Product Data and Attributes - Beyond the Basics

Google's product data specification includes over 170 attributes spanning identification, categorization, pricing, shipping, promotions, and more. While only a handful are strictly required, the depth and accuracy of your product data directly influences auction performance. This guide goes beyond the basics covered in Feed Optimization to examine the optional attributes that create competitive advantage.

The Full Attribute Landscape

Google's product data specification is organized into several categories, each serving a different purpose in the Shopping ecosystem:

• Basic product data (id, title, description, link, image_link, additional_image_link): The foundation of every product listing
• Price and availability (price, sale_price, availability, cost_of_goods_sold): Determines what users see and what Google can calculate
• Product category (google_product_category, product_type): Helps Google classify and match your products
• Product identifiers (brand, gtin, mpn, identifier_exists): Used to match products across merchants
• Detailed product description (condition, adult, age_group, color, gender, material, pattern, size, size_type, size_system): Provides granular product details
• Shopping campaigns and other configurations (custom_label_0-4, promotion_id, ads_redirect): Campaign management attributes
• Shipping (shipping, shipping_label, shipping_weight, shipping_length/width/height, transit_time_label, max_handling_time, min_handling_time): Determines shipping display
• Tax (tax, tax_category): Tax configuration for applicable markets
• Marketplace attributes (external_seller_id, pause): For marketplace and multi-seller setups

Most merchants use 20 to 40 attributes depending on their product categories. The goal is not to populate every possible attribute but to provide complete and accurate data for all attributes relevant to your products. Google rewards completeness within relevant categories, not raw attribute count.

Most Impactful Optional Attributes

Not all attributes carry equal weight. These optional attributes have the most measurable impact on Shopping performance and should be prioritized in your feed optimization efforts.

google_product_category

Google automatically assigns a product category based on your product data, but the automatic classification is not always accurate. Manually setting the google_product_category attribute ensures your products are classified correctly, improving query matching and competitive positioning. Use the most specific category available in Google's taxonomy. For example, use "Apparel & Accessories > Shoes > Athletic Shoes > Running Shoes" rather than just "Apparel & Accessories".

product_type

Unlike google_product_category, product_type uses your own category hierarchy. It does not directly affect Google's query matching, but it enables product group subdivisions in your Shopping campaigns. A well-structured product_type hierarchy gives you granular bidding control. Use up to five levels separated by the ">" character.

product_highlight

Up to 10 short bullet points (each up to 150 characters) highlighting key product features. Product highlights may appear in free listings and enriched product results. They help users make purchase decisions without clicking through to your site, which can improve conversion rates for users who do click. Keep each highlight concise and focused on a single feature or benefit.

GTIN (Global Trade Item Number)

GTINs (EAN in Europe, UPC in the US, ISBN for books) are critical for product matching. Google uses GTINs to link the same product across different merchants, enabling price comparison and rich product pages. Products with valid GTINs receive preferential treatment in the Shopping auction. If your products have manufacturer-assigned GTINs, always include them. The performance difference between products with and without GTINs is well documented and significant.

MPN (Manufacturer Part Number)

For products without GTINs, the combination of brand + MPN serves as a product identifier. This is particularly relevant for custom or specialty products, industrial equipment, and parts where GTINs are less common. Always provide MPN when GTIN is not available.

shipping

Product-level shipping information overrides account-level shipping settings for specific products. This is valuable for heavy or oversized items with different shipping costs, free shipping promotions on specific products, and products with expedited shipping options. Shipping cost and speed are displayed in Shopping ads and significantly influence click and conversion behavior. Free shipping badges, in particular, improve CTR.

sale_price and sale_price_effective_date

When you set a sale_price along with sale_price_effective_date, Google displays the original price with a strikethrough and the sale price prominently. This triggers a "Sale" badge on your Shopping ad, which significantly improves CTR. The visual treatment catches user attention and creates urgency. Use this for genuine promotions, not as a permanent pricing strategy, as Google may remove the badge for perpetually discounted items.

cost_of_goods_sold

Providing your cost of goods enables Google Ads to calculate and display gross profit metrics. This is transformative for bidding optimization, as you can see which products generate the most profit (not just revenue) and adjust bids accordingly. With Cobiro CSS reducing your CPCs, the profit per click increases, and cost_of_goods_sold data helps you quantify that improvement precisely. This attribute is only visible to you in reporting and is never shown to shoppers.

additional_image_link

You can provide up to 10 additional product images beyond the primary image_link. Additional images appear in Shopping ad galleries and product detail pages. They are particularly important for products where users want to see multiple angles, close-up details, or the product in use. Lifestyle images (showing the product in context) complement standard product-on-white images and can improve engagement.

New AI-Driven Attributes for 2025 and 2026

Google has been steadily expanding the product data specification to leverage AI capabilities. Several new and evolving attributes reflect this direction.

Automatically Improved Product Data

Google now uses AI to enhance product information automatically. If you enable "automatic improvements" in Merchant Center, Google may update certain attributes based on data from your landing pages, structured data markup, and other signals. This includes automatically correcting product categories, extracting missing attributes from product descriptions, and standardizing color and size values. While helpful for filling gaps, manual curation still produces better results for high-value products.

AI-Generated Product Descriptions

Google has introduced the ability to generate product descriptions using AI within Merchant Center. For products with minimal descriptions, this feature can create more detailed text based on the product title, category, and image. Merchants can review and edit generated descriptions before they are published. This feature is gradually rolling out and is not yet available in all markets.

Visual Search Optimization Attributes

As Google Lens and visual search become more prominent in the shopping journey, image quality and metadata are increasingly important. Google now processes product images with AI to extract features like color, pattern, style, and shape. While there are no specific new feed attributes for visual search, the quality and variety of your product images directly influence how well your products perform in visual search results.

Sustainability and Certification Attributes

Google has introduced attributes for environmental certifications, energy efficiency ratings, and sustainability labels. These include certification attributes for EU energy labels, organic certifications, and other environmental credentials. As consumers increasingly factor sustainability into purchase decisions, these attributes can differentiate your products in Shopping results.

Product Details and Structured Specifications

The product_detail attribute allows you to provide structured key-value pairs for specifications that do not have dedicated attributes. For example, you can specify "Battery Life: 12 hours" or "Thread Count: 400" as structured data. This information may appear in enriched product listings and helps Google better understand and match your products.

Data Quality Score

Google Merchant Center evaluates product data quality across multiple dimensions. While Google does not publish a single "quality score" number for feed data, the platform surfaces quality indicators through several mechanisms:

• Product-level status: Each product shows an approval status (Approved, Disapproved, Pending) along with specific issues
• Diagnostic issues: The Diagnostics tab groups issues by severity (errors, warnings, suggestions) and shows affected product counts
• Potential improvements: Merchant Center highlights opportunities to improve product data, such as adding missing attributes or fixing inconsistencies
• Competitive visibility metrics: In Merchant Center Next, the Performance tab shows how your products rank relative to competitors, which is influenced by data quality

Feed quality assessment factors into the Shopping auction in subtle but important ways. Products with higher data quality receive better Ad Rank, all else being equal. This means a product with complete, accurate attributes can outperform a competitor's product with the same bid but less complete data. When you combine superior data quality with the 20% CPC advantage from CSS, the competitive advantage is substantial.

Image Requirements and Best Practices

Product images are one of the most visible elements of a Shopping ad. Image quality affects both approval status and click-through rate. Here are the complete requirements and best practices.

Minimum Requirements

Recommended Specifications

• Resolution: 800 x 800 pixels minimum, 1200 x 1200 pixels or higher preferred. Higher resolution images display better across devices and in image search.
• Background: White or light-colored background for the primary image. This produces the cleanest Shopping ad appearance. Lifestyle images are appropriate for additional images.
• Product coverage: The product should occupy 75 to 90% of the image frame. Avoid excessive white space or very tight cropping.
• Consistency: Maintain consistent image style across your catalog for a professional appearance in Shopping results.

What Is Not Allowed

• Watermarks: No text, logos, or watermarks overlaid on the product image
• Promotional text: No "Sale", "Free shipping", or other promotional overlays
• Placeholder images: No generic category images or "image coming soon" placeholders
• Borders or frames: No decorative borders around the product image
• Multiple products: The primary image should show only the product being sold (bundles excluded)

Additional Image Strategy

For the additional_image_link fields, consider a structured approach:

1. Primary image: Product on white background, front-facing
2. Additional image 1: Product from a different angle
3. Additional image 2: Close-up detail shot
4. Additional image 3: Product in use or lifestyle context
5. Additional image 4: Size or scale reference
6. Additional images 5-10: Other relevant views, packaging, included accessories

Apparel-Specific Attributes

The apparel and fashion category has the most extensive attribute requirements. In addition to the standard attributes, these fields are required or strongly recommended for clothing, shoes, and accessories:

• color (required): Use standard color names. If the product has multiple colors, list the primary color first.
• size (required): Use the sizing system appropriate to your target market. Be specific (do not use "One Size" unless genuinely universal).
• gender (required): male, female, or unisex
• age_group (required): newborn, infant, toddler, kids, adult
• size_type (recommended): regular, petite, plus, tall, big, maternity
• size_system (recommended): US, UK, EU, AU, etc.
• material (recommended): Primary material of the product
• pattern (recommended): solid, striped, plaid, floral, etc.
• item_group_id (required for variants): Groups product variants (different sizes and colors of the same product) together

For apparel advertisers, filling in these attributes is not optional from a performance perspective. Apparel searches are highly specific, and incomplete attribute data means missing high-intent queries. A user searching for "women's red midi dress size 12" will only see products that have gender, color, product type, and size properly defined.