Ecommerce Product Discovery Insights for Retail Fashion

Fashion Intelligence Studio
February 16, 2021
Ecommerce Product Discovery:

An Interview with Velou’s Fashion Intelligence Director, Tricia Lahren, on Retail Fashion’s Changing Technologies

The retail fashion landscape is changing rapidly. Brands and retailers are moving online and strengthening their customer experience across the digital shopper’s journey. We interviewed Velou’s Fashion Intelligence Director, Tricia Lahren, to give our readers a glimpse into developments in fashion and technology, and how Velou creates innovative customer experience and product discovery solutions for fashion retailers to support their ecommerce goals. Tricia has two decades of working in fashion styling with a range of ready-to-wear and luxury retailers, such as Baby Gap, Neiman Marcus, Pottery Barn, Lord & Taylor, and Levi Strauss, and with Tailor App, an in-house incubator of Area 120 for Google. Welcome, Tricia.

You’re the Fashion Intelligence Director at Velou. What does that mean?

My primary goal is to create quantifiable, fashion-related datasets, so that our engineers can build the algorithms that our retailers need. I have categorized and indexed over 1,500 attributes to thoroughly tag any fashion or accessory product. From off shoulder to halter to asymmetric and everything in between, there are at least 25 different necklines, for example. Plus the words and phrases we use to describe things in fashion, like dress length, are always changing and evolving. So I’m researching trends and emerging styles to make sure that our AI has all of the data it needs to understand our customers’ products. Additionally, my days are spent interpreting data, communicating with engineers, and checking our customers’ webstores.


What’s your background? How did you get into this field?

I’ve been working in fashion for a couple decades, from sales at Benetton and Nordstrom to dressing for New York Fashion Week and designing for sportswear brands. I got my B.S. in Merchandise Management and an A.A.S. in Fashion Buying and Merchandising from the Fashion Institute of Technology and worked with clients such as Baby Gap, Neiman Marcus, Pottery Barn, Lord & Taylor, and Levi Strauss.


I started to get more heavily involved at the intersection of tech and fashion when I was hired by a Google incubator to offer personalized styling services. I was astounded by the sheer number of users asking for fashion and shopping advice. The Google incubator built an app that lets you interact directly with a human stylist. Then, customized "carousels'' were sent to the user. Although Google wanted to promote Google Shopping, the biggest takeaway is that all people want styling help. I learned that there is a gap in the technology to capture the knowledge that a human stylist brings. I apply that now towards AI models. Our solutions at Velou for retail customers will be able to offer this personalized styling algorithmically.

“A great stylist will know as much as she can about her clients and about retail stores.”

What are the skills a fashion stylist brings to ecommerce technology?

A great stylist will know as much as she can about her clients and about retail stores. I myself might “invade” my clients’ closets—snoop around to learn about their preferences, size, colors, fits, styles, and designers who they gravitate toward. It’s very personal and requires a tremendous amount of trust. In regards to retailers, I will know the demographics of each retailer, their store’s floor layout, what designers are sold there, the price points and when to expect new inventory to arrive, as well as end-of-season sales.


An experienced stylist will also offer their client options. Customers may see other things they want to buy but just as importantly, they want to make sure that they made the right choice with their purchase. By seeing multiple, similar products, they can make that decision with ease. For example, I recently helped my niece buy a prom dress. She had very specific requirements - navy blue color, strapless style, floor length and...sexy. I combed through the internet and offered her a variety of options to her specifications. Because I understood her, and her preferences and tastes, I was able to narrow down the options I knew would resonate. I saved her time and reduced her anxiety from endless browsing so she could focus on what she already knew she wanted. In the end, she was totally confident in her choice and she looked great!


What’s your approach to creating algorithms to help fashion become more discoverable?

I’m driving algorithms at Velou that take the same approach as a personal fashion stylist: learn everything we can about the client and then apply that knowledge to make accurate predictions about shopper’s behaviors. We can teach technology because of the developments in AI to recognize these style preferences. Through repetition, we can build the algorithm to be stronger each time. The algorithm will recognize the pattern, style, color, and other product features such as necklines, and unique attributes, like crystals. The algorithm also continues to build upon the preferences of the user, similar to how a stylist understands her client.

How do you think major fashion retailers can benefit from using search technology?

At Velou, we’ve designed our algorithms to fit our customers’ needs. Our search understands each of their inventories and how they label their products. Then, our AI models dramatically build upon the details of each and every item in our customer’s catalog by diving deep into their products and labeling each feature through our Hyper-tagging Engine, which is a data enrichment process.  


Retailers can benefit by knowing that our search engine isn’t going to leave their products behind. We display all available products as well as similar products for their customers in the size(s) they are looking for. It's incredible. Offering like products increases sales and ultimately makes the customer feel confident that they looked at all available options and that the retailer was really on top of their web store. Have you ever gone to a store and typed in a floral maxi dress and gotten the completely wrong item? It's a turn off.


How does the technology you’ve worked with change a stylist’s job and how do you see it change the experience of fashion in a retail setting? Where do you see the retail industry headed with the incorporation of technology such as AI?

Sales associates are often the ones to assist customers in finding different products, like a similar option, when the retailer doesn’t have a size in stock. Technology will do this automatically for online stores. It can ensure products are discoverable and offer all the matching options available. All this is the bulk of a stylist’s job and using tech to present products in an orderly fashion (no pun intended!) saves time and makes for a fulfilling shopping experience.


Retailers are seeing an increase in online sales. Keeping their online customers happy is crucial to a retailer's success. Customers want to find products...and fast. Technology will enable customers to access stock in real time and provide retailers with real-time feedback on the most searched-for items. Velou alerts our retailers to adjust product inventory based on demand so that they can keep stores stocked with the right products and the right merchandise that keeps the customer coming back.


What are you excited to work on next and what exciting solutions can we expect to see from Velou?

I’m excited to work on predictive styling suggestions with the Velou team. Our product is already able to recognize the garment and understand its occasion. We can then provide options that would be appropriate through the use of hyper tagging. Developing a new solution to give shoppers outfit suggestions based on our retail customer’s stock is a game changer. When it comes down to it, everyone wants a well-styled, personalized look. Our looks will be created through algorithms and by thoroughly understanding the end customer. Exploring outfit suggestions through the use of AI enables shoppers to visualize the outfit, which is really exciting.


Tricia Lahren's Bio: Tricia is the Fashion Intelligence Director for Velou. She has been working in fashion for two decades, from sales at Benetton and Nordstrom to dressing for New York Fashion Week and designing for sportswear brands. She received a B.S. in Merchandise Management and an A.A.S. in Fashion Buying and Merchandising from the Fashion Institute of Technology. Her interest in “styling” came about from exposure to Vogue Magazine and assisting established stylists. Her clients range from ready-to-wear to luxury retailers, such as Baby Gap, Neiman Marcus, Pottery Barn, Lord & Taylor, and Levi Strauss. Prior to Velou, she worked with Tailor App, an in-house incubator of Area 120 by Google.

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Interview

Ecommerce Product Discovery Insights for Retail Fashion

Fashion Intelligence Studio
February 16, 2021
Ecommerce Product Discovery:

An Interview with Velou’s Fashion Intelligence Director, Tricia Lahren, on Retail Fashion’s Changing Technologies

The retail fashion landscape is changing rapidly. Brands and retailers are moving online and strengthening their customer experience across the digital shopper’s journey. We interviewed Velou’s Fashion Intelligence Director, Tricia Lahren, to give our readers a glimpse into developments in fashion and technology, and how Velou creates innovative customer experience and product discovery solutions for fashion retailers to support their ecommerce goals. Tricia has two decades of working in fashion styling with a range of ready-to-wear and luxury retailers, such as Baby Gap, Neiman Marcus, Pottery Barn, Lord & Taylor, and Levi Strauss, and with Tailor App, an in-house incubator of Area 120 for Google. Welcome, Tricia.

You’re the Fashion Intelligence Director at Velou. What does that mean?

My primary goal is to create quantifiable, fashion-related datasets, so that our engineers can build the algorithms that our retailers need. I have categorized and indexed over 1,500 attributes to thoroughly tag any fashion or accessory product. From off shoulder to halter to asymmetric and everything in between, there are at least 25 different necklines, for example. Plus the words and phrases we use to describe things in fashion, like dress length, are always changing and evolving. So I’m researching trends and emerging styles to make sure that our AI has all of the data it needs to understand our customers’ products. Additionally, my days are spent interpreting data, communicating with engineers, and checking our customers’ webstores.


What’s your background? How did you get into this field?

I’ve been working in fashion for a couple decades, from sales at Benetton and Nordstrom to dressing for New York Fashion Week and designing for sportswear brands. I got my B.S. in Merchandise Management and an A.A.S. in Fashion Buying and Merchandising from the Fashion Institute of Technology and worked with clients such as Baby Gap, Neiman Marcus, Pottery Barn, Lord & Taylor, and Levi Strauss.


I started to get more heavily involved at the intersection of tech and fashion when I was hired by a Google incubator to offer personalized styling services. I was astounded by the sheer number of users asking for fashion and shopping advice. The Google incubator built an app that lets you interact directly with a human stylist. Then, customized "carousels'' were sent to the user. Although Google wanted to promote Google Shopping, the biggest takeaway is that all people want styling help. I learned that there is a gap in the technology to capture the knowledge that a human stylist brings. I apply that now towards AI models. Our solutions at Velou for retail customers will be able to offer this personalized styling algorithmically.

“A great stylist will know as much as she can about her clients and about retail stores.”

What are the skills a fashion stylist brings to ecommerce technology?

A great stylist will know as much as she can about her clients and about retail stores. I myself might “invade” my clients’ closets—snoop around to learn about their preferences, size, colors, fits, styles, and designers who they gravitate toward. It’s very personal and requires a tremendous amount of trust. In regards to retailers, I will know the demographics of each retailer, their store’s floor layout, what designers are sold there, the price points and when to expect new inventory to arrive, as well as end-of-season sales.


An experienced stylist will also offer their client options. Customers may see other things they want to buy but just as importantly, they want to make sure that they made the right choice with their purchase. By seeing multiple, similar products, they can make that decision with ease. For example, I recently helped my niece buy a prom dress. She had very specific requirements - navy blue color, strapless style, floor length and...sexy. I combed through the internet and offered her a variety of options to her specifications. Because I understood her, and her preferences and tastes, I was able to narrow down the options I knew would resonate. I saved her time and reduced her anxiety from endless browsing so she could focus on what she already knew she wanted. In the end, she was totally confident in her choice and she looked great!


What’s your approach to creating algorithms to help fashion become more discoverable?

I’m driving algorithms at Velou that take the same approach as a personal fashion stylist: learn everything we can about the client and then apply that knowledge to make accurate predictions about shopper’s behaviors. We can teach technology because of the developments in AI to recognize these style preferences. Through repetition, we can build the algorithm to be stronger each time. The algorithm will recognize the pattern, style, color, and other product features such as necklines, and unique attributes, like crystals. The algorithm also continues to build upon the preferences of the user, similar to how a stylist understands her client.

How do you think major fashion retailers can benefit from using search technology?

At Velou, we’ve designed our algorithms to fit our customers’ needs. Our search understands each of their inventories and how they label their products. Then, our AI models dramatically build upon the details of each and every item in our customer’s catalog by diving deep into their products and labeling each feature through our Hyper-tagging Engine, which is a data enrichment process.  


Retailers can benefit by knowing that our search engine isn’t going to leave their products behind. We display all available products as well as similar products for their customers in the size(s) they are looking for. It's incredible. Offering like products increases sales and ultimately makes the customer feel confident that they looked at all available options and that the retailer was really on top of their web store. Have you ever gone to a store and typed in a floral maxi dress and gotten the completely wrong item? It's a turn off.


How does the technology you’ve worked with change a stylist’s job and how do you see it change the experience of fashion in a retail setting? Where do you see the retail industry headed with the incorporation of technology such as AI?

Sales associates are often the ones to assist customers in finding different products, like a similar option, when the retailer doesn’t have a size in stock. Technology will do this automatically for online stores. It can ensure products are discoverable and offer all the matching options available. All this is the bulk of a stylist’s job and using tech to present products in an orderly fashion (no pun intended!) saves time and makes for a fulfilling shopping experience.


Retailers are seeing an increase in online sales. Keeping their online customers happy is crucial to a retailer's success. Customers want to find products...and fast. Technology will enable customers to access stock in real time and provide retailers with real-time feedback on the most searched-for items. Velou alerts our retailers to adjust product inventory based on demand so that they can keep stores stocked with the right products and the right merchandise that keeps the customer coming back.


What are you excited to work on next and what exciting solutions can we expect to see from Velou?

I’m excited to work on predictive styling suggestions with the Velou team. Our product is already able to recognize the garment and understand its occasion. We can then provide options that would be appropriate through the use of hyper tagging. Developing a new solution to give shoppers outfit suggestions based on our retail customer’s stock is a game changer. When it comes down to it, everyone wants a well-styled, personalized look. Our looks will be created through algorithms and by thoroughly understanding the end customer. Exploring outfit suggestions through the use of AI enables shoppers to visualize the outfit, which is really exciting.


Tricia Lahren's Bio: Tricia is the Fashion Intelligence Director for Velou. She has been working in fashion for two decades, from sales at Benetton and Nordstrom to dressing for New York Fashion Week and designing for sportswear brands. She received a B.S. in Merchandise Management and an A.A.S. in Fashion Buying and Merchandising from the Fashion Institute of Technology. Her interest in “styling” came about from exposure to Vogue Magazine and assisting established stylists. Her clients range from ready-to-wear to luxury retailers, such as Baby Gap, Neiman Marcus, Pottery Barn, Lord & Taylor, and Levi Strauss. Prior to Velou, she worked with Tailor App, an in-house incubator of Area 120 by Google.

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