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The best app to organise your clothes

OVERVIEW

OVERVIEW

This project addresses a common issue many people face: the challenge of organising and effectively use of their wardrobes. M!Closet not only aims to streamline the getting-ready process but also to empower users to maximize their wardrobe's potential while saving time and enhancing their style.

This project addresses a common issue many people face: the challenge of organising and effectively use of their wardrobes. M!Closet not only aims to streamline the getting-ready process but also to empower users to maximize their wardrobe's potential while saving time and enhancing their style.

The best app to organize your clothes

  1. HOW I GET HERE?

  1. HOW I GET HERE?

One busy morning, I found myself staring at my overflowing wardrobe, feeling frustrated and overwhelmed. I had a meeting to attend and wanted to look my best, but after try countless options, I felt like I had nothing to wear. In a rush, I grabbed an outfit that didn’t quite match my mood and I didn't feel comfortable at all that day.

This experience made me realise how much time and stress choosing an outfit could cause. I thought about how many others must feel the same way—standing in front of their closets, unsure of what to wear, and wasting precious time. I envisioned this app that could help organise clothes, suggest outfits, and ultimately boost confidence.

  1. LET'S DO THE RESEARCH

  1. LET'S DO THE RESEARCH

Some important data points that I found and the results of an online survey done by 48 people:

  1. Time Spent Choosing Outfits: A survey by Marks & Spencer revealed that women spend an average of 17 minutes daily deciding what to wear, while men take about 13 minutes. This highlights the potential for an app that streamlines outfit selection.

  1. Impact of Clothing on Mood: Research from the Journal of Experimental Social Psychology found that wearing formal clothing can enhance cognitive flexibility and abstract thinking. This suggests that feeling good in what you wear can positively affect performance and confidence, reinforcing the app's value in helping users choose outfits that boost their mood.

  1. Consumer Trends: A report from Statista indicated that the global online clothing rental market is projected to grow significantly, suggesting that consumers are increasingly looking for innovative ways to manage and curate their wardrobes.

  1. Wardrobe Management Apps: According to a survey by App Annie, fashion and clothing apps have seen increased engagement, with users spending more time on apps that help them organize and style their clothing, indicating a demand for such solutions.

  1. Sustainability Awareness: A study by McKinsey found that 67% of consumers consider the use of sustainable materials important when making clothing purchases. An app that helps users maximize their wardrobe can promote sustainable fashion practices by reducing unnecessary buying.

I also interviewed 8 people, their needs are reflected on the following comment:

Then I researched the competition. The app's that were similar had a very unintuitive design, they were outdated, or had dark patterns.

Then I researched the competition. The app's that were similar had a very unintuitive design, they were outdated, or had dark patterns.

  1. WHAT PROBLEM DO I NEED TO FOCUS ON?

  1. WHAT PROBLEM DO I NEED TO FOCUS ON?

I conducted a benchmark with over 30 functionalities that my app could have. This, along with the negative reviews of the competition gave me many ideas. After several rough sketches, I decided to address the following problems represented in my user persona:

Becky wants to:

1. Be more organized, know what she has in her wardrobe, and avoid buying clothes she doesn't need.

2. Save time when getting ready to go out.

  1. Make the most of her clothing and combine them effectively.

Becky wants to:

1. Be more organized, know what she has in her wardrobe, and avoid buying clothes she doesn't need.

2. Save time when getting ready to go out.

  1. Make the most of her clothing and combine them effectively.

Becky wants to:

1. Be more organized, know what she has in her wardrobe, and avoid buying clothes she doesn't need.

2. Save time when getting ready to go out.

  1. Make the most of her clothing and combine them effectively.

  1. THE SOLUTION? LEAN METHODOLOGIES

  1. THE SOLUTION? LEAN METHODOLOGIES

To address my user persona problems, the final prototype needed to have the following functionalities:

  1. Organise and maintain an inventory of her clothes.

  2. Create looks with her items and customise them in a calendar, including the time and event for which she plans to wear them.

  3. Receive outfit suggestions based on the items she owns.

I then created several prototypes that were tested by 20 users:

  1. The low-fidelity prototype for quick testing of the basic element placement.

  2. The medium-fidelity prototype with recognisable patterns to determine if it is intuitive enough for users aged 12 to 55.

Testing led me to the final high-fidelity prototype, which I will explain by accompanying Becky in three different situations:

HIGH FIDELITY

Case 1

HIGH FIDELITY

HIGH FIDELITY

CASE 1

Case 1

On boarding and Sign up

ON BOARDING & SIGN UP

Becky complains to her friend that her wardrobe is full of clothes, but she feels like she has nothing to wear or has very similar items. Her friend recommends M!Closet, and she downloads it.

Upon opening the app, she encounters a simple onboarding process that introduces the main features. We ask for her name to personalize her experience and to engage with her more. She selects her usual style when dressing and arrives at the home screen.

Case 2

CASE 2

Categorization

CATEGORIZATION

Becky from the Homepage touch the screen and immediately the app show her a short tutorial on how to add her clothes to the app.

Next, she adds an image of one of her garments from her gallery, edits it to remove the background, and categorise it filling up filters such as type of garment, colour, and brand…

She saves it in the Closet > Clothing > Blouses.

Case 3

CASE 3

Using filters

USING FILTERS

This time, Becky is standing in line to pay for a green dress on sales at Zara. There are a lot of people and she opens M!Closet to check if she already has a similar one and if the purchase is necessary. On the app, we see her logging into her account, where the homepage shows the look she created for an event she has that same day.

Then, we see her in the Closet section, where she has three options: view her clothes, her looks, or chat with an AI stylist. She clicks on "Clothing" and filters to see which green dresses she has. She realises she has plenty of them and doesn’t need another one. She decides to save time by focusing on getting ready for the event later that afternoon, and she’s also saved some money.

Case 4

CASE 4

Calendar. Outfit Planner.

CALENDAR. OUTFIT PLANNER

Becky is on the bus and gets bored, so she grabs her phone to see what she’s going to wear the next day. Suddenly, she remembers that she has plans to meet a friend, so she goes to Calendar > October 8th and creates a look with her new dress and favourite sandals. Once added, she can make them larger, rotate them, or overlap them. She also personalizes the look of the day writing the name of the event "Breakfast with Emily" and set up the time 10:00.

  1. NEXT STEPS

  1. NEXT STEPS

1

AI Clothing Recognition

Use AI to automatically recognise and categorise clothes from user-uploaded photos, making it easier to add items to the wardrobe.

  1. AI Clothing Recognition

Use AI to automatically recognize and categorize clothes from user-uploaded photos, making it easier to add items to the wardrobe.

2

Virtual Stylist

Include a virtual stylist powered by AI to suggest outfit combinations, fit adjustments, and style tips based on the user's preferences.

  1. Virtual Stylist

Include a virtual stylist powered by AI to suggest outfit combinations, fit adjustments, and style tips based on the user's preferences.

3

Automated Outfit Suggestions

Suggest outfits based on the weather, season, or upcoming events. The app can recommend combinations using the user's existing clothes.

  1. Automated Outfit Suggestions

Suggest outfits based on the weather, season, or upcoming events. The app can recommend combinations using the user's existing clothes.

4

Integration with Online Stores

Link the app to online stores so users can save items they want to buy and be alerted to sales or new collections.

  1. Integration with Online Stores

Link the app to online stores so users can save items they want to buy and be alerted to sales or new collections.

5

Wardrobe Analytics

Provide insights into the most and least worn items in the wardrobe, helping users declutter and optimize their collection.

  1. Wardrobe Analytics

Provide insights into the most and least worn items in the wardrobe, helping users declutter and optimize their collection.

6

Collaboration with Influencers or Brands

Partner with fashion influencers or brands to create curated looks and exclusive collections, encouraging users to try new styles.

  1. Collaboration with Influencers or Brands

Partner with fashion influencers or brands to create curated looks and exclusive collections, encouraging users to try new styles.