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Dresspicker

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Dresspicker

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Dresspicker is an augmented reality featured native apps prototype designed for teenagers. It's an online favorite virtual closet for teenagers who want to save their time but also shop for stylish dresses like their peers.

Dresspicker looks easy, appealing, and fresh. 

If all my friends are wearing black and I’m wearing black and white, it’s like I don’t fit in with them, so I don’t feel right. I'd want to go home and change so I can feel like part of the group.

TARGET AND CHALLENGE

Before developing Dresspicker, I read interesting articles about teenagers' fashion culture by Stephanie Newman Ph.D.

I discovered that by dressing the same way, speaking the same way, and adopting their friends’ mannerisms, teenagers are actually expressing something complicated about their own developing self-esteem.

I went a step further in my study by researching teenagers in the 12-18 age range. 

When I discovered is that there are similarities, but these similarities are expressed in different styles.

Therefore, Dresspicker needed to be easily understandable by teens without any specific knowledge regarding brands or reputation, and that's exactly what we have here. 

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The Hypothesis

We believe that by creating a function that allows teenagers to virtually try customized clothes on for Teenagers, we will be able to offer them the best fit.

The Problem

Teenagers need a way to virtual closet and try on before they buy, because they would like to save time and money, they shop around and get optimized stylish clothing because each individual is unique. Teenagers are not only interested in how many clothes they have, but also how much of it reflects their taste. This gives them confidence in their daily life. They truly want to get "nice and well-suited" clothing.

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The Solution

Teenagers need a way to get an organized selection of clothing lines and customized recommendations because it will save their time and money. I will create an advanced search feature for teenagers' preference for fashion style.​

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The Hypothesis

Augmented Reality Closet gives teenagers the opportunity to try clothes from their favorite brand and search for offline try-on stores. It gives details, mood board and optimized size specs with a color chart.

We will know this to be true when we see higher conversion rates. The company can make a great deal from the targeted valuable customer. 

COMPETITIVE ANALYSIS

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Designing for Easy Navigation

  • Ensuring the right links are on the page.

  • Making those links clearly noticeable and identifiable.

  • Removing clutter so a user can clearly move to the next step of their journey.

  • Using the right labels.

  • Using sidebars and site menus to help users move forward, backward, and out of a predicted user flow.

Mid-Fidelity

Applications can access functions including GPS, push notifications, virtual camera, offline access, Q&A messaging, and background downloading of data.
Once a user has installed your app on a mobile device, it stays there, showing up with its unique icon on the home screen.
You can take a photo of your clothing and we will offer you items similar to it. 
Dresspicker matches the best brands and design for your custom taste using Augmented Reality Closet.
We can even give you the GPS location of try-on stores near you. 
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Meanwhile, users can set up the app and fine-tune the preferences in terms of brand, size, coloration, and detail when they sign-in.
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Clothing brands that teens are obsessed with.
(Business Insider, Piper Jaffray surveyed 8,600 teens on Oct 18th, 2018.)
College Friends
which fashion brands dominated the marke

MDP Usability Testing

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Outcomes and Achievements

The UX study, basic branding, and prototype were released. Thanks to the general users, we were able to validate the UX flows every release cycle with lots of feedback. Built to validate a customer idea and feedback, the prototype eventually helped teenagers shop effectively and style themselves successfully while saving time.

USER PERSONA

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Menu Bar

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The menu bar empathizes with the teenager user by showing their favorite brand at the first menu bar through their virtual options.

It is also important for company sales to understand their target market and not waste their time and money on the wrong audience. 

Most of the time, users aren’t navigating through menus and category pages to find what they want. They’re going directly to search, even if they only have a vague idea of what they’re interested in.

Behind effective search, breadcrumbs, and recommendation algorithms is typically content that contains a good deal of behind-the-scenes metadata. This gives weight to aspects of the content that may not be captured in titles and keywords.

Optimized Filter/Options

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Every teenager user has a different budget, color preference, and size. You don't need to spend your time with an out-of-stock item.
 So, augmented reality camera can optimize the teenagers' personal budget, color, size, occasion type, dress style, etc by showing filters or favorite brands in the menu section. 
Our app algorithm will calculate your favorite clothing line and then suggest several styles just for you.

Augmented Reality Closet

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Augmented Reality Closet tries to focus on your interest, size, design, color, and the details

that you are the most interested in.

You may be setting up for your true size and you will see the perfectly optimized size and real customer reviews based on your true size, you have an array of options to choose and you can also save time and money.

Order History

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Once you have selected your items, you can confirm by using your shopping card and billing details. 

You can even use your promo code for discount.

You can optimize brands that you would like to connect with.

Clothing and accessories companies can get true conversion rate from the real customers.

Shipping Success

Once you go through the payment process and you pay for a product, you will receive a confirmation email and a "thank you" pop-up notification.

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THE NEXT BIG THING

Usability testing, building on more features, collaborating with retail companies, setting up with fashion knowledge for teenagers, connecting with blogs, bloggers, and fashionistas, social media networking, launching a new clothing line, and in-app events are some of the next big things to be done.

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Planing digital marketing strategies to collaborate with apparel and clothing companies.

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Finding a better search algorithm and targeting market is crucial for both companies and customers. Dresspicker is curious about you.

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Data analytics for customer preference algorithm and developing an e-commerce platform

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We are a user-centered platform focused on finding the right market for users.

Research and survey would be developed day by day for better service.

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Planning for multiple events and updates for each of every brand social networking and parties inside of an application.

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Code it out for the next stage. Fix bugs and errors and keep updates.

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Cloud-based E-commerce data.

Dresspicker handles everything from marketing and payments, to secure checkout and shipping in front of your door.

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There is nothing more important than you feeling safe and comfortable with our e-commerce platform.

Dresspicker keeps on eye on online safety.

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Connect with social communities around your area and get prompt updates from launching shows and new arrival items.

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Offering try-on clothing and advice on teenage fashion through offline and online services can socially engage the target users.

THE FINAL PROTOTYPE

A final application with augmented reality featured prototype was developed. 

These are totally new features in e-commerce/ retail area to collaborate with multiple markets. 

We had to keep updating several features and hold back from releasing the app. We still need time because we have a long way to go. I will give updates every single feature in this case study.

We also need to collaborate with apparel and fashion retailers, e-commerce corporations, magazine editors, bloggers, and some other street brands. 

Would you like me to share a little bit more of my ideas with you?

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Next Project​​

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