The EyeFitU patented Sizing Engine is now available for integration via a SaaS model for online stores and offers consumers personalised sizing recommendations when shopping online.
The platform is now available due to the success of EyeFitU’s B2C shopping app where millions of interactions have provided global user generated sizing content that has been interpreted by its AI.
The future of fashion retail is all about personalisation. Tailored shopping experiences are not just what customers want, but what they expect. What’s more, fashion retail is gathering momentum on the sustainable front as the industry faces the challenge of the increasing demand for fast-fashion, a practice that can have a huge environmental impact.
Isabelle Ohnemus, CEO and founder of EyeFitU, commented: “Fashion brands are renowned for having different size charts, that change from country to country, resulting in high returns rates from consumers and crazy inventories for retailers. EyeFitU eliminates all these sizing issues for shoppers and lets designers size the way they want. Our smart sizing algorithm suggests the best possible fit recommendations, saving both retailers and consumers time and money”.
The EyeFitU patented Sizing Engine is a multi-parameter software integrating Artificial Intelligence. Through user-generated content, the feedback loop enables the platform to cross reference consumers sizing preferences in an indefinite amount of brands and garments (Virtual Size Charts™). This is unique because no two people are created equally, body shapes vary widely and the information available from brands can differ vastly also. EyeFitU’s agile technology allows for brands to integrate the specificities of their garment types per brand in the most granular way currently available in the industry.
Significantly, last year, EyeFitU obtained its patent for the ‘Body Reference Model’ which is very important for the sizing software as it ensures the body model technology produces the most accurate results possible.
With the aim to solve the issue of inconsistent sizing across different brands, EyeFitU uses Machine Learning to improve the information provided by the mass of data from consumers. Recommending the correct fit to its users, the platform helps to reduce returns rates and dead inventories, saves wasted time, lets customers have an enjoyable experience and encourages a more eco-conscious approach to clothes shopping.
Reducing returns will result in higher net revenues and lower fulfilment costs as well as increased customer satisfaction which has a positive impact on average basket size and shopping frequency of the consumer. Retailers using the platform have the ability to send personalised messages about new products, sales and leftover stock.
Increase sales by improving customer confidence and satisfaction (conversion rate, basket size and shopping frequency)
Respectful of the sizing of each brand
Use of customer data for personalisation
Single customer view
Easy API integration across all platforms
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