
What could have gone better
Due to company being a startup we had little to work from. Had we had more idea about the companies values, tone etc we could have applied this to our research.
Next steps
Continue research Into target audience
Leverage unique brand attributes to differentiate from competitors and create a memorable brand identity.
Encourage customer feedback and community building
to create a loyal customer base and improve product offeringsStrengthen partnerships and collaborations to expand
brand visibility and tap into new markets
Measurements
Users emphasized the importance of adding personal measurements like height, waist, and bust to improve the AI's accuracy in mapping clothing onto the body. They were unsure if the accuracy would be sufficient without this option.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Push Notifcations
The majority of users explained that they would prefer to receive emails rather then push notifications. They feel that it is a more controllable method to receive information from the app and less intrusive.
Multiple Photo Angles
Users want to upload multiple photos from various angles to improve AI's clothing mapping. They believe this will enhance the experience, aiding in better fitting and appearance assessment.
Shopping Habits
Most users shop online for ease and like sites with accurate sizing guides. Most users shopped from their phone had no issues with site interfaces.Typically users shopped online once every one to two months for clothes.
Key Takeaways From User Interviews (20 + People Interviewed By Our Team)
Application
Offering diverse brand clothing for try-on, using AI to virtually model clothes on user pictures. Operating solely as a try-on app, aiming for investor and Google app launch by August 2024.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Security & Privacy
Uploaded photos aren't stored on the device. Location data is only used for store localization, not shared otherwise.
Monetisation
The app relies heavily on Google Ads for advertising. Clients pay for visibility.
Application
Offering diverse brand clothing for try-on, using AI to virtually model clothes on user pictures. Operating solely as a try-on app, aiming for investor and Google app launch by August 2024.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Security & Privacy
Uploaded photos aren't stored on the device. Location data is only used for store localization, not shared otherwise.
Monetisation
The app relies heavily on Google Ads for advertising. Clients pay for visibility.
User research revealed focus areas for usability testing, notably the app's limitation to try-on experiences without in-app purchasing options. Two processes below were tested:
Concept*
Concept*
Research & Planning
Impact and Value
Added
Research & Planning
Impact and Value
Added
Research & Planning
Competitor
Analysis
Research & Planning
Competitor
Analysis
Concept
Accessibility
Concept
Accessibility
Key findings from Usability Testing
Privacy
Concerns about privacy and how the app uses data
Customisation
Opportunity to add the ability to input measurements
Experience
Hopes the app is intuitive and has a glitch free try- on experience
Personalised
User wants a wide range of clothes, specifically brands he likes
Monetise
Utilise to ability to monetise purchase links
Seemless Experience
Provide the ability to purchase products in app
Privacy
Concerns about privacy and how the app uses data
Customisation
Opportunity to add the ability to input measurements
Experience
Hopes the app is intuitive and has a glitch free try- on experience
Personalised
User wants a wide range of clothes, specifically brands he likes
Monetise
Utilise to ability to monetise purchase links
Seemless Experience
Provide the ability to purchase products in app
Tests Revealed
Extra postage costs when redirected to third-party sites for purchases
I Identified
Preferred end process
Tests Revealed
Necessity for an offline viewing version of the shopping list
I Identified
Areas for improvement
Tests Revealed
Extra postage costs when redirected to third-party sites for purchases
I Identified
I adjusted the layout placement, added extra info, and enhanced usability.
Tests Revealed
Extra postage costs when redirected to third-party sites for purchases
I Identified
Preferred end process
Tests Revealed
Necessity for an offline viewing version of the shopping list
I Identified
Areas for improvement
Tests Revealed
Extra postage costs when redirected to third-party sites for purchases
I Identified
I adjusted the layout placement, added extra info, and enhanced usability.
User Testing
User Testing - End Process
Key findings from Experience Map
Research & Planning
Experience
Mapping
Below are user stories for each of our personas. Each user story reflects on the personas lifestyle, what they need from the try on app and what needs to be implemented to meet their requirements
We constructed a number of user personas to reflect the apps target audience and show the kind of goals, frustrations needs and motivations that users may have.
Research & Planning
User Personas &
User Stories
Measurements
Users emphasized the importance of adding personal measurements like height, waist, and bust to improve the AI's accuracy in mapping clothing onto the body. They were unsure if the accuracy would be sufficient without this option.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Push Notifcations
The majority of users explained that they would prefer to receive emails rather then push notifications. They feel that it is a more controllable method to receive information from the app and less intrusive.
Multiple Photo Angles
Users want to upload multiple photos from various angles to improve AI's clothing mapping. They believe this will enhance the experience, aiding in better fitting and appearance assessment.
Shopping Habits
Most users shop online for ease and like sites with accurate sizing guides. Most users shopped from their phone had no issues with site interfaces.Typically users shopped online once every one to two months for clothes.
Measurements
Users emphasized the importance of adding personal measurements like height, waist, and bust to improve the AI's accuracy in mapping clothing onto the body. They were unsure if the accuracy would be sufficient without this option.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Push Notifcations
The majority of users explained that they would prefer to receive emails rather then push notifications. They feel that it is a more controllable method to receive information from the app and less intrusive.
Multiple Photo Angles
Users want to upload multiple photos from various angles to improve AI's clothing mapping. They believe this will enhance the experience, aiding in better fitting and appearance assessment.
Shopping Habits
Most users shop online for ease and like sites with accurate sizing guides. Most users shopped from their phone had no issues with site interfaces.Typically users shopped online once every one to two months for clothes.
Application
Offering diverse brand clothing for try-on, using AI to virtually model clothes on user pictures. Operating solely as a try-on app, aiming for investor and Google app launch by August 2024.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Security & Privacy
Uploaded photos aren't stored on the device. Location data is only used for store localization, not shared otherwise.
Monetisation
The app relies heavily on Google Ads for advertising. Clients pay for visibility.
Application
Offering diverse brand clothing for try-on, using AI to virtually model clothes on user pictures. Operating solely as a try-on app, aiming for investor and Google app launch by August 2024.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Target Audeince
The target age is approximately 25-35, open to all genders but with a focus on female shoppers. Initially UK-based, with plans for later expansion to the US.
Security & Privacy
Uploaded photos aren't stored on the device. Location data is only used for store localization, not shared otherwise.
Monetisation
The app relies heavily on Google Ads for advertising. Clients pay for visibility.
Team In Mind
Organise and label my design system for ease of navigation and use
End Results
With my team we put together a design strategy for brand positioning
Helped Redefine Design Strategy
Challenged ideas with insights from user research.
User Research
Conducted 8 Interviews which helped establish user painpoints & needs
Data Analysis
Helped with decision making to speed up process
Team In Mind
Organise and label my design system for ease of navigation and use
End Results
With my team we put together a design strategy for brand positioning
Helped Redefine Design Strategy
Challenged ideas with insights from user research.
User Research
Conducted 8 Interviews which helped establish user painpoints & needs
Data Analysis
Helped with decision making to speed up process
Key Findings from the Stakeholder Interview
Key Takeaways From User Interviews (20 + People Interviewed By Our Team)
Researched T.I.O's target audience to grasp their needs. Analysed findings to identify audience, needs, opportunities, and pain points. Presented design strategy for brand positioning.
Solution
Researched T.I.O's target audience to grasp their needs. Analysed findings to identify audience, needs, opportunities, and pain points. Presented design strategy for brand positioning.
Solution
Startup with no brand presence exploring virtual try-on app market. Basic audience and design research done, but more needed to confirm audience. Insufficient evidence for app's alignment with user needs.
Problem
Project Overview
Overview - Try It On
(T.I.O London)
Project Overview
Overview - Try It On
(T.I.O London)
T.I.O. aims to dominate virtual try-on with its user-friendly mobile app, lifelike 2D representations from user photos, precise attire suggestions, and extensive clothing options from various stores.
T.I.O. aims to dominate virtual try-on with its user-friendly mobile app, lifelike 2D representations from user photos, precise attire suggestions, and extensive clothing options from various stores.
Project Timeline: January - March 2024
Tools Used: Figma
Roles: UX Researcher, UX & UI Designer
Project Timeline: January - March 2024
Tools Used: Figma
Roles: UX Researcher, UX & UI Designer
We Conducted and Analysed
UX Research for a Virtual Try-On Experience App
All apps are free to use
All on companies are on social media
Some give you the ability to add your measurements
Some send you to 3rd party platforms to make purchases
Key findings from Competitor Analysis
All apps are free to use
All on companies are on social media
Some give you the ability to add your measurements
Some send you to 3rd party platforms to make purchases
Key findings from Competitor Analysis
Research & Planning
Stakeholder & User Research Summary
Research & Planning
Stakeholder & User Research Summary
I built upon previously added products in the saved list and used feedback to inform the transition to wireframing. I transformed sketches into Figma wireframes, refining designs and gathering feedback to improve usability. I also created high-fidelity versions to demonstrate what the final design could look like.
Paper Sketches, Low & High Fidelity Wireframes
I chose colours that felt modern and thought would fit well with the brand but also were WCAG AA compliant. This takes into consideration people with accessible needs.
Text sizing for the app concept screens maintained a minimal pixel size of 16px to meet WCAG compliance.
Text Sizing
Concept: Even though a design had not been created, I wanted to add a little colour to my end process to demonstrate what the app could look like. I also tested the colours to make sure they met WCAG AA compliant.
Colour Contrast Testing
Red appears weak
Green appears weak
Colours appears weak
Colour Blindness Testing
It is important to remember that users may have visual impairments where they see colours in different ways. I ran colour blindness tests to identify how designs would look to people with red, green and monochromatic colour blindness
Conclusions
Next Steps
What went well
As a larger team we interviewed a large group of people giving us better results
We pinpointed key focus areas and identified others needing more research.
We built upon the Stakeholders' initial research, pinpointing the target audience and providing suggestions to broaden it across different age groups.
What could have gone better
Due to company being a startup we had little to work from. Had we had more idea about the companies values, tone etc we could have applied this to our research.
Next steps
Continue research Into target audience
Leverage unique brand attributes to differentiate from competitors and create a memorable brand identity.
Encourage customer feedback and community building
to create a loyal customer base and improve product offeringsStrengthen partnerships and collaborations to expand
brand visibility and tap into new markets