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Returns in online retail Dresslife in great demand
Finding items they really like quickly isn’t always so straightforward for customers. Unsuitable items of clothing inevitably means more returns.
This is where the German fashion-tech startup Dresslife from Hanover comes into play. In the interview, Dr. Julian Hensolt, co-founder and CEO of Dresslife, explains why personalization is a key factor for fashion retailers and how the technology works.
Why is personalization relevant to a returns-intensive sector like fashion?
Personalization can help customers to quickly find items of clothing that fit them well and in the style they like, while also reducing the returns rate in online fashion retail. The online shops of leading fashion brands sell a vast range of clothing. This presents a challenge for customers looking for an item that fits well, but is also just the right style. Per shopping session, customers view less than 5 percent of the items of clothing available. This means they usually don’t see the item that’s ideal for them, resulting in lost revenue for fashion retailers. Customers can’t try items on when shopping for fashion online. This means end consumers don’t get the chance to find out whether an item suits them or if the fit is right. This leads to high returns rates for clothing of up to 50 percent and significant additional costs for fashion retailers and consumers.
How does personalization based on artificial intelligence (AI) work?
Using AI, product recommendations can be made in line with each customer’s individual needs. Dresslife’s AI “personalizes” or sorts the product range in an online fashion shop based on a customer’s individual style and fit. The technology predicts the likelihood of online shoppers liking an item of clothing and not sending it back. Dresslife’s AI recognizes the similarities between individual products just as well as a human can. The technology can also generate exact recommendations for over 70 percent of customers based on previously purchased or returned products and fashion retailers’ clothing data (e.g. size of an item). Dresslife significantly reduces the number of returns due to fitting issues.
What’s the benefit of “fashion-specific” technology for personalization in fashion?
Personalization is much more complex for clothing than in other segments. Firstly, product life cycles in fashion are extremely short. Products are often only displayed in an online shop for just two weeks and new products are continually being added for which no verifiable data on sales yet exists. There’s also direct dependence on the human body in fashion. Both factors mean greater data complexity and make accurate product recommendations more difficult. That’s why Dresslife – with its fashion-specific AI – specifically addresses the special characteristics of the fashion industry and can increase net revenue by over 5 to 15 percent (compared to standard recommendation engines).
How can this technology optimize the e-commerce experience for fashion consumers and companies long-term?
AI-based personalization will continually improve in generating product recommendations over a long period of time. The more artificial intelligence is trained, the more accurate the recommendations produced for online customers. As well as providing benefits in terms of revenue and returns, personalization also enables fashion retailers not only to predict which products will sell well, but also enables better forecasting on which and how many items of clothing should be produced.
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