Moda Operandi leverages 350 trunk shows and additional real-time data from customers who buy fashion a season ahead to accurately predict key trends, sought-after items and top-performing collections. Some of these insights were released today in Moda Operandi’s SS20 Runway Report, which takes the guesswork out of the buying process through a combination of sales and engagement data; pattern identification through machine learning and traditional tools used by the fashion buying team.
Moda’s two businesses, trunk shows for preorders, and boutique for in-season merchandise, are symbiotic. “We’ve found that, once in our boutique, trunk show bestsellers can have two-to-10-times greater sales per item than boutique inventory that’s not informed by preseason sales,” said fashion director Lisa Aiken. “That’s because we’ll able to react to what she wants up front, by gauging consumer demand.
“Any traditional retailer will go to market and have all the history at their disposal and have a very keen eye on what they want to stand behind,” said Aiken. “This trend report is not relying on history. It’s an analysis of the consumer response to the runway season overall. The findings will validate some things, which gives you added conviction for the things you want to stand behind.”
Aiken was surprised by the reaction to Simone Rocha‘s giant pearl Perspex top-handle bag, which was Moda Operandi’s best-selling bag. “The Simone Rocha bag is a truly beautiful piece,” she said. “That’s what the client is in love with. I’m not sure I would have chosen it because it’s a very emotional purchase.”
Customers were clearly enamored of the romantic bent for spring. Several brands that went against their established grain and fell hard for femininity, caught consumers’ attention. “A trend becomes most compelling when unexpected brands lean toward the aesthetic,” Aiken said.
Minimalist labels Khaite, Marina Moscone and Gabriela Hearst‘s more feminine direction incorporated florals, sheer fabrics and decorative embroidery. The romantic trend also played out with sweetheart necklines at Khaite, while one-fourth of Miu Miu’s necklines were exposed to reveal the décolletage.
Brandon Maxwell, who’s known for his eveningwear, ventured into denim and tailoring for spring. “It’s interesting when you have immediate consumer reaction,” Aiken said. “Designers would have to wait six months until something landed in a store. We can get an amazing response and that fuels opportunities for their business.”
Moda Operandi used AI to identify SS20’s top color trends, which include ivory overtaking optic white and more muted shades. Gray saw a 36 percent increase with Prada and Miu Miu leading the charge. Offbeat brights such as bold orange and buttercream yellow also registered with customers.
Blazers accounted for 30 percent of all jackets and outerwear sold for SS20, a 275 percent increase from SS19. “Different silhouettes are giving the client a reason to buy new and are driving the business,” Aiken said, citing The Row and Jacquemus’ strong-shouldered versions.
The report analyzed the buzz around brands on social media. The collection that generated the most preorder inquiries over Instagram direct messaging was Bottega Veneta, which Aiken dubbed, “the hottest brand on the planet.” Other buzz-generating brands included Maxwell, with the most engagement, and Loewe, the most traffic.
Jennifer Lopez‘s appearance on Versace’s Milan Fashion Week runway wearing an updated version of the now-infamous palm print dress she wore 20 years ago at the Grammy Awards, fueled interest at Moda, which saw 22-times more traffic from consumers preordering the dress than the average SS20 product.
Moda customers spend $2,000 on average per trunk show preorder. The higher investment doesn’t stop them from shopping on a mobile device. In fact, two-thirds or 65 percent of shopping sessions for SS20 took place on mobile devices, with 35 percent occurring on desktops.
“We’re seeing the positive response of using data,” Aiken said. “The opportunity is trunk show, and that’s the acceleration pedal. Based on insights, we can drive more depth. Ultimately, it’s blending data science with the human touch, and recognizing how we can be powered by it.”