Fashion shoppers browse ten items and buy one. The agent knows which one.
Sizes, seasons and taste change from one shopper to the next. The agent learns each visitor from the first click and sells to that person on the site, in chat and by email.
- Search that suggests from the first keystroke, ranked per shopper
- Follow-ups that pick the products, not a template
- Runs next to Klaviyo on Shopify, live the same day
Size and season decide the sale.
A fashion visitor rarely buys the first item she sees. She compares, checks the size, leaves, and comes back when something fits. Most tools see only the shoppers who sign up; the agent starts with the first visit and keeps the size, the brands and the price range she looks at.
When she returns, the search, the product page and the email all show her size and her taste. When the item she viewed is back in stock, she hears about it first.
The agent ranks search and recommendations by the sizes a shopper looks at, so out-of-size items do not win the page. New arrivals reach the shoppers who bought that category last season, in the order the data says they will buy. And a chat that answers fit and material questions before the order cuts the returns that follow a guess.
What the agent did in stores like yours
Each result comes from one store, with its period and method on the page.
Nine times the revenue on the same email flow
A womenswear brand moved its abandoned-browse flow from Klaviyo to Releva and added recommendations on its site: 9.4× the revenue on the same flow, 3× the shoppers reached.
Read the case study →Womenswear · Shopify · Meta adsTwice the Meta budget, the same return
Audiences built from each shopper's predicted value held the return within 8% while the daily budget grew 2.1× over 79 days.
Read the case study →Kids' fashion · EU4.9% of visitors, 27.5% of revenue
Search that suggests from the first keystroke: the few who searched bought 4.5× more often and brought 7.2× the revenue per visitor.
Read the case study →Shopify brands on KlaviyoThree times the shoppers on the same email flow
Start with one flow next to Klaviyo and let each email pick its own products.
Read the use case →Four jobs, tuned to fashion
Search by size and style
Suggestions from the first keystroke, ranked for each shopper, with her size first.
Product pages that know her
The picks under the product change with the shopper: what goes with it, in her size and price range.
Follow-ups that choose the products
Abandoned browse, back in stock and new arrivals, each email built for one person.
Audiences by predicted value
Meta and Google audiences built from who will buy again, with existing customers kept out of retargeting.
See which of last week's visitors you missed
Thirty minutes, with your store and ad accounts open. Then 30 days free. A holdout group decides: if the agent doesn't add orders in 30 days, you don't pay.
Book 30 minutes
You'll talk to one of us.