One who knows their taste from the very first visit, remembers them every time they return, and guides them to what they'll actually buy.
Every shopper you pay to acquire sees the same generic store. Is that really the best first impression you've got?
Your best customer has shopped with you a dozen times. Do you know their taste, or are they still just shopper4471@gmail.com?
What if your best customers came back because the store knows them, not because you paid to chase them down again?
A good salesperson would never treat a regular like a stranger. Your store does it every day.
You can't make acquisition cheaper. You can make sure that once a shopper arrives, someone who knows them is there to help them buy.
Every visit is the shopper telling you who they are: what they chose, what they skipped, what they came back for. A good salesperson reads those cues in the moment and acts on them. Most stores file the same signals away in analytics and marketing segments, used later, in isolation, long after the shopper has gone. We put them to work in real time, compounding visit over visit, so the store knows the shopper while they're still standing in it.
Anyone can tag a shopper by what they buy. Real taste is the specifics, and the things they'd never touch. That's the difference between a guess and a fit.
Not another popup or discount engine. A store that reads who each shopper is and gets sharper the more they visit, the way the best salesperson on your floor would.
A brand-new visitor with no history still gives off cues: where they came from, device, time, intent. We read them and make the first visit feel like the fifth. No generic store for everyone.
Clicks, skips, dwell, purchases, returns: each visit teaches the store more, the way a salesperson remembers a regular. The experience sharpens instead of resetting to zero.
Not "likes apparel," but the real, specific read your best salesperson would have: cut, material, price, what they'd never buy. Enough to guide them straight to the right thing.
Easier to show than to tell. Watch it read a shopper and style the store around them, in real time.
See it style a shopper →When the store already knows each shopper, its AI assistant inherits all of it: their taste, their history, what they'd never buy. It stops guessing and starts advising, the way a salesperson who knows you would.
The best salesperson you ever had knew every regular by name. We're rebuilding that, run by people who have spent two decades on exactly this problem.
Founder Aviral Gupta has spent 20+ years on both sides of this problem. At Amazon he ran real retail businesses: a $100M apparel P&L, fashion across Japan, the #1 national baby brand and Amazon's first private label, plus retail operations across the US, Australia, and India. He knows firsthand what it takes to run a store and win a customer.
Then he built the answer. At Fetch he ran the commerce and discovery surfaces serving 18M monthly users, roughly 60% of company revenue, and is lead inventor on the patented personalization system behind ~360M monthly interactions. At Trashie he led taste-driven recommendation, turning customer signal into personalized discovery. Earlier, product strategy and operations leadership at LinkedIn.
On the data and ML side, ForYouLabs is advised by Raj Prazad, former SVP of Data at Fetch, who brings the modeling and infrastructure depth that turns shopper signal into a store that knows them.
This isn't a bet on a new idea. It's the next version of work that's already shipped at scale.
We're working with a small number of pilot partners to prove it out on a real store. A short call to see if yours is a fit. No deck, no pressure.