In 2021, there were 90 million more returns for fashion retailers compared to 2019. This year, there are expected to be 121 million returns in 2022. For retailers, this hurts EBIT margins and has a substantial environmental impact contributing 400,000 metric tons of CO2 on par with the levels that would be contributed by 4574 double-decker buses and 1.6 million hours’ worth of flight emissions. Dressipi was the brainchild of Sarah McVittie and Donna North, co-founders of return rate reduction software.

At the core of what Dressipi has done is predicting what customers will buy and not return. They work exclusively with fashion and apparel retailers. They can create and use data to transform the product discovery process to make the supply chain more efficient. While there is other return prediction software, they are currently the only one that’s exclusive to just fashion, so they have been able to outperform competitors, like Salesforce, specifically in the fashion category.

“Fashion is very different, it needs a very different approach,” McVittie said. “We’ve never failed to deliver less than 8 percent revenue growth year-over-year. We also help companies improve their profits by quite large margins seeing as we impact returns and sell-through rates.”

Fashion tastes and trends are not static when compared to other things like people’s opinions of their favorite books and movies. Also, when people are shopping, they are buying things to go with other things they already own. Tastes also change from season to season. Fashion is also in a constant state of newness, so turnover is very fast. What Dressipi attempts to do is solve all those problems of size fragmentation, return rates, and what retailers who have new products every month will do to get people to buy and not return.

“What we do is very simple,” McVittie said. “We take every product and create a product feed, then we ‘enrich’ every product. We look at over 1000 unique attributes that are analyzed by our fashion stylist team. The technology is then created and scaled by our AI team to help retailers understand the feature of every product. This helps them build a model around every visitor to figure out what their preferences are from a category level to a department level. Therefore, much better and relevant recommendations can be driven in real-time.”

McVittie has managed to scale Dressipi without any venture capital money. McVittie describes her business as “A bit like Stitch Fix, except for B2B.”

Dressipi helps retailers get more in control of their data for better selling products and data for later on in the supply chain in terms of what they need to be stocking. It keeps retailers more in control of the customer journey.

“One of our clients, an Italian retailer, has a huge loyalty program,” McVittie said. “What we’re able to do for him is send emails regularly of the best edit of what’s available in size in his store. That helps him drive a lot of traffic. We also help retailers understand what kind of product to buy based on these edits. All this has a huge benefit on company margins.”

Dressipi has racked up an impressive roster of clients so far including River Island, John Lewis & Partners, and Belstaff. The company’s current goal is to get more U.S. clients as they work on growing their business overseas. Who likes the hassle of returning clothes anyways?