Size data in Klaviyo
Most apparel flows are size-blind. A shopper looks at a medium, leaves, and gets an email showing the product with no size, or a restock alert for a size they never wanted. The email is technically right and practically useless.
We fix this at the data layer. Shopify sends the variant to Klaviyo on viewed product, added to cart and placed order events. We store the shopper's most frequent size per category on their profile, so a tops size and a jeans size can differ. Every flow and recommendation block reads from that.
Three rules follow from it:
- Recommend only what is in stock in their size. A product they cannot buy is a wasted slot.
- Show fit notes from reviews. "Runs small, size up" from three reviewers does more than a size chart.
- Treat gift orders separately. An order shipped to another address tells you nothing about the buyer's size.
Back in stock by variant
In apparel, the size a shopper wants sells out first. Back in stock is one of the highest-intent flows a fashion brand can run, because the shopper asked for this exact item in this exact size.
Klaviyo's back in stock flow works at the variant level on Shopify. We set it up so the signup form appears on sold-out sizes only, the alert goes out as soon as the variant restocks, and a second touch goes 24 hours later only if the size is still available. When stock is thin, we stagger sends so the first group is not met with "sold out" again.
Exchanges before refunds
The National Retail Federation estimated that consumers would return 19.3% of online purchases in 2025. Apparel carries more than its share, because fit is hard to judge on a screen.
Two places to act:
- Before the order. Measurements in inches, the model's height and size, and fit notes beside the size picker. Most fit returns start as a guess on the product page.
- After the order. A fit-check email two days after delivery, with the exchange link first and the refund option second. When a return is started, the flow offers another size or an item of equal value before the refund. Our post on turning returns into exchanges on Shopify covers the setup.
Drops and campaigns
Fashion runs on newness. The calendar should follow your release cadence, not a fixed number of sends. A drop email goes first to people who bought from the same category, then to engaged subscribers, then to everyone else over 48 hours. That order protects deliverability and puts the most likely buyers in front of limited sizes first.
Between drops, styling content earns its slot: one product worn three ways, or what to wear it with. Discounts are the exception, not the calendar. Klaviyo's own industry data shows how wide the gap is: for clothing and accessories, flows convert at 2.15% placed order rate against 0.12% for campaigns. Flows come first for that reason.
Meta creative for apparel
Apparel ads sell movement and fit. The concepts we test most:
- Try-on across body types, with the size each person is wearing on screen.
- Fabric close-ups, stretch, weight and drape, the things a photo cannot show.
- Outfit builds, one hero piece styled three ways.
- Founder or designer notes on why a piece is cut the way it is.
We judge Meta on cost per new customer and the return rate of the customers it brings in. A campaign that drives orders that come back is not a good campaign. For how we structure tests, see our Meta creative testing framework.
Product page fit signals
- Size guide in inches, one tap from the size picker, not in the footer.
- Model details: height and size worn, for every product photo set.
- Fit summary from reviews: runs small, true to size, or runs large, with the count behind it.
- Exchange terms near the price, stated plainly. Easy exchanges reduce the hesitation that causes bracketing.
Agencies with apparel clients can have us deliver this under their brand: see white-label for agencies. For other categories, see all industries.