Runway Report: Spring Summer 2020










Runway Report: Spring Summer 2020







The Moda Operandi SS20 Runway Report: Using Data Science & Fashion Expertise to Predict Next Season’s Trends

We’re excited to bring you the second installment of the Moda Operandi Runway Report, the only consumer-driven trend analysis based on real-time data from interactions with the luxury fashion consumer. Unlike other trend reports, Moda’s forecast is determined by those who shop a season ahead, giving us a unique position to accurately predict next season’s trends, key pieces, and best-performing collections.

Because Moda sells runway in real time, our data identifies the key pieces and trends of next season before any other retailer. This model can benefit our designers and Moda as we make inventory investment decisions for the season ahead. We take the guesswork out of the buying process, and as a result, we’ve found that, once in our Boutique, bestsellers in Trunkshow on average have two-10x greater sales per item than Boutique inventory that is not informed by preseason sales. For example, Prada’s Leather Combat Boots and Sheer Lace Cape, both bestsellers in Prada’s FW19 Trunkshow, saw a 100 percent sell-through within just days of hitting our Boutique site. Among other Trunkshow hits that now boast a higher- and faster-than-average sell-through are Isabel Marant’s Milane Sweater and Jalford Printed Jersey Top, and Paco Rabanne’s Tiger-Print Lurex Dress and Tailored Floral Suit. The list goes on.

The Moda Operandi SS20 Runway Report: Using Data Science & Fashion Expertise to Predict Next Season’s Trends

We’re excited to bring you the second installment of the Moda Operandi Runway Report, the only consumer-driven trend analysis based on real-time data from interactions with the luxury fashion consumer. Unlike other trend reports, Moda’s forecast is determined by those who shop a season ahead, giving us a unique position to accurately predict next season’s trends, key pieces, and best-performing collections.

Because Moda sells runway in real time, our data identifies the key pieces and trends of next season before any other retailer. This model can benefit our designers and Moda as we make inventory investment decisions for the season ahead. We take the guesswork out of the buying process, and as a result, we’ve found that, once in our Boutique, bestsellers in Trunkshow on average have two-10x greater sales per item than Boutique inventory that is not informed by preseason sales. For example, Prada’s Leather Combat Boots and Sheer Lace Cape, both bestsellers in Prada’s FW19 Trunkshow, saw a 100 percent sell-through within just days of hitting our Boutique site. Among other Trunkshow hits that now boast a higher- and faster-than-average sell-through are Isabel Marant’s Milane Sweater and Jalford Printed Jersey Top, and Paco Rabanne’s Tiger-Print Lurex Dress and Tailored Floral Suit. The list goes on.










To identify next season’s trends, we use a blend of sales and engagement data, pattern identification through machine learning, and traditional planning tools from our fashion and buying team.

Ganesh Srivats, CEO


















To identify next season’s trends, we use a blend of sales and engagement data, pattern identification through machine learning, and traditional planning tools from our fashion and buying team.

Ganesh Srivats, CEO















To identify next season’s trends, we use a blend of sales and engagement data, pattern identification through machine learning, and traditional planning tools from our fashion and buying team.

Ganesh Srivats, CEO












To identify next season’s trends, we use a blend of sales and engagement data, pattern identification through machine learning, and traditional planning tools from our fashion and buying team.

Ganesh Srivats, CEO






To identify next season’s trends, we use a blend of sales and engagement data, pattern identification through machine learning, and traditional planning tools from our fashion and buying team. For instance: It was clear to us that one of next season’s biggest trends will be the thong sandal, thanks to results from our computer vision analysis, combined with input from our fashion team who saw the modern thong sandal popping up in shows like Marni and Staud. To find SS20’s top color trends, we used AI to analyze all product images from the season, extracting the dominant color from each product image and computing the number of items offered (supply), against the number of items bought (demand), at each point in the spectrum. The results showed that warm tones of orange and yellow, shades of gray, and ivory were most popular among our customers. 

We believe the consumer is the biggest beneficiary of this data. By leveraging these predictive insights to buy into the most in-demand inventory, we allow the consumer—not just industry insiders—to determine next season’s fashion trends and more easily realize their unique personal style.

We’re excited to share our findings with you. 

Until next season, 

Ganesh Srivats, CEO

To identify next season’s trends, we use a blend of sales and engagement data, pattern identification through machine learning, and traditional planning tools from our fashion and buying team. For instance: It was clear to us that one of next season’s biggest trends will be the thong sandal, thanks to results from our computer vision analysis, combined with input from our fashion team who saw the modern thong sandal popping up in shows like Marni and Staud. To find SS20’s top color trends, we used AI to analyze all product images from the season, extracting the dominant color from each product image and computing the number of items offered (supply), against the number of items bought (demand), at each point in the spectrum. The results showed that warm tones of orange and yellow, shades of gray, and ivory were most popular among our customers. 

We believe the consumer is the biggest beneficiary of this data. By leveraging these predictive insights to buy into the most in-demand inventory, we allow the consumer—not just industry insiders—to determine next season’s fashion trends and more easily realize their unique personal style.

We’re excited to share our findings with you. 

Until next season, 

Ganesh Srivats, CEO


CONTINUE TO TABLE OF CONTENTS



CONTINUE TO TABLE OF CONTENTS