Social e-commerce platform for clothing and accessories based on visual search technology
Users find products by taking or uploading a photo from device, social network or Internet
Wide variety of price point categories and brands
AI Personalized recommendations
Apps are in the store with soft launch of about 1000 users.
Our user is the Females and Males from 20 to 50 years old.
eCommerce "Fashion" Revenue 2018
eCommerce "Fashion" Revenue 2022
Revenue CAGR 2018-2022
"Clothing” segment Revenue 2018
"Clothing" segment ARPU* 2018
E-commerce user penetration rate 2018
E-commerce user penetration rate 2022
Problem or Opportunity
Fashion industry needs to “go tech” to address tech-savvy millennials and Generation Z who have short attention span and use visual search the most.
Users want to find their look and purchase it instantly when they see it on someone else.
Solution (product or service)
We solve those problems by connecting retail and customer using visual search
Look App solution:
Enables users to shop screenshots and other images from their devices by identifying elements of clothing in photos and offering visually similar products (visual search)
Large database of products from leading online stores in different price categories
AI-powered personalized recommendations
Social interaction through creating and sharing looks
Screenshop - powered by syte.ai technology (supported by Kim Kardashian)
Comb - powered by ViSenze technology
Craves - powered by Slyce Visual Search
Retailers introduced Visual search into their apps:
H&M, ASOS, Ebay, Lamoda, Clouty, Spree
ViSenze (H&M, ASOS, Comb), Wide Eyes (Lamoda)
Advantages or differentiators
We use segmentation together with visual search and immediately provide user with shopping options.
On average, 5% commission from sales
Global base of 3 million active buying users
Projected revenue (2022):
3 mln * $269 * 0.05 = $40.35 mln
Operating expenses/R&D = $4 mln
Marketing costs = $15 mln