
Anya Cheng - Taelor
About the Guest Anya Cheng is the founder and CEO of Taelor, a Silicon Valley–based men’s clothing rental service that pairs professional stylists with AI and turns customer feedback into insight for fashion brands. Before co-founding Taelor with Phoebe Tan, Anya spent around 15 years building digital products for some of the world’s largest consumer companies. At Meta she helped build Facebook and Instagram Shopping. At eBay she was head of product, launching new businesses across the US, Latin America, Africa and Asia. As head of product at Target she helped open its Silicon Valley tech office, and as a senior director at McDonald’s she was in charge of everything digital, from in-store ordering kiosks and digital menu boards to the drive-thru, the mobile app and food delivery. Originally from Taiwan, Anya has grown Taelor to more than 100 brand partners, partnerships with the New York Yankees and Coffee Meets Bagel, and recognition in Inc.’s 2025 Best in Business awards. Episode Summary What if the most valuable thing a clothing company could collect wasn’t the sale at the till, but what happens after you get dressed? That question sits at the centre of Taelor. In this episode of Shape the System, host Vincent Turner talks with founder and CEO Anya Cheng about a men’s clothing rental service that doubles as a data engine for the fashion industry, and why the two halves of the business make each other stronger. Anya’s starting point was personal. Leading large teams at Meta, and feeling like an imposter, she wanted to dress in a way that projected confidence. She had no interest in fashion itself. Subscription boxes required her to buy from every shipment, and rental sites asked her to scroll through tens of thousands of garments. That led to her realisation: most fashion companies are designed for people who love fashion, not for people who simply want to be ready for their day. The consumer offer is simple. For around US$100 a month, members receive six garments chosen by AI and professional stylists. They wear them, send them back without washing them, and receive the next lot, so there’s no shopping and no laundry. What members give back is feedback, and because Taelor knows who they are and where they wore each outfit, that feedback comes with context. It might be a founder heading to a conference, a Boston lawyer on a date night, or a man whose size medium now sits an inch short at the belly. That context is the gap Anya sees in today’s AI. Models know what people review, click and buy online, but almost nothing about what happens in the physical world once the parcel arrives. The fashion industry badly needs that knowledge. By Anya’s figures, around 40% of most brands’ inventory goes unsold. That’s roughly US$300 billion of stock in a US$1.8 trillion market, in an industry she says accounts for around 10% of global carbon emissions. The main cause is that brands forecast next year’s demand from last year’s sales. Taelor’s feedback is specific enough to act on: the second button falls off after five washes, or the fabric doesn’t stretch enough for bigger, active American customers. Anya contrasts that with the one-star “too big” reviews she saw as head of product at Target, which never said which size, which body shape or after how many washes. She says brands using Taelor’s data have seen sell-through improve by around 20%. The brand stories show how this works in practice. A Los Angeles label that had only ever sold through wholesale found out which hoodie fabric was its real hit, and began using it across its range. FINE, a Taiwanese manufacturer that produces for global athletic brands, launched its own label in the US. It learned that its single-material, easily recyclable fabric wasn’t stretchy enough for the market, and it changed course. Dutch brand R2 Amsterdam faced new European rules against destroying unsold stock, so it used Taelor to rent that inventory to American customers and test a new market at the same time. Many of these suppliers have since become customers of Taelor’s AI agent, which lets them query benchmark data across brands without needing an engineer. Vincent draws out a theme that runs through the whole conversation: the gap between what the customer is buying and what the system achieves. Taelor’s members aren’t paying for sustainability. They want to close the deal, win the job or land the second date. One member wore a dolphin-print shirt to a conference and found it opened conversations. Another reluctantly wore a blazer to dinner, and it ended up around his date’s shoulders on a chilly walk home. Anya describes Taelor as the gadget guy behind the superhero. Yet the model quietly delivers environmental outcomes. Like an airport rental car fleet, garments are sold before they wear out, on average after about three rentals and at around 50% off, through dynamic pricing. Inc. highlighted exactly this when recognising Taelor: it had brought secondhand clothing to busy men who would never set foot in a thrift store. Brands are paid through revenue share, so a durable garment keeps earning. At the end of its life, a piece goes to resale, repurposing and recycling partners. Looking ahead, Anya sees Taelor as a one-stop shop on both sides. For members, that means proactive AI that connects to a calendar and prepares the week ahead, plus expansion into shoes, accessories and gifting. For brands, it means a full product journey. AI helps decide what to make, small sample runs are rented to real customers for feedback within two weeks before mass production, and the platform provides a home for whatever doesn’t sell. She’s also in talks with AI labs that need proprietary real-world data, and believes the data business could one day match the consumer business at much higher margins. She points to Nuuly, Urban Outfitters’ women’s rental service, as proof the consumer model can scale profitably. The episode closes on the human side of the work. Anya describes a US government official posted in Southeast Asia who always rents for the opposite season, a father dressing to win custody of his two children, and a customer with cancer who says a new outfit makes him feel alive. Against those stories sits the relentless pace of Silicon Valley, and Anya’s way of coping with it: swapping “I should” for “I would like to.” That small shift, she says, is how she ended up partnering with the New York Yankees and Coffee Meets Bagel. Key Takeaways Forecasting from last year’s sales is a structural flaw. Most fashion brands predict demand from historical sales. Anya says that leaves around 40% of inventory unsold, roughly US$300 billion worth, because last year’s bestseller tends to become next year’s markdown. Rental captures data that retail never sees. Taelor knows each member’s body shape, occupation and occasion, and how many times each garment has been washed. That makes its feedback precise enough for brands to act on, and Anya says it has lifted brands’ sell-through by around 20%. Lead with the outcome the customer actually wants. Members are paying to close deals, land jobs and get second dates, not to reduce waste. The environmental benefits are real, but they ride on a proposition built around confidence and convenience. Rental can be a gateway to secondhand. Like a rental car fleet, garments are typically sold before they show wear, on average after about three rentals and at around 50% off. That gives busy men a route into pre-owned clothing without visiting a thrift store. Unsold stock becomes an asset, and so does the data. Through revenue share, brands earn back their wholesale price, and often more from durable pieces, while gaining exposure and feedback. They can also test small sample runs with real customers before committing to mass production. AI labs are now interested in the same physical-world data. Notable Quotes “Last year’s bestseller is pretty much next year’s markdowns. So using historical sales numbers is a horrible idea, but that’s what the $1.8 trillion market is still doing today.” — Anya Cheng “AI knows what people review, click and buy on the internet, but it knows nothing about the physical world.” — Anya Cheng “We can tell the manufacturers and the brands: after your clothes are washed five times, the second button falls off. That’s very actionable insight.” — Anya Cheng “We are not really selling clothes. We are selling the chance to succeed. We are selling peace of mind.” — Anya Cheng “The more you say ‘I should’, the more you are blaming yourself. Now I say, ‘I would like to.’” — Anya Cheng Resources Experience effortless style with rental and personal styling services: Taelor: Get 10 DAYS FREE TRIAL your first month of men's clothing subscription. Use code: ANYAFREE10 Sign up at: https://taelor.style/pages/membership - pick monthly plan Give the gift of time, convenience, and effortless style: Taelor Gift Cards: Get 15% OFF Use code: PODCASTGIFT Purchase at: https://taelor.style/products/menswear-rental-gift-card Shape the System is an independent podcast with support from KPMG High Growth Ventures More about KPMG High Growth Ventures Scale up for success. We’re here for that. We navigate founders and their teams to the services they need to reach their next milestone. From startup to scale and beyond. No matter where you are right now, we’ll get you the help you need to drive your business forward. We help founders fully realise their potential, as well as the potential of their team and their business, by connecting them to the expertise, skills and resources they need at every stage of their growth journey. Our extensive experience in partnering with evolving businesses means that we can provide you with tailored support as well as independent and practical insights. Whether you are looking to refine your strategy, establish your operations, prepare for a capital raise, expand abroad or simply comply with regulatory requirements, we are here to help. Links: Website: About (highgrowthventures.com.au) LinkedIn: https://www.linkedin.com/showcase/kpmg-enterprise-high-growth-ventures/ Contacts: highgrowthventures@kpmg.com.au










