Shoptrue Unveils Fashion Playlists: Changing Shopping, Social Media

Shoptrue Unveils Fashion Playlists: Transforming Shopping and Social Media Amid Rapid Expansion

As AI continues to quake the fashion apparel industry from generative imagery to auto-generated product detail descriptions, a start up called Shoptrue is taking a unique approach that combines AI-driven personal recommendations with taste-driven shopping. This process, which blends human fashion authority and machine-driven results, allows Shoptrue to be a first-of-its-kind fashion marketplace where users can discover and purchase styles from thousands of brands in a single destination through a highly personalized shopping experience, giving each shopper her own one stop personal shop curated to each person’s style, brands, fit, and size. Shoptrue’s approach is resonating with shoppers.  In early ad testing on Meta, about 40% of all traffic is converting into new registered users.   

And the brand continues to evolve. The recent launch of their innovative feature, Fashion Playlists, combines the power of AI-driven personal recommendations with the individual’s unique taste and style preferences. “We wanted to take ecommerce from a sIngle player game to a multiplayer game,” says founder Romney Evans. He likens the feature to Spotify where anyone can be the DJ. “Fashion Playlists allows any shopper to be a fashion  editor,” he said.  This means that a shopper can favorite, organize and share her Fashion Playlist with her network enabling them to shop or be inspired from her edit. “This is a huge move in ecommerce,” says Brandon Holley, Chief Fashion Officer. “Online fashion has been idling in a mode where brands, celebrities and giant influencers define taste. While this feature has the potential to supercharge celebrity and influencer sourced fashion inspiration, for the first time we are allowing any user to be the creator and curator of the ecommerce experience.”  With Fashion Playlists Shoptrue is aiming to put shoppers in the driver’s seat of their own personal shops, using AI to make the discovery process even more efficient. The creator’s network will be able to  shop, favorite, follow and save Playlists.  

Example of a user made Fashion Playlist on

Creating a Fashion Playlist on Shoptrue is a simple and intuitive process.  I tried it out while writing this story.  It’s pretty cool. I visited, and was presented with a wide range of clothing options from various brands, styles, and price points. As I explored the marketplace, I was able to  add items to my own  Fashion Playlists that I created and named with a single click, curating a collection that resonates with my style sensibilities. The more a user engages with the platform, liking items that catch her eye along the way, the better the AI algorithms understand her preferences, ultimately leading to more relevant recommendations over time. It’s like Tinder for clothes and shoes, matchmaking me to prospective clothing crushes with every new page load.  Users can curate playlists for different occasions, moods, or fashion themes–I created my own Fashion Playlists  for  “casual weekend getaway”, “work wardrobe”, and  “night out”, which admittedly is more aspirational than practical at this point.  

In an age where the attention is shifting from celebrity influencers to smaller, more authentic social media personalities, Fashion Playlists offer an escape from the mega-influencer domination and allow for smaller, more intimate shopping experiences. 

In addition to the new Fashion Playlist feature, Shoptrue has made  significant momentum and continues to innovate: going from 2,000 brands on its platform in January to 10,000 with over 600,000 unique styles. The large scope of product offering is intentional, and gives Shoptrue the ability to curate a relevant subset of products to every shopper’s style, brands, fit, and size. For instance, a value shopper might get recommended items from Target, PacSun, Gap, or Loft.  A premium shopper might see items from Rag and Bone, Banana Republic, or Frame Denim.  Luxury shoppers might see suggestions from Burberry, Gucci, or Fendi. The catalog spans everything from Lane Bryant, to Prada, Dick’s Sporting Goods, Nike, Saks, SSENSE, Athleta, Levi’s, North Face and Free People.   

Going forward, Shoptrue is also addressing common vexing problems faced by most marketplaces. One annoying issue in particular is inventory sell-outs, an industry-wide problem. Mirakl, a $3B marketplace software platform used by major retailers like Macy’s and BestBuy recently published that 55% of marketplace products have stockout issues. “It’s frustrating as a shopper to find something you like only to find out it’s not available in your size,” says Evans. “To fix this, we built a data-driven personalized size filter that automatically filters out items not available in your recommended size, funneling users to relevant items they’ll love.” 

Though still in its early stage, Shoptrue is innovating ecommerce from the top down starting with the consumer UX of its Fashion Playlists to solving inventory problems on the backend that plague even the biggest players. Its unique combination of AI and authority-driven recommendations are the core that ties all the pieces together, a dynamic approach that allows users a way to shop for fashion that combines AI with individual taste and style preferences.  

If you’re like me, you can’t afford to buy every dress or pair of shoes that catches your eye.  What I love about Shoptrue’s Fashion Playlists is that it gives shoppers the opportunity to collect, save, and organize their fashion discoveries while shopping.  For some just having the tools to express one’s style POV might be the main attraction. For others, maybe the appeal of having a kind of sandbox for mixing and matching, or comparing items before narrowing selections to purchase might be the main appeal. 

Visit to try it out yourself and create your own Fashion Playlists. 

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