product_type Attribute: Your Own Taxonomy for Google Shopping Bidding

What is the product_type attribute?

The product_type attribute allows you to submit your own custom product taxonomy to Google Merchant Center. Unlike google_product_category, which uses Google’s predefined taxonomy, product_type is entirely defined by you — you choose the category names and hierarchy that best reflects your own product organisation. Its primary purpose is enabling granular product segmentation in Google Ads for campaign targeting and bid management.

While product_type is not visible to shoppers and has only a minor role in search matching, it is one of the most operationally important attributes for running well-structured Shopping campaigns. A well-designed product_type taxonomy is the difference between campaigns where you can set smart bids by product category and campaigns where everything is lumped together in an unmanageable product group.

Technical specifications

product_type vs. google_product_category — when to use which

Best practice: submit both attributes for every product. They are complementary, not redundant.

Designing an effective product_type taxonomy

A good product_type taxonomy has the following properties:

• Reflects your business structure — The categories should map to how your merchandising, buying, and marketing teams think about your products. It’s your taxonomy, not Google’s.

• Enables bid differentiation at multiple levels — You should be able to create meaningful bid rules at every level: the top level (broad product area), mid level (product category), and bottom level (specific product type). If all products in a level share the same ROAS, the level isn’t granular enough.

• Stable once established — Changing product_type values disrupts historical Google Ads segmentation and reporting. Design it right the first time, or plan a careful migration that preserves segment history.

• 3–5 levels deep — Shallow (1–2 levels) loses segmentation value; too deep (6+ levels) creates management complexity without proportionate bid benefit.

Where product_type is used

• Google Ads product groups — The primary use case. In Standard Shopping and Performance Max campaigns, you can create product group subdivisions based on product_type. Each level of your hierarchy creates a subdivision option, allowing you to set distinct bids or budgets for each category. For example: bid €0.50 for “Electronics > Cables” but €2.50 for “Electronics > Headphones > Noise Cancelling”.

• Shopping campaign reporting — In Google Ads reports, you can segment performance by product_type to compare ROAS, CTR, and conversion rates across product categories. This identifies your best and worst-performing categories, informing both bidding and inventory decisions.

• Merchant Center product segmentation — GMC’s product performance reports can be segmented by product_type, giving visibility into which category segments drive the most clicks, impressions, and conversions from an organic (free listing) perspective.

• Smart Shopping and Performance Max auto-bidding context — Product type data helps Google’s Smart Bidding algorithms understand product context, which can improve bid calibration. While not as strong a signal as price or conversion history, a well-structured product_type adds incremental context for bid automation.

Best practices

• Align product_type with your Google Ads campaign structure — Design your product_type hierarchy specifically to enable the campaign segmentation you want. If you want to run separate campaigns for “Furniture” and “Lighting”, those should be top-level product_type nodes.

• Be consistent in format and capitalisation — “Electronics > Audio” and “electronics > audio” are treated as different values by Google Ads. Standardise format across your entire feed via feed rules or your PIM system.

• Use the same separator consistently — Always use > with spaces on both sides. Mixing separators (“Electronics / Audio”, “Electronics-Audio”, “Electronics > Audio”) creates confusion in product group filtering.

• Include brand or margin tier as a hierarchy level where useful — Some merchants include their brand (for own-brand vs. multi-brand retailers) or margin tier (high-margin, medium-margin, clearance) as a product_type level. This enables margin-based bidding — bid higher for products with higher margins.

• Document your taxonomy — Maintain an internal reference document listing all valid product_type values and their intended use. This prevents different teams from independently creating overlapping or inconsistent categories.

Impact on performance

• Bid precision — The most direct benefit. Without granular product_type segmentation, Shopping bids apply uniformly across products with vastly different margins, competition levels, and conversion rates. Granular product_type allows ROAS-optimised bidding per category, often improving overall account ROAS by 20–40% compared to flat bidding.

• Budget allocation — In multi-campaign structures, product_type enables dedicated budgets per category, preventing high-volume commodity products from consuming budget that would be better spent on high-margin premium products.

• Performance diagnostics — Product_type segmentation in Google Ads reports makes it instantly visible if a specific product category is underperforming. Without it, diagnosing “why is ROAS declining” requires manual product-by-product analysis rather than a clear category-level view.

Common mistakes

• Using a flat single-level product_type (“Shoes”, “Shirts”) — provides no segmentation depth for bid management

• Copying google_product_category values into product_type — defeats the purpose; use your own business logic

• Inconsistent capitalisation or separator usage across the feed

• Changing product_type values frequently — disrupts historical segmentation in Google Ads reports

• Using product_type as a substitute for google_product_category — they serve different purposes; both are needed

• Making the taxonomy too deep (6+ levels) — creates diminishing bidding returns and feed maintenance overhead

Pro tips

• Use product_type to encode margin tiers — Add a “High Margin”, “Standard Margin”, or “Clearance” node at the first or second level of your product_type hierarchy. This allows you to create Smart Bidding targets that differ by margin: higher Target ROAS for clearance items (which need fast turnover), lower for high-margin products (which can sustain higher CPCs). This is one of the highest-leverage bidding techniques available in Shopping.

• Map product_type to your PIM categories at source — The best time to implement product_type is during your product data pipeline configuration. Map from your PIM’s internal category tree to your product_type hierarchy at the ETL layer, ensuring every new product automatically receives the correct value on creation.

• Use product_type filters in Google Ads script audits — Google Ads scripts can iterate over product groups segmented by product_type and programmatically identify categories with zero impressions, zero conversions, or outlier CPCs. Automating this audit catches bid management issues at scale that are invisible when reviewing accounts manually.

• Consider a “Seasonal” product_type node — Add a seasonal-products node (e.g., Seasonal > Christmas, Seasonal > Summer) for products you promote only during specific periods. This lets you create a high-urgency bidding rule that automatically applies to all seasonal products when that period is active, then falls back to standard bids — without touching individual product bids.