November 27, 2020
We’re all aware of the environmentally-destructive impact the fashion industry has on our planet. Its practices account for 10% of the planet’s global carbon emissions, and by 2050, this percentage is expected to increase to 24%. In attempts to reduce the impact, movements like second-hand fashion are on the rise.
In fact, the second-hand segment is expected to reach $64 billion within the next five years. Younger shoppers are the ones that pursue this trend the most, with 90% of Gen Z-ers open to second-hand purchases. What is more, according to a report called The Smart Side of Fashion by Vestiaire Collective, they are also looking for more sustainable options, with eco-friendly brands like Veja, Stella McCartney, and Ganni gaining popularity.
As demand continues to rise, online marketplaces for both standard and secondhand shopping are facing more competition. When it comes to efficiency and personalization, shoppers expect it from second-hand e-commerce stores too, just like they do from standard retailers.
In this article, we’re doing a brief overview of the second-hand e-commerce landscape, with suggestions on how to leverage emerging technologies like Artificial Intelligence (AI) to make the customer experience more personalized.
Coming from Lithuania, Vinted is an online marketplace where users can purchase, sell, and exchange their clothes or accessories. What is more, together with the second-hand marketplace, Vinted also provides forums where users can communicate and talk about fashion. The marketplace started with women’s clothing and then expanded to men’s and children’s items. The platform has over 20 million members, with 15,000 new visitors coming every day. It’s currently available in 12 countries, where users can access the app through iOS, Android, or desktop.
Endless Wardrobe is a UK-based startup that offers users to buy or rent women’s clothing. The Enless Wardrobe offers apparel that is normally purchased specifically for an event or celebration and is then either discarded or left unworn for long stretches of time, wasting the clothing and the fabrics that used to create it.
The method is easy: find the apparel that suits you, order it, wear it for your event, and then return it free of charge to The Endless Wardrobe. This way, you don’t have to buy a new dress for every wedding you go to and then leave it forgotten in the back of your closet.
Loopster is a UK-based second-hand marketplace for children’s and women’s clothing. Sellers give Loopster their clean clothes their children don’t wear anymore and get paid upfront. The pieces that Loopster doesn’t accept go to the company’s charity partner. Loopster focuses mainly on high-quality brands, selling their pieces at affordable prices.
Unlike other stores that allow sellers to sell directly to buyers, One Scoop Store and Stashrak collect the selling pieces themselves. At car boot sales, the teams of the two stores hunt through piles at charity shops to find pieces they can sell in their stores. The shopping process is quite standard: buyers can search for clothing using categories and search filters to help them find what they desire.
Secondhand stores and marketplaces must create experiences that are customized to the needs of their target consumers. AI is a technology that can help them achieve this.
We can describe AI as a set of intelligent programs that execute tasks faster and more effectively than humans. This is an area of study that involves machine learning, deep learning, natural language processing (NLP), recognition, and others.
In order to provide insightful information, AI uses vast amounts of data, allowing apparel retailers to smartly produce and build a more competitive business model.
For example, retailers can leverage visual search to improve the customer experience. This AI-based technology allows website visitors to search by images instead of text queries. For example, if they see a bag they like, they can take a picture of it, upload it on the e-commerce store’s visual search engine, and get a list of the most similar ones. This makes product discovery much faster and more customized.
Another AI-based technology that provides personalization is automatic tagging. Automatic tagging organizes and tags images from the product catalog, using sophisticated AI algorithms. Thanks to these smart descriptive tags, second-hand retailers can collect data about how users search for products. They can leverage this data to identify bestsellers, eliminate unpopular products, and show the customer what they want to see on their feed.
Many second-hand retailers have started adopting AI to engage shoppers. For example, thredUp personalizes its services by leveraging AI to provide suggestions and place the products of sellers in the right offerings. The technology has also been used to automate the manufacturing of its Goody Boxes, which sell shoppers a range of items depending on their preferences.
The goal of the organization is to empower a new generation of shoppers to consider second-hand first, holding clothes out of landfills so that individuals can look fantastic without contributing to environmental pollution.
One perfect example is also Project Cece. An online platform for recycled apparel was developed by this Dutch tech fashion startup. To take their platform one step forward and encourage users to locate sustainable versions of their desired products simply by uploading images of them, they introduced Pixyle's visual AI engine.
AI adds innovative tools, dynamic aspects of analytics, and new data sources. The technology has the ability to make organizations more flexible and competitive, allowing them to respond to trends and events in real-time. Most notably, in a way that's both collaborative and transparent, AI can push fashion retailers towards sustainability.
AI can power up second-hand e-commerce stores to be as competitive as their traditional industry opponents. Gaining insightful information, they can find out what shoppers want and create personalized feeds according to their preferences. Moreover, through market forecasts and predictive maintenance, they can improve product circulation.
As the world is in a situation where becoming aware of the environment is the only option, the second-hand model is the model that will become mainstream.