Object recognition might be one of hottest sector of computer vision but one company decided that it can wait to be solved. Instead of a battery of computers trying to figure out what is in the picture you just took, it is a battery of human beings that powers Fetch. The goal ? Making your mobile shopping experience as easy as having your own personal 24/7/365 assistant. Here’s their intro video :
We sat down with founder and ceo Tom Hadfield so he could tell us more:
In a few words, what is Fetch?
Fetch is a personal buying assistant that aims to make buying easy on your phone. Just let Fetch know what you want to buy – by sending a text or photo – and your personal buying assistant will find the best price available online, check for coupon codes, and place the order for you. Our goal is to make mobile commerce as easy as describing the product you want to buy.
What made you decide to create it ?
2014 is the first year we’ll spend more time on our mobile devices than our desktops, and yet mobile commerce accounts for only 10% of all dollars spent online. Why? Because buying on your phone is a pain. It takes 16 clicks and at least four minutes to fill out your billing address, your shipping address, your card number, your security code, your expiry date, etc – let alone doing price comparison and checking for coupons – all on a tiny screen. It doesn’t need to be this hard.
What’s wrong with computer image recognition ? People make mistakes too.
I’ve never met anyone who would trust Siri – or Amazon Firefly – to make an online purchase for them. With Fetch, you can take a photo of a pair of shoes, and one of our buying assistants will track down that exact pair, find the best price, present you with color options and – if you approve the price – will order them for you. We use image recognition technology to help improve the efficiency of our buying team, but we use human judgment to make sure we find exactly what you’re looking for every time.
Human powered image recognition. Is that scalable ?
The unit economics are very attractive. We get a commission from the retailer, and we share some of the proceeds with the buying assistant which enables us to keep the service free to use.
Can you tell us how it is funded ? How big is the team currently?
Fetch raised $2.3 million in spring 2014 from seed investors including Kapor Capital, Black Green Capital, Tamarisc, Cane Investments, Beechwood Capital, Thatchstone, Ryerson Futures, Tom Rutledge, RP Eddy, Michael Foster and Dariush Maanavi. We have currently trained 44 buying assistants and we’re adding 20 more this month.
What do you think is the number one appeal for people to use Fetch?
Fetch makes buying easy. It’s that simple.
Who do you see as your typical user ?
Fetch users tend to be busy online shoppers who don’t have time or patience to search for the best prices and check for coupon codes. They know what they want to buy, and they just want to get it done.
What are some upcoming features that we can expect to see in the near future ?
Look out for the Fetch app on the Apple Watch in early 2015!
Fetch is available for iOS with an Android version in the works.
Photo by Funky64 (www.lucarossato.com)
Author: Paul Melcher
Paul Melcher is the founder of Kaptur and Managing Director of Melcher System, a consultancy for visual technology firms. He is an entrepreneur, advisor, and consultant with a rich background in visual tech, content licensing, business strategy, and technology with more than 20 years experience in developing world-renowned photo-based companies with already two successful exits.