I’m excited to finally share with you what I’ve been working on for the past year. Today we’re launching Shoptrue, your one stop personal shopTM curated for you and by you.
Shoptrue is the first of its kind ecommerce platform that allows shoppers to explore over 2,000 leading brands in one place, curated to their individual style, brands, fit, and size. Users can find inspiration from stylists, tastemakers and peers, and ultimately build and share their own Shops reflective of their personal style.
Prior to starting Shoptrue, I co-founded True Fit, the industry’s leading fit and size technology, with my co-founders Jessica Murphy and Bill Adler and a really talented team. Together we pioneered a new market for size and fit technology that is now used by over 80 million active users globally across a vast network of the world’s best retailers. I’m so proud of all the work we’ve done together at True Fit, and I’m excited by all the innovation True Fit continues to produce since I left the company to pursue Shoptrue. And now, we leverage True Fit’s software for all of our size and fit-related capabilities. That’s one wheel we won’t be reinventing and nobody does it better!
So after spending the past fifteen years tackling one of fashion ecom’s most vexing challenges—size and fit—I’m now moving upstream in the shopping journey to tackle one of fashion’s biggest opportunities: style discovery and inspiration, where we can be a powerful ally and channel to merchants and brands, and a fun and new shopping experience for consumers.
Shoptrue is a fashion discovery company; the only constantly learning fashion marketplace that combines AI-driven personal recommendations with taste-driven shopping. Shoptrue gives every shopper her own one stop personal shopTM, curated for you and by you; a singular destination where shoppers can explore thousands of leading brands, curated to each shopper’s personal style, brands, fit, and size. It’s a place to find taste-driven style inspiration from stylists, tastemakers, and peers; and ultimately build and share their own shops (collections) reflective of their personal style POV. We have developed powerful insights and unique capabilities to help match people to relevant brands and styles, and change the way the world buys and sells clothes.
And I’m not doing this alone. I’m thrilled to be working with an initial team of about 44 people, including a really talented leadership team which includes Brandon Holley as Chief Fashion Officer, a former Condé Nast veteran and fashion tech entrepreneur. After a celebrated career in publishing, Brandon built Everywear, a software platform dedicated to better style inspiration, which has now been incorporated into Shoptrue. John Lashlee, former Data Scientist for Netflix and LinkedIn, as VP of Data Science. Together, John and Brandon personify the duality of programmatic, data-driven curation (FOR YOU) and the human driven curation, editorial, and shop building (BY YOU) that is core to Shoptrue’s FOR YOU BY YOU position and differentiation in the market.
I’m also grateful to be working alongside other great execs, including Jill Jarvis, VP of Product (former TripAdvisor); Robert Pate, Chief Architect (former Meryll Lynch, True Fit); Kate DeLanders, Sr. Director Marketing (former J.Jill, Reebok); Phil Dubina, VP UX and Creative (former True Fit), Suma Mandagiri, Director India Operations (former Paletly, True Fit), and Nikhil Jain, Director Engineering (former True Fit). See more about us at Shoptrue.com.
We have an awesome group of investors at Signal Peak Ventures, Pelion, and Peterson Ventures. I’m grateful for their belief in what we’re building and for their continued partnership.
Algorithms don’t buy clothes, people do.
We’re trying to harness 3 major strategic forces:
1. Data and personalization as the antidote to the paradox of choice
2. Serendipity and the power of human curation (creators)
3. Network Effects
Shoptrue is grounded in the belief that AI should complement and enhance every part of the fashion discovery process, but not replace it. I think many attempts at AI-driven style recommender systems and the marketing of these systems have been too prescriptive. Too often we as an industry create narratives around all-knowing algorithms that will just know what we want. There are two main problems with this approach:
1. People don’t believe it. This inevitably creates outsized expectations for style recommendations and sets shoppers up for disappointment and failure.
2. Top-down recommendations alone inadvertently take the shopper out of the discovery process.
Data plus personalization is the antidote to the paradox of choice.
Amazon leads the world in product search, when a user already knows what they’re looking for. Yet only 20% of Amazon Prime members choose Amazon first for apparel and footwear. That’s because sometimes we don’t know what we’re going to love until we see it. People are looking to be inspired.
We want to harness personalization to prompt you with higher probability suggestions, but we acknowledge that the serendipity of discovering something new happens entirely in the mind of the shopper. Algorithms don’t buy clothes, people do. E.O. Wilson, the Pulitzer Prize winning Harvard Biologist and writer said, “There’s no greater high than discovery.” We agree. Don’t take the serotonin out of serendipity. That’s the fun part of shopping. Let’s use AI to increase the conditions and probability for serendipity so when it happens, people have the tools to collect and share their inspiration, and create unique new combinations of products in their own collections that they name and that reflect their style POV.
By creating a virtuous cycle between AI-driven product recommendations and human-driven curation, we’re putting the shopper in the driver’s seat of their own shopping experience and putting the “person” back in personalization.
Brandon Holley said it well when she said “We are making it easier for people to find only the things they’re going to love, and then giving them the tools to organize and share their style POV with the world. Anybody’s shop has the potential to set off a chain reaction of fashion inspiration that can surprise and delight you from any direction.”
Network Effects
As we enable shoppers to organize and share their style POV through “shops” or collections they curate for themselves and others, we are building the power of network effects into our business model, and making network effects central to the shopping experience. Even with the proliferation of AI and machine learning, the shopping model for discovery clothes and shoes really hasn’t changed much. It’s largely been a single player. We’re changing shopping from a single player game to a multiplayer game.
Come and join us on this journey!
See November 15, 2022 Official Press Release here
