Enhanced Retail Experience with AI Technology
With the launch of the AI Shopping Assistant, Fit Analytics Innovation aims to revolutionise the online shopping experience. This innovative tool provides conversational guidance using advanced size and fit technologies.
Fit Analytics, based in Berlin, regained independence from Snap Inc. two years ago. This strategic decision allowed them to retain 16 years of expertise and data insights, facilitating the development of the AI Shopping Assistant as part of their expanded product suite.
Tests conducted with major European retailers have demonstrated impressive results. There was a 42.5% increase in net revenue per visitor and a 3% reduction in size-related apparel returns. shoe return rates decreased by 15%.
Dr. Christoph Sawade, CTO of Fit Analytics, emphasised the importance of their technology by stating, "The real value comes from the engines behind it that actually understand size, fit, and style. Two decades of building that structured mapping is what shapes our data."
Challenging Traditional Retail Models
The AI Shopping Assistant challenges current 'pay-to-play' models in online retail. By prioritizing relevance and match accuracy, Fit Analytics seeks to enhance the shopping experience, ensuring the first product seen is the right one for consumers.
CEO Mar Mercadé highlighted their vision by saying, "We’re making a bet that in three years online shopping will be unrecognizable. AI will drive that change; but the industry is moving in the wrong direction."
Fit Analytics is positioning its AI Shopping Assistant as a direct challenge to the 'Google Shopping' model. While other players rely on 'pay-to-play' keyword bidding, Fit Analytics leverages its extensive industry knowledge to create meaningful shopping experiences.
Starting in June, retailers will have access to the AI Shopping Assistant, marking a new era in the integration of AI with consumer retail. This move underscores Fit Analytics' commitment to transforming online shopping.
The company believes that by reclaiming independence, they bypassed corporate red tape to build a deep-learning engine that understands the nuances behind two decades of global returns.
