OVERVIEW

Amazon Visual Fashion Finder

2015

A new way for customers to shop visually for fashion on Amazon, also known as "Amazon Willow". My approach was focused on visual filtering, visual search and applied machine learning. Customers can use visual cues and photos instead of words to describe what they are looking for. Like a personal shopper: find it on Amazon by describing it visually.

willow

Goal: Solve for a complex problem in my 12 week internship: Irrelevant Search Results, by providing comprehensive tools for filtering by the visual aspects of a product, including a friendly interface that makes shopping for clothes on Amazon more fun and creative.

Users: All Amazon users

Why: Customers often find it hard to describe what they are looking for when it comes to fashion, but have an idea of what they personally like and don't like based on features of a product such as sleeve type, neckline etc. Many of the most important aspects for shopping for garments and accessories including cut, material, and pattern cannot be specified through filters, leaving customers to scroll endlessly and feel frustrated by overwhelming and irrelevant search results. Also, customers who have a starting point want to be able to discover the products they see in photos so they can purchase it themselves. There is no way to know what something is or find something similar via a photo.

Role: Designer paired with other interns, an Android developer and PM, UX/UI design, prototyping, product strategy

Process: Taking inspiration from my concept brief, my plan was to create a mobile experience that is: 1) A convenient and efficient solution for customers to, "Shopby" rather than "Shopfor," 2) Scalable, reliable, a long-term solution that reduces customer effort, 3) Fun, creative, interactive, innovative, unique; game-like and 4) In line with the Amazon brand and its best practices.

Outcome: A full time designer on the Amazon Fashion Team picked up where I left off and Dress Finder was launched a year later based on my concepts. There are also new patterns being developed by the Search Experience Team today, based on my concepts. When I returned to Amazon as a full-time designer, I was able to see through solving the second problem, search via a photo, with Amazon StyleSnap which launched 4 years later. 

PROCESS

Vision Storyboard Video

I wanted to bring the customer into the room when presenting concepts, so I filmed various use cases and scanarios in which I thought best represented the user, from engaging in social shopping with a partner or friend to seeing something in the "wild" or in a store window that sparked their inspiration.

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North Star Prototypes

1. Visual Search

Shop using a photo

2.  Results Feed

View results on Amazon

3. Recommendations

4. Filtering

5. Interaction/Navigation

Selected Works

Amazon StyleSnap #Software #VisualSearchUpload photos or screenshots to find visually similar styles on Amazon #VisualSearch #Mobile

Amazon Camera Modality #Software #ARBiggest redesign of Visual Search technology across Amazon #Mobile #AR #Camera

Amazon Package X-Ray #Software #ARSee which of your packages holds which gift, without opening them #Mobile #AR #Camera

Amazon Publisher Services #Desktop #AdsNew suite of cloud services, built to monetize and grow your media business #Desktop #Advertising

Amazon Visual Fashion Finder #Software #AIFilter the most important aspects when shopping for garments #Mobile #Internship #Fashion #AI

Photography #ArtDirection #PrintCollection of photographed International Editorials #Print #Digital #Identity #Photography

        © Andrea Alam 2019