Guidance at the point of choice
The recommendation appears where shoppers are already deciding, so they do not need to leave the product page to compare charts.
How Zizr gives every shopper a better size recommendation
Zizr reads product data, fit signals and shopper context to show a clear recommendation directly on the product page, without asking for weight, body photos or measurements.
The size decision happens on the product page
Zizr improves the moment where the shopper chooses size. The guidance stays close to the item, the size selector and the add-to-cart decision.
Close to the size selector
Zizr keeps the help connected to the actual product and the size options available for that SKU.
Less guessing before add-to-cart
Customers can move from uncertainty to a clearer size choice before hesitation turns into abandonment.
Zizr understands the item first
A good recommendation starts with the product, not an average body. Zizr can account for category, model, cut, fabric and product-specific size behaviour.
Category and model context
A dress, blazer, jeans and shoe can each need different fit logic, even when sold by the same store.
Cut, fabric and silhouette
Recommendations can reflect how an item is built and how that shape changes the size decision.
Different items, different guidance
Two products from the same brand can receive different recommendations when their fit context is different.
Zizr uses fit signals, not intrusive body data
The experience is designed to be useful without asking shoppers for weight, body photos, measuring tape steps or intrusive body questions.
Product and retailer data
Zizr starts with product, catalog and size context from the store.
Purchase and return history where available
Where the store has useful history, those signals can help Zizr understand how items behave in real shopping.
Fit feedback where available
Shopper feedback can help refine future guidance when it is available and appropriate to use.
No weight, photos or measuring tape
Zizr keeps the shopper journey low-friction and privacy-respecting by avoiding unnecessary body data.
How the recommendation flow works
The system is built to make the product-page size decision clearer for shoppers and more useful for stores over time.
Understand the product
Zizr reads item, SKU, category, model, cut, fabric and size behaviour.
Use available fit signals
The recommendation layer can use product data, retailer data, purchase history, return history and feedback where available.
Show guidance on the product page
The recommendation appears near the size selector, where the shopper is making the decision.
Improve over time
As more useful signals become available, guidance can become more helpful for returning shoppers and similar product decisions.
Built for stores, simple for shoppers
Zizr is designed for a practical store rollout and a calm shopper experience.
Shopify is the fastest path
Shopify stores can start through the app path and review how product-page recommendations fit their theme and catalog.
Custom platforms are supported
For other ecommerce stacks, Zizr can review API, storefront and data-flow needs before recommending the right setup.
How it works FAQ
Does Zizr ask for weight or photos?
No. Zizr is designed to avoid weight, body photos, measuring tape steps and intrusive body questions.
Can recommendations differ between products from the same brand?
Yes. Recommendations can vary by item or SKU because category, cut, fabric and size behaviour can differ within the same brand.
What data does Zizr need?
Zizr starts with product and catalog context, then reviews available store signals such as size options, purchase history, return history and fit feedback where those signals exist.
Does Zizr work only on Shopify?
No. Shopify is the fastest route for many stores, but Zizr can also support custom ecommerce platforms through integrations, API or scoped setup.
Do shoppers need to create an account?
No. Zizr is designed to support product-page recommendations without forcing shoppers into an account flow.
How does Zizr improve over time?
Where useful signals are available, feedback from products, purchases, returns and shopper responses can help make future guidance more useful.
How is privacy handled?
Zizr uses a privacy-respecting approach and GDPR-aware implementation practices. The shopper experience avoids weight and body photos.
See how product-level recommendations fit your store
Share your platform, catalog and launch goals. Zizr can help you review the right path.