Based on averages
Most sizing systems assume everyone fits a model.
In reality, every shopper and every SKU is different.
Precision sizing that boosts conversion and cuts returns
The Nordic gold standard of sizing — now available to all.
Zizr gives each shopper a personal, precise size recommendation — at the SKU level.
It works without asking for weight or photos, and adjusts across styles, categories, and even between items from the same brand.
Fast to launch. Easy to integrate. Proven in both luxury and lifestyle.
Live within hours, no development required.
From Shopify stores to global fashion leaders — Zizr powers better sizing for all.
Trusted across fashion — from Nordic leaders to global luxury retailers
Zizr isn’t new. It’s the sizing layer behind some of the most respected fashion retailers in the Nordics and now being adopted by global players.
Our infrastructure has been live for years, powering millions of personalized size recommendations at the model level.
Because yes, your customers often need different sizes for jeans or shoes, even within the same brand.
From fast-moving Shopify brands to iconic high-end stores, Zizr adapts to your platform, your products, and your pace.
The Gold Standard of Sizing
AI-driven precision sizing — engineered and developed in the Nordics, trusted worldwide.
Learn how leading fashion stores create personalized fit experiences that increase conversion and reduce returns — without asking for weight, photos, or any personal details customers don’t want to share.
Why sizing fails today
The fashion industry still sizes for averages — not for individuals.
Conventional tools rely on generic data, static charts, or customer guesses.
That’s why even great products get returned for “fit issues” that could have been avoided
Conventional tools rely on generic data, static charts, or customer guesses.
That’s why even great products get returned for “fit issues” that could have been avoided
Intrusive or inconvenient
Tools that ask for body measurements, photos, or weight data create friction — and most customers drop off before finishing.
Stuck in isolation
Each retailer relies only on their own limited data — so insights stay small and improvements stay local.
Without shared learning from real transactions across stores and brands, sizing accuracy never truly evolves.
Meet Zizr — The Gold Standard of Sizing
Zizr delivers personalized, SKU-level size recommendations powered by real shopping behavior — not assumptions.
We learn from what actually fits across brands, styles, and seasons, giving every shopper a perfect fit without asking for weight, photos, or private details.
Individual, not average. Every shopper is unique. Zizr matches real people to real products with SKU-level precision.
Privacy-first design. No intrusive questions or scans. Just insights from real-world transactions matched with personal favourites.
Continuous learning. Each recommendation makes the next one smarter. Across categories, brands, and regions.
Zizr makes personalized sizing effortless
Zizr makes personalised sizing effortless.
If a shopper has bought before, they get instant recommendations.
If they’re new, they just tell Zizr what they already wear, how they like it, and Zizr does the rest automatically.
Instant sizing for your customers
When a store uses Zizr, existing customers automatically receive personalized size recommendations based on what they’ve previously bought and how those items fit.
Each new purchase fine-tunes the next recommendation, creating a perfect fit history that travels with the shopper inside your store.
No setup, no login, and no guessing. Just accurate sizing from the very first click — straight out of the box.
Personalized fit from the first visit
New to Zizr? They can chat right on the product page — for example:
“I have Levi’s 511, size 26/30.
Fits well, but a bit tight at the hips."
From that short input, Zizr identifies the exact model and SKU, maps it to verified fit data from real purchases, and translates that context into a perfect recommendation for the new product — even if it’s from another brand or category.
Every response is based on item-level data, not averages or size charts.
Always accurate - from FitBack
Behind the scenes, Zizr continuously validates its recommendations through FitBack — real, feedback from shoppers about how items fit.
Each transaction updates how that specific SKU fits in practice, not just how it measures on a model at photoshoot.
As new products enter the catalog, Zizr compares them against this growing network of verified fits to fine-tune recommendations for every shopper.
The result: accuracy that keeps improving automatically — across styles, brands, and seasons — without ever collecting personal or sensitive data.
How Zizr looks for your customers
What real impact looks like
You’ve seen it before from other sizing tools: “30 % fewer returns,” “20 % higher conversion.”
Those are just averages pulled from a mix of stores, seasons, and categories.
Zizr doesn’t do averages. We measure and show what actually happens.
In real stores — product by product, category by category, week by week.
Because every product behaves differently — and so do the people who buy them.
A hoodie doesn’t carry the same sizing risk as a pair of jeans, and a summer dress doesn’t fit the same way in London as it does in Seoul.
That’s why Zizr tracks real outcomes, not assumptions — revealing the true effect of better sizing where it actually happens.
Real performance, not marketing math.
Proven performance in live fashion retail
When Capone, a Nordic multi-brand retailer, implemented Zizr, we tracked every transaction in real time — product by product, week by week.
No test panels, no cherry-picked results. Just what actually happened across live shoppers and categories.
What we saw:
– A clear drop in size-related returns, first in denim and footwear, the toughest categories to get right.
– Customers started trusting recommendations earlier, leading to fewer multiple-size baskets.
– Repeat customers were twice as likely to buy again within 60 days.
That’s not marketing math, it’s what real-world sizing accuracy looks like.
Get the full story, with all the data and context, in the Capone Case Study.
