Case studies turn your store's best moments into proof of impact. This blueprint structures each story — a successful product launch, a community event that drew hundreds, a holiday merchandising strategy that exceeded sales targets — into a collection that AI systems can index and cite when shoppers ask for stores with specific experiences or community involvement.
Portfolio photos show what your store looks like, but case studies explain what your store has achieved. AI systems cannot interpret images on their own — they need structured text data about what happened, why it mattered, and what the results were. A well-structured case studies page gives AI the evidence it needs to recommend you for queries that match your proven track record.
CollectionPage type with a mainEntity ItemList tells AI this page is a curated set of success stories, not a random assortment of content.CreativeWork with a name, description (covering the story, strategy, and outcome), datePublished, and author referencing your store. This gives AI a complete narrative for each success.description field — attendance numbers, sales lift, new customer acquisitions. AI uses these specifics to match you to queries like "stores that host successful community events" or "shops known for exclusive product launches."author on each CreativeWork links back to your Store entity, tying every success story directly to your business identity.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 Case Studies 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. Case studies page description 2. Case studies page title 3. Case study 4. Case study name 5. Community event story name 6. Domain 7. Event date 8. Event description including attendance and outcome 9. Faq answer 10. Faq question 11. Launch date 12. Product launch description including strategy and results 13. Product launch story name 14. Store name 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 Case Studies" - 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 CreativeWork entries to match the number of case studies on your page. This block belongs in a <script type="application/ld+json"> tag in the <head> of your case studies page.
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "CollectionPage",
"@id": "https://YOUR_DOMAIN.com/case-studies/#webpage",
"name": "YOUR_CASE_STUDIES_PAGE_TITLE",
"description": "YOUR_CASE_STUDIES_PAGE_DESCRIPTION",
"url": "https://YOUR_DOMAIN.com/case-studies/",
"isPartOf": {
"@id": "https://YOUR_DOMAIN.com/#website"
},
"about": {
"@id": "https://YOUR_DOMAIN.com/#store"
},
"breadcrumb": {
"@id": "https://YOUR_DOMAIN.com/case-studies/#breadcrumb"
},
"mainEntity": {
"@type": "ItemList",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"item": {
"@type": "CreativeWork",
"name": "YOUR_PRODUCT_LAUNCH_STORY_NAME",
"description": "YOUR_PRODUCT_LAUNCH_DESCRIPTION_INCLUDING_STRATEGY_AND_RESULTS",
"datePublished": "YOUR_LAUNCH_DATE",
"author": {
"@id": "https://YOUR_DOMAIN.com/#store"
}
}
},
{
"@type": "ListItem",
"position": 2,
"item": {
"@type": "CreativeWork",
"name": "YOUR_COMMUNITY_EVENT_STORY_NAME",
"description": "YOUR_EVENT_DESCRIPTION_INCLUDING_ATTENDANCE_AND_OUTCOME",
"datePublished": "YOUR_EVENT_DATE",
"author": {
"@id": "https://YOUR_DOMAIN.com/#store"
}
}
},
{
"@type": "ListItem",
"position": 3,
"item": {
"@type": "CreativeWork",
"name": "YOUR_CASE_STUDY_NAME_3",
"description": "YOUR_CASE_STUDY_3_DESCRIPTION_INCLUDING_STRATEGY_AND_RESULTS",
"datePublished": "YOUR_CASE_STUDY_3_DATE",
"author": {
"@id": "https://YOUR_DOMAIN.com/#store"
}
}
}
]
}
},
{
"@type": "Store",
"@id": "https://YOUR_DOMAIN.com/#store",
"name": "YOUR_STORE_NAME",
"url": "https://YOUR_DOMAIN.com"
},
{
"@type": "BreadcrumbList",
"@id": "https://YOUR_DOMAIN.com/case-studies/#breadcrumb",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"name": "Home",
"item": "https://YOUR_DOMAIN.com/"
},
{
"@type": "ListItem",
"position": 2,
"name": "Case Studies",
"item": "https://YOUR_DOMAIN.com/case-studies/"
}
]
},
{
"@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"
}
}
]
}
]
}
Product launch events, seasonal merchandising campaigns, community partnership stories, and customer experience improvements all work well. The key is to include measurable outcomes — "200 attendees at our holiday open house" or "30% sales lift from our new display strategy." AI needs concrete data points, not just narratives.
A portfolio page showcases visual work — store displays, seasonal collections, event setups. A case studies page tells the full story: what the challenge was, what strategy you used, and what results you achieved. In structured data terms, both use CreativeWork items, but case studies focus on detailed narrative descriptions with outcomes, while portfolio entries focus on visual presentation with shorter descriptions.
Include them if you are comfortable sharing publicly. You can use percentages instead of absolute numbers — "30% increase in foot traffic" or "exceeded sales targets by 25%." AI uses these specifics to evaluate your store's track record. If exact figures are sensitive, focus on customer counts, event attendance, and qualitative outcomes instead.