Google Shopping Age Group Attribute: Values, Requirements & Best Practices

What is the age_group attribute?

The age_group attribute declares the intended demographic age range for a product. In Google Merchant Center, it serves as a primary classification signal for ensuring products appear in the correct age-segment searches and shopping filters. It is required for all Apparel & Accessories products — including explicitly adult products — because Google needs to be able to distinguish children’s from adult content at the product level.

Beyond simple search matching, the age_group attribute carries real-world safety implications. Children’s products are subject to different regulations, advertising restrictions, and content policies than adult products. Accurate age_group data is not merely an optimisation best practice — for brands selling to children, it is a compliance and brand safety necessity.

Technical specifications

Where it displays

• Shopping Ads — Google uses age_group to match products against age-qualified search queries. Searches for “baby onesies”, “toddler snowsuit”, “kids’ football boots”, or “adult swimming costume” each carry an age intent signal. Products with the correct age_group attribute are matched to these queries; products without it may appear for the wrong age group or miss the query entirely. The Shopping filter panel also surfaces an age group selector for Apparel, which exclusively shows products with the matching attribute.

• Free Listings — Free Listings in the Google Shopping tab include age-based filtering. The “Kids’” and “Baby” filter categories are directly powered by age_group data. A children’s clothing retailer without age_group data on its products loses visibility in the filtered Shopping browsing experience entirely — a major source of free impressions for age-segmented apparel brands.

• Dynamic Remarketing & Display Ads — Google’s audience engine uses age_group data when building remarketing audiences. When a parent browses infant clothing, the remarketing system categorises their browsing history within the infant product segment — and shows them infant products in follow-up display ads, not adult products. This age-accurate remarketing requires correct age_group data at the product level. Additionally, Google’s demographic targeting (Parental Status audience segments) is informed in part by the age_group distribution of products a user has browsed — accurate data improves the quality of these audience inferences.

Rules

• Only five values are valid — newborn, infant, toddler, kids, adult. All lowercase, exact spelling. Variations like “baby”, “children”, “junior”, “teen”, “adult+” will cause feed validation errors.

• Required for all Apparel & Accessories — This includes adult products. Do not leave age_group blank for adult clothing and footwear — submit adult explicitly.

• One value per product — If a product spans multiple age ranges (e.g., 6–24 months), choose the value that best represents the intended primary user. Do not submit multiple values.

• Must accurately reflect the product — Submitting adult for a children’s product to avoid children’s content restrictions is a policy violation. Google’s review processes and user flags can surface such misclassifications.

• Children’s advertising policy compliance — Products with newborn, infant, toddler, or kids age_group are subject to Google’s Children’s Content policy. Review this policy if you sell in these segments to ensure your ad creatives and landing pages comply with children’s advertising standards in your target markets.

Best practices

Age range mapping guide

Use this reference when mapping your internal age/size categories to Google’s five values:

• newborn — 0–3 months. Products labelled “Nb”, “Newborn”, “0-3M”, or “Premature” in your system.

• infant — 3–12 months. Products labelled “3M”, “6M”, “9M”, “3-6M”, “6-9M”, “6-12M”, “12M”.

• toddler — 1–5 years. Products labelled “12-18M”, “18-24M”, “2T”, “3T”, “4T”, “2Y”, “3Y”, “4Y”, “4-5Y”.

• kids — 5–13 years. Products labelled “5Y”, “6Y”, “7-8Y”, “9-10Y”, “11-12Y”, or size ranges “116-158 cm”.

• adult — 13+ years. All adult, teen, and junior adult products. Sizes XS–4XL, EU 34–58, etc.

Always pair with gender for children’s products

Age group alone is insufficient for children’s apparel. Always combine with gender:

• Boys’ Kids Hoodie → age_group: kids + gender: male

• Girls’ Infant Sleepsuit → age_group: infant + gender: female

• Unisex Baby Bodysuit → age_group: newborn + gender: unisex

Include age terminology in the product title

For children’s products, include age-relevant terminology in the title: “Kids’”, “Baby”, “Toddler”, “Infant”. This reinforces the age_group attribute signal and directly matches how parents search: “toddler rain jacket”, “baby winter hat”, “kids’ school shoes”.

Safety certifications in description, not age_group

The age_group attribute is purely a classification field. Safety certifications (EN 71, OEKO-TEX, CE marking), flammability standards, or age-appropriate warnings should be declared in the product description — not in the age_group field. This helps with trust-building and may support query matching for safety-conscious shoppers.

Impact on performance

• Age filter visibility — Children’s apparel retailers without age_group data are largely invisible in age-filtered Shopping browsing. Parents who filter by “Baby” or “Kids” will see only products with the correct age_group attribute — without it, you simply don’t exist in that filtered view.

• Query matching precision — Age-qualified searches (“toddler waterproof jacket”, “baby girl dress 0-3 months”) have high purchase intent. Products with correct age_group data are matched to these queries; products without it are not. This is pure incremental impression coverage.

• Budget protection for adult products — Correctly declaring adult for adult products prevents them from appearing in children’s product searches — avoiding irrelevant clicks from parents looking for children’s items who stumble upon adult products.

• Remarketing accuracy — Parents who browse baby gear are a distinct audience segment with specific purchasing patterns. Age-accurate remarketing shows them age-appropriate products, increasing relevance and conversion rates on Display campaigns.

• Regulatory risk reduction — Accurate age_group classification reduces the risk of accidental exposure of children to adult products (or inappropriate marketing of adult products to children’s-adjacent audiences), protecting your brand from GDPR, COPPA, and local children’s advertising regulatory risks.

Common mistakes

• Missing age_group for adult products — The most common mistake is assuming age_group only matters for children’s products. Adult apparel must explicitly declare adult.

• Using free text instead of enum values — Submitting “baby”, “children”, “toddler girl”, “teen”, “young adult”, “5-10 years”, etc. instead of the five exact accepted values.

• Miscategorising children’s products as adult — Often done unintentionally when a feed generator defaults all products to adult without category-specific logic. This is both a query matching problem and a policy risk.

• Not combining with gender for children’s products — Submitting age_group alone without gender for children’s apparel produces incomplete product classification.

• Wrong age range assignment — Placing a product that covers 6–24 months as toddler instead of infant because “18-24 months sounds like a toddler”. Choose the value that covers the majority of the intended age range.

• Inconsistent age_group across a product line — A children’s shoe range where some sizes are classified as kids and others as adult because the feed automation uses shoe size as a proxy for age without a proper mapping table.

Pro tips

• Build an age-size mapping table in your feed tool — The cleanest approach is to create a mapping table that converts your product’s actual size/age range label to Google’s five age_group values. Tools like Mergado, DataFeedWatch, and Channable support conditional rules that make this straightforward: if size contains “0M” or “3M” → age_group = infant; if size contains “2T” or “3T” → age_group = toddler; etc.

• Use custom labels for age-based campaign segmentation — In Google Shopping campaigns, add age_group-mirroring custom labels (e.g., custom_label_1: baby, custom_label_1: kids, custom_label_1: adult). This lets you set different bidding strategies per age segment — critical for retailers where baby products convert very differently than kids’ or adult products.

• Monitor age_group-qualified search terms separately — In your Search Terms report, filter for terms containing “baby”, “infant”, “toddler”, “kids”, “children”. Cross-reference against your age_group data to spot mismatches: if “toddler shoes” is converting well but you’re classifying those products as kids, your age_group data may be inaccurate and you’re likely losing impressions for toddler-specific queries.

• Double-check children’s product policy compliance before running campaigns — Before scaling spend on children’s products (newborn, infant, toddler, kids), review Google’s Families Policy and your target country’s children’s advertising regulations. Ad creative restrictions, landing page requirements, and data collection rules differ significantly for children’s products and violations can result in account-level suspensions.