WhatAreThose!? LLC

The WhatAreThose!? app is the ultimate discovery app for sneakers! (The Shazam + Pinterest for Sneakers!)

Simply take a picture of a pair of sneakers, and our app will you give the name and best places to buy them from!


Problem
------------------------------------------------------------------------

Sneakerheads can have difficulty being updated on the latest trends and releases of sneakers due to the market's growth and the increasing frequency of releases. Currently, there are on average 20 sneaker drops/per month.

It's quite common for a sneakerhead to experience a "WhatAreThose!?" moment, where he/she doesn't know the shoe's name, and it can be challenging to find the exact name + best places to find that particular shoe. Consumers typically have to input the colors of the shoe on a search page, and the search to purchase the shoe itself can take at least 10 minutes.

Because of this problem, businesses can miss opportunities for potential transactions and customers.

Sneakers can miss out on being a part of consumer trends, which can help their brands or resellers.

We have built a functional app that would take less than 15 seconds to accurately recognize sneakers

We are also aiming for our app to be 80 - 99% accurate in recognizing sneakers in less than 5 seconds.

We also plan on utilizing ML Models to display a newsfeed of sneakers from classics to the latest releases tailored to our user's styles and preferences.

Team
 ------------------------------------------------------------------------

Our team aims to solve this problem by building a sneaker recognition/discovery app similar to Pinterest and Shazam, that will keep sneaker lovers updated on the latest releases that would most likely interest them using various ML Models.

Our team currently consists of Soumya Pattanayak , a current SDE @Amazon Music, who is the CEO, and Frontend/ML Engineer of the app; and Sean Brown who is the CTO and a Security Engineer @Cruise, who is the infrastructure and cloud engineer of the app.

Solution
 ------------------------------------------------------------------------

We aim to build a functional app that would take less than 5 seconds to  recognize sneakers, and  80 - 99% accurate in recognizing sneakers

We also plan to utilize ML Models to display a newsfeed of sneakers from classics to the latest releases tailored to our user's styles and preferences.

Here is a live demo of what we have built so far

Business Model
------------------------------------------------------------------------

Our Business Model has many channels:

Affiliate Marketing

When users find and purchase the shoe they're looking for from our app,  we will get a percentage/commission of the sales from the vendor, as we've marketed their information through our app.

Many Sneakerheads tend to have a preference for a certain brand of shoe.  Our app will provide ads targeted for those specific shoes based on the preference of the user.

We're collecting valuable data for footwear companies such as data on trends in the footwear industry. This data can be sold to retailers and manufacturers in order to help them make market predictions and find customer trends/patterns.

Market Size
------------------------------------------------------------------------

There are about 35M sneakerheads in the world just by judging from the sum of followers on sneakerhead pages such as goat, StockX, hypebeast, highsnobiety, yeezymafia etc...

A sneakerhead spends about $400 on average on sneakers per month.

This would mean $170B is estimated to be made annually from selling exclusive sneakers.

Assuming our main source of income is affiliate marketing, and if we were to take on average a 10% affiliate cut, servicing just 0.06% of sneakerheads (21K MAU) can help us achieve $100M annually, making us a billion dollar business in 10 years.

The Footwear market is still growing at 5% annually, while its resale market is growing at a rate of 17.5%. There are already up to 40 sneaker releases/month, 17 times more than 12 years ago, so this frequency is still projected to grow, making our problem more significant in the future.

What We Need
------------------------------------------------------------------------

$500k - This is for hiring engineers, cloud services, and a full-time salary to get this app, with PMF, to market!

Mentorship - to point us in the right direction throughout our journey to PMF

With this money, we’ll hit all the milestones for our next round within the next year