Blog posts are the content AI actually cites. When a financial firm publishes market commentary, retirement planning guides, or tax strategy articles, structured data tells AI who wrote it, when it was published, and which firm stands behind it — turning a page of financial advice into a quotable, attributable source.
Financial blog posts are the pages AI cites most often when users ask about investing, retirement, or tax strategy. When someone asks an AI for advice on a topic your firm has written about, these are the signals it looks for before quoting or linking your article:
BlogPosting as the @type so AI recognizes the page as authored editorial content rather than a generic web page or marketing copy.Person node with name, jobTitle, url, and sameAs links tells AI exactly who is responsible for the financial advice and whether they have relevant credentials.publisher field links the article to your firm. AI uses this to attribute the financial advice to a regulated institution, not just an individual blogger.articleSection to categorize the post — "Retirement Planning," "Tax Strategy," "Market Commentary" — so AI can match it to the right type of financial query.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
headlinedescriptiondatePublisheddateModifiedauthorpublisherimagenamejobTitleurlsameAsnameurllogoCopy 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 Financial Service Blog 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. Author name 2. Author slug 3. Category 4. Crd number 5. Domain 6. Faq answer 7. Faq question 8. Featured image 9. Firm name 10. Job title 11. Linkedin 12. Logo 13. Modified date 14. Post description 15. Post slug 16. Post title 17. Publish date 18. Word count 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 Financial Service Blog" - 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 the template below and replace every YOUR_* value with your own data. This template covers a single blog post page on a financial service website.
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "BlogPosting",
"@id": "https://YOUR_DOMAIN.com/blog/YOUR_POST_SLUG/#article",
"headline": "YOUR_POST_TITLE",
"description": "YOUR_POST_DESCRIPTION",
"datePublished": "YOUR_PUBLISH_DATE",
"dateModified": "YOUR_MODIFIED_DATE",
"author": {
"@id": "https://YOUR_DOMAIN.com/#author"
},
"publisher": {
"@id": "https://YOUR_DOMAIN.com/#organization"
},
"image": "https://YOUR_DOMAIN.com/YOUR_FEATURED_IMAGE.jpg",
"articleSection": "YOUR_CATEGORY",
"wordCount": YOUR_WORD_COUNT
},
{
"@type": "Person",
"@id": "https://YOUR_DOMAIN.com/#author",
"name": "YOUR_AUTHOR_NAME",
"jobTitle": "YOUR_JOB_TITLE",
"url": "https://YOUR_DOMAIN.com/team/YOUR_AUTHOR_SLUG/",
"sameAs": [
"https://www.linkedin.com/in/YOUR_LINKEDIN",
"https://brokercheck.finra.org/individual/summary/YOUR_CRD_NUMBER"
]
},
{
"@type": "Organization",
"@id": "https://YOUR_DOMAIN.com/#organization",
"name": "YOUR_FIRM_NAME",
"url": "https://YOUR_DOMAIN.com",
"logo": "https://YOUR_DOMAIN.com/YOUR_LOGO.png"
},
{
"@type": "WebPage",
"@id": "https://YOUR_DOMAIN.com/blog/YOUR_POST_SLUG/",
"isPartOf": {
"@id": "https://YOUR_DOMAIN.com/#website"
},
"breadcrumb": {
"@id": "https://YOUR_DOMAIN.com/blog/YOUR_POST_SLUG/#breadcrumb"
}
},
{
"@type": "BreadcrumbList",
"@id": "https://YOUR_DOMAIN.com/blog/YOUR_POST_SLUG/#breadcrumb",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"name": "Home",
"item": "https://YOUR_DOMAIN.com/"
},
{
"@type": "ListItem",
"position": 2,
"name": "Blog",
"item": "https://YOUR_DOMAIN.com/blog/"
},
{
"@type": "ListItem",
"position": 3,
"name": "YOUR_POST_TITLE",
"item": "https://YOUR_DOMAIN.com/blog/YOUR_POST_SLUG/"
}
]
},
{
"@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"
}
}
]
}
]
}
Use a Person node for the author and an Organization node for the publisher. This tells AI that a specific advisor wrote the article and that the firm published it. AI systems give more weight to content with a named, credentialed author than to content attributed only to a company name.
Very important. Financial advice has a shelf life. Tax rules change, market conditions shift, and regulatory updates can make old advice inaccurate. AI systems check dateModified to decide if your article is still current. If you update a post with new tax year numbers or revised regulations, update the dateModified field so AI knows the content is fresh.
Use clear, descriptive categories that match how users search: "Retirement Planning," "Tax Strategy," "Investment Management," "Estate Planning," "Market Commentary," or "Financial Education." Avoid internal jargon. The value should be something a user might actually type into a search query.