Add Sizebay size recommendations and virtual try-on to your BigCommerce store to improve fit confidence on PDPs, reduce return risk, and collect product-level sizing data.
• Product identifiers (SKU, product ID, variant attributes) are mapped between BigCommerce and Sizebay to keep recommendations aligned to the correct PDP and variant.
• Size charts and size rules are associated to products, categories, or attributes, with option values (EU/US/UK sizes, width, inseam, and fit notes) mapped to Sizebay’s sizing model.
• Catalog syncs transfer new and updated products, variants, and option changes; delta updates send only changed records to reduce reprocessing.
• A storefront widget renders on BigCommerce PDP templates and calls Sizebay services at runtime to return size guidance and virtual try-on outputs based on shopper inputs.
• Event payloads (views, interactions, and recommendation outcomes) are captured and attributed to product and variant context for reporting and model tuning.
• Sync errors and schema mismatches are logged with record-level details, and retries handle transient API failures to keep catalog and sizing data consistent.
.png)
We install and configure the Sizebay widget on BigCommerce PDP templates, then map products, variants, and attributes so shoppers see the right fit guidance per SKU.
Typically you’ll need clean variant structure plus size, category, and key fit attributes; we validate and normalize the catalog so Sizebay can generate consistent recommendations.
Yes, Sizebay can be configured per storefront, language, and sizing system, and we align the configuration to your BigCommerce multi-store and localization setup.
Fit guidance on the PDP reduces “wrong size” purchases and hesitation, which usually improves add-to-cart rates while lowering return risk tied to sizing uncertainty.
Most implementations take a few weeks depending on catalog complexity; scandiweb handles data mapping, frontend placement, QA, and tracking so you can measure impact.










