In this article, we explain what user experience is and the three key ways machine learning can enhance user experience in apparel e-tail.
Machine learning allows companies to get to know their users in an intimate and non-evasive manner. This technology is being utilized by various industries – the healthcare system, security and of course, apparel retail.
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Summer 2020 trends are changing due to the effects of COVID-19. Shopping patterns are shifting and conversions for key summer items have declined.
Summer 2020 is expected to be unlike any summer we’ve experienced. With stay-at-home orders still in place for some locations and summer trips being canceled due to COVID-19, it’s no surprise that shopping trends have shifted this year.
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As a follow up to our latest e-book, we analyzed the data in the first half of Q2 2020 to bring you updated insights on the effects of COVID-19 on the retail industry.
In our recent e-book, COVID-19: The Impact on Global Buyer Behavior, we reported on the 27% increase of first quarter purchases (January 2020 – March 2020), but also noted that we saw a downtrend in purchases as the pandemic unfolded and uncertainty was on the rise with stay-at-home orders. Since our last e-book, the rules towards social distancing have pivoted from complete lock-down to a slightly more relaxed, but still ‘socially distant normal’. Consequently, we felt it imperative to follow-up on how the apparel retail landscape has continued to evolve to safely support shoppers.
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Fit Analytics has an intuitive solution that reduces the need for shoppers to deliberately over-order.
The Multi-Size Purchase Issue
Poor fit is one of the leading reasons shoppers return items they purchase online. Sizing varies across different apparel brands and even within a single retailer’s store. This has led shoppers to mistrust online sizing information and taking matters into their own hands by multi-size ordering.
In this article, we cover how to reduce returns in e-commerce by focusing on how Fit Analytics is using the power of machine learning to combat the apparel industry’s multi-size purchase problem.
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Fit Analytics’ Head of Product, Dan Mayer, explains how Fit Finder takes the guesswork out of finding the perfect size online.
Launched in 2013, Fit Finder was created to help find your fit. The intuitive size advisor tool is powered by the most advanced machine learning algorithms in the business and the industry’s biggest data set.
Bridging the gap between in-store and online shopping, Fit Finder provides customers with the requisite confidence needed to find the right size and fit every time, without ever stepping foot inside a store.
Fit Analytics’ Head of Product, Dan Mayer, gives a deeper insight into Fit Finder and reveals how the tool can evolve in the future.
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Our eBook shares key insights on the impact COVID-19 has on e-commerce consumer behavior.
It’s no secret that COVID-19 has affected everyday life for individuals around the world. People and businesses are adjusting to a new normal unlike anything they’ve experienced in the past. With non-essential businesses being forced to close their doors and stay-at-home orders in place until at least the end of April, consumers are turning to online shopping to fulfill their needs.
We found that buyer behavior has changed in different ways globally. Retailers, in general, experienced a surge in online purchases in the first quarter of 2020, even with the spread of the pandemic.
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New technologies in the apparel e-commerce space continue to evolve on a regular basis. We’ve sourced 4 of the hottest technologies to fuel growth online.
There is a hot spot in e-commerce innovation – and it’s apparel. These days, customers expect to interact with products in a variety of ways, on and offline. From smartphone inspiration to AI personalization, we selected four of the hottest e-commerce tech trends we think apparel and footwear retailers should use in 2020.
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How Machine Learning Delivered 355 Million Size Recommendations in 5 Days.
The trends across retail and e-commerce continue to evolve every year. After a busy week of Black Friday and Cyber Monday, changes in the industry became even more clear. This year brick and mortar retailers saw a steady decline in foot traffic. Customers turned to online shopping – through both mobile and desktop. Purchases through mobile devices saw a 21% increase from last year. Mobile accounted for 39% of all e-commerce sales – totaling $2.9 billion in sales from smartphones alone (source: Retail Dive). According to the Shopify Plus Fashion Industry Report, retailers are driving growth through machine learning, artificial intelligence, and personalized customer experiences.
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We are excited to announce that Aéropostale is now live with Fit Finder. Aéropostale, a global lifestyle brand, represents inclusive, modern and collaborative youth culture.
We are excited to announce that Aéropostale is now live with Fit Finder. Aéropostale, a global lifestyle brand, represents inclusive, modern and collaborative youth culture. The retailer specializes in effortlessly stylish, everyday apparel and on-trend accessories for young men and women. They provide authentic jeans and comfortable fashion and fashion basics at compelling values in an exciting store environment on and offline.
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A two-month A/B test with Fit Finder showed positive results for Swedish outdoor retailer Ridestore. Customers using Fit Finder showed a 9% increase in value per visitor and a 4% increase in conversion rate.
Everyday explorers need extraordinary gear – Ridestore is where they go to get it. Founded in Sweden over 10 years ago, Ridestore is known for its impressive selection of outdoor brands. With customers at the heart of its operational strategy, the company offers regional online shops in Sweden, Finland, Norway, Denmark, Poland, Germany, Austria, Switzerland, Italy, France, Spain, The Netherlands, and the UK.
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