Interview: How Fashion E-Tailer And Recommendation Platform Suggesty Is Enabling Next-Generation International Commerce
Using a hybrid strategy of human-driven and AI curation, Suggesty offers global customers access to lesser-known international designers while enabling lower-than-market prices and premium quality
Ecommerce changed the fashion retail industry in many ways, but efficiency was perhaps the greatest outcome: Instead of browsing rack after rack, shoppers can refine their search with an endless array of filters all on one centralized platform. Ideally, this should cut shopping time in half. Yet as of 2018, 80% of apparel and shoe purchases were occurring in traditional brick-and-mortar stores. One possible explanation for this paradox is the lack of human element on the internet; consumers still crave the personalized attention and style advice from in-store assistance.
Enter Suggesty, an online fashion retailer and recommendation platform. Using a human-driven and AI-assisted strategy, Suggesty evaluates customers' individual information and provides tailored selections based on that data. The Korea-based website and mobile app analyzes consumer preference, physical appearance and geographical location, and curates its corresponding recommendations from an extensive list of international designer brands. PSFK caught up with founder Sangwoo Kang to learn more about the virtual stylist platform, and how the ecommerce industry can benefit from a human-oriented approach:
PSFK: Could you describe some of the trends that you're seeing in retail today?
Sangwoo: I have the fortunate chance to compare the retail spaces in Korea, in Asia and in the U.S. There's definitely a temperature change and the market spaces are very different.
For example, the space I'm in, which is the fashion ecommerce sector in Korea and Asia, is huge compared to what it was a decade ago. We are probably almost at the saturation point. However, In the U.S., fashion ecommerce has been growing in double digits year after year for the last 10 years. We still think the market is somewhat premature. That's the biggest difference between the two. We can see that with major U.S. department stores across the country. They're closing down and focusing more online.
The second trend that I see with fashion ecommerce in the U.S. is that the customers are still more hesitant to make online purchases for more than $200. However, in Asia, consumers are more used to having a higher-priced digital transaction.
I think consumers need more time to adjust to a new way of shopping, and they're used to finding only cheap items online versus high-quality and proper designer items. That's the major difference.
Could you explain what led you to found Suggesty and what got you noticed in the U.S. marketplace?
In the U.S., the fashion retail supply chain was owned by all the major brands. They dictated what was designed, what was supplied, what was produced, where it was sent and how much it cost.
They owned the real estate in department stores. They dictated the entire industry. But in Asia, especially in Korea, the big brands never really had a hold on the entire market. It was always about grassroots brands, personal designers. It was never about big vertical brands owning the entire supply chain. It was more about small brands and retailers just selling their own merchandise in these little markets. That was a huge portion of the industry.
Due to that climate, individuals were used to buying clothes and selling online. That's why the ecommerce in Asia started really early on and started with small businesses. There were so many of them, which saturated the market.
In the U.S., it was totally different: It was giant brands. They were very slow to adapt. That's why I believe ecommerce in U.S. was slightly slower for the fashion business. That's where Suggesty came in.
I got my first idea for Suggesty three years ago when I was working in New York. I decided I needed some new clothes—I'm one of the worst dressers out there. I went online with the intent to buy and the money, but I just didn't know how to search.
I didn't know what to choose. I was basically paralyzed. That's when I thought, the way we search for fashion items online should change.
It can't be the way Amazon enabled us to buy books 20 years ago—we don't buy clothes like we buy books. It should be different. I thought the search engine should be human‑oriented versus product‑oriented.
Could you explain what you mean by saying Suggesty's recommendation platform is more human‑oriented?
Let me give an example. When you enter “blue shirt” into a search engine, you would get maybe 2,000 results. Those 2,000 hits have nothing to do with you. It's just shirts that are blue. It doesn't care what kind of body shape you have. It doesn't care what kind of skin tone you have.
The fact that you're searching for “blue shirts” means you're already brainwashed to this product‑oriented search. The fact is, in fashion, you shouldn't search for “blue shirt.” In fashion, you should search, “You know who I am. I'm going clubbing this Friday night with my friends in SoHo. Tell me what to wear.” Accordingly, Suggesty quickly analyzes your style, your wants and needs through a very Tinder‑esque style profiling.
Do your consumers input their sizes and age or other criteria, or is the curation based on their aesthetic preferences?
We try not to judge our customers based on their age. We do count some of their factors like that, especially the region—customers from the East Coast are vastly different from those on the West Coast.
I think that's one of the things that Amazon is doing wrong in the fashion industry. They're very good at customer clustering. That's why they're number one in the ecommerce market. They own 56% of the market, but they only own 7% of the fashion market. They try to stereotype a customer into a certain group, which is correct most of the time. But when it comes to fashion, it has to be unique. That is why our approach is treating customers as uniquely as possible.
Every customer in our service receives a tailored collection, as opposed to suggestions like “a customer who bought this blouse also bought these jeans.” We never do that.
How are the recommendations generated? Is it driven by AI or is there a human element with associates pulling some of the looks?
We did experiment with AI, but at the end of the day, AI and fashion don't go together. There is a big human element in it. Every item on our platform is indexed and categorized. It's given a certain number of fashion points for various aspects by our fashion analysts.
It's AI‑assisted. The AI that we developed guesses what kind of clothing an item is and what it should be used for based on its color, size, type, etc. It does the basic categorization like that, but the final approval is done by a human. That is why we can't do 50,000 different kinds of clothes. We are very focused on international designer brands. We only have roughly 8,000 items on our site, only very high quality.
Could you describe your curation process and how you decide which designers and items to carry?
This relates back to the current U.S. market situation. The fashion industry here is polarized. Everyone in the middle has died out. They couldn't keep up with the cost or they couldn't keep up with the designs. That's where our international designer brands come in. The design quality is comparable to the high‑end brands in the U.S, but on the price side, we are comparable to smaller brands. We are slightly more expensive than they are, at about 15% more. However, the quality is definitely comparable to the high‑end brands, which creates this niche market that works for us.
And because they're Asian designers, the product is cheaper—design cost in Asia is cheaper than in the U.S. or Europe.
How do you incorporate data and consumer feedback in order to improve the offerings that you carry?
We do the same basic analysis that everyone else does—who clicked on what, who bought what. My background is big data analysis in the online advertisement industry. I'm very familiar with how to track and analyze big data. What we actually do is analyze trends, and we give them back to the designers for them to prepare for the next season. It's more of a feedback loop to help designers understand U.S. customers.
How do you handle the delivery and returns process and make that as seamless as possible given that it's international?
As I'm sure you know, delivery & logistics is the nightmare of ecommerce, especially with fashion because it has such a high return rate. So far, we have seen surprisingly low return rates. We believe that's to do with our recommendation and curation support.
As far as timing and shipping, we have the time zones to our advantage: We're about 16 hours ahead. When we go to work, we've got all the orders ready for us. At that point, we're basically about one business day ahead. Since our items are all somewhere between $80 to $250, we use expedited shipment. Customers are fine with that.
If a customer is buying a $20 item and the shipping cost is $15, it doesn't make sense. If they're buying a $200 coat with another $100 bag, then $15-shipping costs start to make sense. I think that's one of the reasons customers are happy with our shipment method.
Do you have plans to expand to other markets besides your current ones?
Currently, we're open in the U.S., Canada, U.K., France, Hong Kong and Singapore. Hopefully by end of the year, we'll be open in China. Those six countries that we're currently open in are chosen because of the language barrier and credit card issues and international tax or tariffs issues.
Because we're an online platform, we're very flexible. As long as they accept credit cards and we can ship to them, we are very easy to open to new markets.
Will you offer designers from other markets besides Korea?
We already do. We're already carrying a couple of the U.S. designers that we knew. We are working on what we call a consignment business model, which basically means we don't pre‑buy, or we don't buy from the designers and sell it to the customers. We do it like a spot resale: Basically, when a customer orders something, we give that information to these brands, and then they will send the item to us. Then, we will ship the item to the customer.
This kind of business model is very familiar in Korean markets, but U.S. designers are not used to this. It will take some time to get used to, but hopefully when people are more used to this kind of consignment model, we should be able to expand to other markets, especially if it's a designer.
Finally, what are your plans for the next, say, three to five years? How do you hope to grow and expand?
Our immediate future goal is to attend New York Fashion Week. Hopefully the coming September one or the one after that. We want to make our debut as a unique platform that introduces obscure international brands that shipping may change the circulation of globally.
On the fashion side, we are the pioneers. We discover new brands. On the customer side, we provide professional‑level curation service. That's the position we want to take in the fashion world.
Suggesty is riding the wave of next-generation ecommerce, combining the best of AI and human input to enable lower-cost, curated premium apparel retail for a global market. For more from similar inspiring retailers, see PSFK's reports and newsletters.