Spotted: Recent years have witnessed two key retail trends: the move towards more personalised, curated customer offers, and pressure from stakeholders to tackle waste in the industry. UK-based Dressipi is working to tackle both issues with machine learning and artificial intelligence (AI). The company’s co-founders were inspired by their own first-hand experience struggling to find the products they wanted to buy.

Dressipi has developed a software platform that gives retailers the tools they need to personalise the shopping experience for individual customers. It does this by using a combination of human style expertise and AI to develop high quality product and brand data. Human stylists create a ‘taxonomy’ of fashion attributes that can be applied to each item. AI technologies, such as computer vision and natural language processing, are then used to apply these attributes at scale.

The same predictive models and algorithms that Dressipi uses to develop personalised insights can also be used to forecast buying and merchandising decisions. By better matching supply and demand, retailers can avoid waste in the supply chain, benefitting both their bottom line and the plant.

Dressipi’s technology has three key strengths. First, its algorithms have been developed over years in collaboration with human fashion experts. They are therefore specific to the needs of the fashion industry. Second, Dressipi owns extensive datasets of garment attributes and fashion-specific customer preferences, and the company’s ability to cleanse and parse all this data is the core of its offer. Finally, the company has a proven track record working with some of the industry’s leading names, delivering externally validated results.

Other AI-powered retail innovations spotted by Springwise
include personalised
wine recommendations, predictive
analysis to speed shipping, and computer
vision used for fashion cataloguing.

Written By: Matthew Hempstead