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To tell us more about EasySize is Gulnaz. Thank you. Can we put the slides on the screen? Perfect. Hi, my name is Gulnaz and I'm the CEO and founder of EasySize. At EasySize we help fashion online shops to solve one of the biggest problems, sizing. If you have ever purchased any clothes online, that is definitely something that you have experienced. Sizes differ dramatically between brands and it's not only a huge hassle for online shoppers, but it's also a big issue for online retailers. Sixty to eighty percent of all online shop visitors leave a website without making a purchase simply because they are not sure about the size. More importantly, size and fit is the number one reason for returns. It is a massive pain. It leads to low conversions, loss in revenue, and enormous costs. More than 10 billion euros a year are spent in Europe by online retailers on solving this problem. So to solve it we've developed sizing intelligence. It's the only scalable solution on the market which knows your best fit every single moment you are online. How do we do it? Fashion is all about perception. Our choice of clothes reflects our style and fit preferences, and it might differ depending on the category or brands. That is why in EasySize we do not rely on body or clothes measurements. Instead we analyze anonymous data of orders and returns provided by online shops. No personal, no payment information, just hard facts. What people buy, what they return. A single shop is usually limited to what people do there. We, on the other hand, can follow the same customer across the entire digital universe. So we see what you buy and return in a shop A and B and C and everywhere else. So eventually what we are trying to do is to build a network of connected sizing and returns profiles where we know what people do everywhere and we are able to have that network which is scalable because everyone contributes to that, which is diverse because it covers different geographies and brands, and which is relevant as this information is getting updated 24-7. Since our launch last year we have gathered already more than half a million unique users on our platform. And every time when such a user gets in contact with our technology, in a shop or a third party service, we immediately request a connected sizing profile and can predict the size right away. If it's a new customer, we will ask them to add a size and a brand of something that they already have. So EasySize uses machine learning algorithms and this crowdsource fashion behavioral data to know your best fit, to really dig deeper into your personal shopping habits, and also understand the market trends in general. So how does this technology help fashion e-commerce as an industry? Fashion e-commerce is unique. It is a massive market, but yet it's one of the slowest growing verticals online, especially if you compare it to books or electronics. And one of the reasons is because fashion online does not really reflect our experience in regular brick and mortar shops. We cannot touch clothes, we cannot chime them out, we don't have a dedicated sales assistant who can help us. There are obviously now technologies that are trying to resolve that, like VR or AR or some support messages and so on. But they're either not accessible 24-7 by customers or they're expensive to implement. What we wanted to do with EasySize is to create an experience that you have an invisible sales assistant who is dedicated, knows everything about fashion, knows everything personally about you, and is also there for you 24-7. So it's there for you on the product page. It helps you if you're about to purchase the same item in multiple sizes. It can act as a size filter, where you click one button and you get their personalized product fit, where everything is in your best fit and available in stock. It can also be implemented on top of marketing campaigns. So you can finally send effective emails and actually get people to click and purchase in one click. We're also trying to embrace the whole trend about conversational experience. That's a new thing in fashion and commerce. People are tired of shopping in a regular online shop. They want to chat, they want to be able to actually have that conversation with an online shop. They want to see the stories. We're able to do that by using AR-driven scenarios and bots. So obviously it is a buzzword now, but we found a way to actually use it for fashion. So we're able to have a chatty bot, which we call it internally on mobile, where we chat with the customer in the messenger format and we help them to find all the best clothes. That is something that works enormously well with millennials and young audiences. We are also able to actually activate living customers who are about to leave the web page and are hesitant about the size. Our web bot pops up when we think that you're about to leave and actually chats with you and helps you to find the right size. Finally, we have a solution which converts leading customers to transactions. More importantly, we are also able now to educate online retailers as we are gathering all the behavioral data. So we share this information with them in a dashboard. So we can say, hey, do you know that 80% of your customers also buy Nike in other shops? Or do you know that this brand, which is leading in returns in your store, is also actually returning the most in other stores as well? That's the unique data which we are able to track because, again, we see the customer's behavior across other shops. So now there is also one additional thing which we are able to do. It's integration with third-party services. So our solution is able to enrich our data through collaboration with recommendation services like ClercIO, which we are launching this month, and other services like Affiliates and so on. We are the only company in the market which is able to do that. We have launched our product starting from the Nordics a year ago, and now we are expanding globally. We have just launched with the largest retailer in Russia, Kupivi IP. And this is just the first big customer outside of Europe. And by using this technology, we are able to really improve the experience, which reflects in the customer's businesses. Conversion to sales without a solution is nearly four times higher than customers online shop see without it. And returns rate is almost three times lower than without our solution. So the next big step for us is to really achieve the global coverage, expand to MENA and APAC, where we have our first customers, and reach the level of 10 million unique users on our platform by summer next year. So, yeah, this is how we solve the fashion problems by using technology and by analyzing customer shopping habits. Thank you. Thank you.
