VeryClothe is a US based fashion retail startup aiming to deliver effective and disruptive solutions in the brick-and-mortar retail model and helping retail business to survive the digital competition getting tougher every day. After being in stealth mode for a while, developing their product, VeryClothe launched its beta version at TechCrunch Disrupt in Berlin at the end of November.
We managed to interview Ms. Galina Charni, CEO and co-founder of VeryClothe. Galina is the ex-chief stylist of a TV Shopping Chanel with over than 10 years of retail experience, who studied at the New York Fashion Institute of Technology and Hebrew University of Jerusalem. Veryclothe has started to collect and analyze location specific anonymized data on shopping patterns and customer behavior. This unique data processed by machine learning algorithms will give insights into users’ needs. Shared with small retail businesses it can make their merchandising decisions much more efficient, blending their intuition with location-based analytics. Smart offline shopping allows VeryClothe to build close relations with local retailers, with the main goal to create an organic “city-as-a-warehouse” infrastructure and implement more marketing leverage tools in a more sustainable retail environment.
When and why did you decide to found Veryclothe? What did your founders bring to the new company from former experiences and backgrounds?
VeryClothe was founded in the end of 2017 in Berlin by Djois Franklin, a former Microsoft veteran for mobile and touch devices and Galina Charni, a fashion management professional with over 10 years of experience in personal shopping and retail sales. Observing his wife’s and daughters’ shopping behavior Djois started researching solutions for retail market that can make shopping offline as easy as online. He was introduced to Galina Charni by a mutual friend in Berlin. Her experience confirmed that it is challenging to find relevant shops and items as well as update one’s wardrobe regularly. The idea of the solution for both shoppers and traditional retailers came from the fact that in spite of e-commerce skyrocketing, traditional retail still remains the main channel of apparel and accessories sales. However, the main problem traditional retailers face is getting foot traffic; this is especially challenging for independent boutiques due to a limited online presence.
The second problem of the fashion industry is that the life cycle of clothes is becoming shorter. Every fifth garment is either never used or used only a couple of times. High volume consumption increases the environmental impact from the production, transportation and disposal phases.
Between two of us we have both technological and retail backgrounds, and we are sure we can make offline shopping as convenient as online rather than taking an easy path by connecting e-commerce solutions. We believe in creating an organic rental infrastructure that will reduce apparel waste and the environmental impact from apparel disposal.
How did you manage your funding early stage?
We are still bootstrapping. We are trying to raise pre-seed right now, but in the current situation it is extremely difficult, so we are prepared to bootstrap for a bit longer to make our solution go to market.
What’s different in Veryclothe? How can you provide effective support to offline and online retailers through your machine learned based solutions?
What is really exciting about VeryClothe is that it will change the way people shop offline. Another exciting thing is that we will accumulate big data on shoppers and shopping patterns, which will be location specific. By applying machine learning we will be able to plan rental stock, help retailers make merchandizing decisions and anticipate shoppers’ needs. This is especially important to independent retailers who can not afford pricey market trend reports and tools for deep market research. Solutions currently available on the market are still too expensive for small chains and individual shop owners. We will gather unique data, and use machine learning algorithms to analyse shopping behaviour.
Can you share with us a success story or case history?
Now there is no unified location-based source of information on offline retail. It is challenging and time consuming to find a specific shop that will carry a certain item that you will like in your size and within your price range as well as to discover unique fashion. We will create a personalized machine learning based feed of products available offline, and in the future make latest trends and original designer fashion a part of people’s lives at a low cost. The whole neighbourhood or city will become one store.
We have already profiled thousands of shops in Europe, UK, US and Israel. After our pilot in Berlin we will be able to launch our app in major cities all over the world. Our app is especially needed in urban environments with a diverse retail scene, where independent retailers play an important role.
We chose Berlin because of it’s multicultural nature and retail environment. There are hundreds of fashion boutiques and designer studios waiting to be discovered by hundreds of thousands of people coming to visit this wonderful city every month.
There’s a fierce competition in e-commerce and fashion is the first wave of the digital shopping, experiencing increasing cost per click in digital campaigns and demanding user experiences needed to overcome the industry noise and really score better performance. Where’se the industry going?
Well, we think the trends are personalization (of services and goods offered); sustainability (in practices, production and in business models as well), which is very important for the new generation of shoppers; and finally the concept of sharing rather than owning, which means rental business models in fashion retail.
Name three ecommerce or tech startups that, in your opinion, are going to reshape the market
Photo by Teddy Kelley on Unsplash