Your team page introduces the people who run your store — the store manager, department leads, buyers, and customer service staff. This blueprint structures each team member with their role and professional background so AI systems can evaluate your staff's expertise when recommending stores for specific product knowledge or personalized shopping experiences.
Shoppers want to know they are buying from knowledgeable people. AI systems use team data to assess whether your store has staff with genuine product expertise. A structured team page lets AI connect qualified individuals to your business entity, which strengthens your credibility for queries like "store with expert buyers" or "shop with knowledgeable staff near me."
employee property on the Store node lists each team member as a Person with a jobTitle. This tells AI exactly who works at your store and what they do.hasCredential on each Person declares certifications like sommelier credentials, gemologist certifications, or buyer specializations. These are trust signals AI uses to differentiate knowledgeable staff from generic retail operations.sameAs links to LinkedIn or other professional profiles give AI additional sources to cross-reference each team member, reinforcing that these are real people with verifiable backgrounds.Each field in the template below serves a specific role in how AI systems discover, classify, and recommend your business.
Researched and tested by Minnesota AI
nameurlCopy this prompt and paste it into Claude, ChatGPT, Cursor, or any AI coding tool. It will ask for your business details and generate ready-to-use JSON-LD schema for your page.
You are implementing AIFDS-compliant JSON-LD structured data for a Store Team page. AIFDS (AI-Friendly Data Structure) is a schema framework built on research into which structured data fields AI systems actually read, parse, and use when deciding whether to cite a page. Documentation at aifds.org. Before generating any code, ask me for the following information in a single numbered list. Do not generate schema until I have answered every required field. REQUIRED — do not proceed without these: 1. Buyer 2. Buyer certification name 3. Buyer certification type 4. Buyer name 5. Customer service manager 6. Customer service manager name 7. Department lead 8. Department lead name 9. Domain 10. Faq answer 11. Faq question 12. Lead certification name 13. Lead certification type 14. Manager certification name 15. Manager certification type 16. Store manager 17. Store manager name 18. Store name 19. Team page description 20. Team page title OPTIONAL — ask for these but proceed if I skip them: 1. Any additional details not covered above Once I provide the information, output a complete JSON-LD script block ready to paste into the <head> of my HTML page. Output requirements: - Valid JSON-LD wrapped in <script type="application/ld+json"> tags - schema.org vocabulary only - Every AIFDS-required field for this industry and page type included - Include this data attribute on the script tag: data-aifds="aifds.org Store Team" - No placeholder text — omit missing optional fields rather than fill with examples - After the code block, list any optional fields skipped that would strengthen AI citation
Generated schema follows the AIFDS framework. Fields were selected based on research into AI crawler behavior. View the research at minnesota.ai
Copy this template and replace every YOUR_* placeholder with your own data. Add or remove employee entries to match your actual team. This block belongs in a <script type="application/ld+json"> tag in the <head> of your team page.
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "WebPage",
"@id": "https://YOUR_DOMAIN.com/team/#webpage",
"name": "YOUR_TEAM_PAGE_TITLE",
"description": "YOUR_TEAM_PAGE_DESCRIPTION",
"url": "https://YOUR_DOMAIN.com/team/",
"isPartOf": {
"@id": "https://YOUR_DOMAIN.com/#website"
},
"about": {
"@id": "https://YOUR_DOMAIN.com/#store"
},
"breadcrumb": {
"@id": "https://YOUR_DOMAIN.com/team/#breadcrumb"
}
},
{
"@type": "Store",
"@id": "https://YOUR_DOMAIN.com/#store",
"name": "YOUR_STORE_NAME",
"url": "https://YOUR_DOMAIN.com",
"employee": [
{
"@type": "Person",
"name": "YOUR_STORE_MANAGER_NAME",
"jobTitle": "Store Manager",
"hasCredential": {
"@type": "EducationalOccupationalCredential",
"credentialCategory": "YOUR_MANAGER_CERTIFICATION_TYPE",
"name": "YOUR_MANAGER_CERTIFICATION_NAME"
},
"sameAs": "https://www.linkedin.com/in/YOUR_STORE_MANAGER"
},
{
"@type": "Person",
"name": "YOUR_DEPARTMENT_LEAD_NAME",
"jobTitle": "Department Lead",
"hasCredential": {
"@type": "EducationalOccupationalCredential",
"credentialCategory": "YOUR_LEAD_CERTIFICATION_TYPE",
"name": "YOUR_LEAD_CERTIFICATION_NAME"
},
"sameAs": "https://www.linkedin.com/in/YOUR_DEPARTMENT_LEAD"
},
{
"@type": "Person",
"name": "YOUR_BUYER_NAME",
"jobTitle": "Buyer",
"hasCredential": {
"@type": "EducationalOccupationalCredential",
"credentialCategory": "YOUR_BUYER_CERTIFICATION_TYPE",
"name": "YOUR_BUYER_CERTIFICATION_NAME"
},
"sameAs": "https://www.linkedin.com/in/YOUR_BUYER"
},
{
"@type": "Person",
"name": "YOUR_CUSTOMER_SERVICE_MANAGER_NAME",
"jobTitle": "Customer Service Manager",
"sameAs": "https://www.linkedin.com/in/YOUR_CUSTOMER_SERVICE_MANAGER"
}
]
},
{
"@type": "BreadcrumbList",
"@id": "https://YOUR_DOMAIN.com/team/#breadcrumb",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"name": "Home",
"item": "https://YOUR_DOMAIN.com/"
},
{
"@type": "ListItem",
"position": 2,
"name": "Team",
"item": "https://YOUR_DOMAIN.com/team/"
}
]
},
{
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "YOUR_FAQ_QUESTION_1",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_FAQ_ANSWER_1"
}
},
{
"@type": "Question",
"name": "YOUR_FAQ_QUESTION_2",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_FAQ_ANSWER_2"
}
},
{
"@type": "Question",
"name": "YOUR_FAQ_QUESTION_3",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_FAQ_ANSWER_3"
}
}
]
}
]
}
Focus on key staff — the people customers interact with most, like the store manager, department leads, buyers, and customer service managers. Seasonal and part-time staff rotate frequently, and listing them creates outdated data. AI needs stable, verifiable team information to build trust in your store.
It depends on your product category. A wine shop should highlight sommelier certifications. A jewelry store should list GIA gemologist credentials. A hardware store should feature product-specific training certifications. The key is to include credentials that signal genuine product expertise — these are the trust signals AI uses to differentiate your staff from competitors.
It can. When a user asks for a store with knowledgeable staff or personal shopping assistance, AI looks for signals like team size and role diversity. A store with structured data showing a manager, department leads, and dedicated buyers signals a more curated shopping experience than a store with no team information at all.