Map your product data to any channel’s taxonomy automatically

Both are about matching your own product values to a required external structure, but they serve different purposes.

Taxonomy mapping matches your product values to the category structure a channel requires. For example, mapping "Running Shoes" to Google's "Apparel & Accessories > Shoes," or to the category tree a marketplace displays products under.

Classification mapping is used with Category Specific Attributes (CSA) on marketplaces like Amazon, so instead of just placing a product in a category, the mapped value triggers the correct set of required attributes for that product type inside the platform.

In short, taxonomy mapping decides where a product is categorized, while classification mapping decides which attribute rules apply to it. Smart Mapping supports both, using the same underlying methods (exact, dictionary, semantic, and AI matching).

Smart Mapping is a Productsup feature that automates taxonomy and classification mapping. It suggests the right target value for each of your product values, shows a confidence score for every suggestion, and lets you review and apply matches in bulk instead of assigning them one by one.

Smart Mapping can map your internal product categories directly to the Google Merchant Center / Google Shopping taxonomy. It suggests a match for each of your category values with a confidence score, so you can review and apply mappings across your whole catalog at once instead of manually assigning each one.

For marketplaces like Amazon that use Category Specific Attributes (CSA), Smart Mapping suggests the correct classification trigger for each product value and applies it in bulk, which is typically the slowest manual step when onboarding a new marketplace.

Yes, Smart Mapping can map source values in one language directly to a target market's taxonomy in another. For example, German product terms to the taxonomy required by Amazon Spain without a separate manual translation step first.

Smart Mapping offers two methods: a) Smart (automatic exact, dictionary, and semantic matching) and b) AI suggestions. The ‘Smart’ method works on its own, while ‘AI suggestions’ are optional and are used for values that ‘Smart’ can't resolve, or whenever you choose to include them.

Every suggestion comes with a confidence score, and you choose the minimum confidence level you're willing to review. Nothing is applied automatically, so you approve each mapping before it takes effect. Accuracy is ultimately in your hands, not the algorithm's.

The Dictionary is a shared database of mappings you've previously approved. It's checked automatically for future lists, new channels, and updated taxonomy versions, so recurring setups and standard updates become a quick review instead of starting from scratch.

Yes, Smart Mapping can map product data to industrial classification standards, such as ETIM and eCl@ss, and reuses previously approved mappings from the Smart Mapping Dictionary when a standard releases a new version.

No, Smart Mapping only shows suggestions for unmapped values, so anything you've already mapped is left untouched unless you choose to reset and remap it.

Manually mapping a list of a few thousand unique values can take days. With Smart Mapping, reviewing and applying suggestions for the same list typically takes minutes, as you're approving matches in bulk rather than picking each one individually.