{
"@context": "https://schema.org",
"@type": "BlogPosting",
"headline": "The 14-Point Schema Markup Checklist for Google AI Overviews",
"author": {
"@type": "Person",
"name": "Vivek Kumar",
"url": "https://softechinfra.com/team/vivek-kumar"
},
"publisher": {
"@type": "Organization",
"name": "Softechinfra",
"logo": {
"@type": "ImageObject",
"url": "https://softechinfra.com/assets/logo/squareLogo.png"
}
},
"datePublished": "2026-04-03",
"dateModified": "2026-04-03",
"image": "https://softechinfra.com/blog/14-schema-checklist.jpg",
"mainEntityOfPage": {
"@type": "WebPage",
"@id": "https://softechinfra.com/blog/14-point-schema-checklist-ai-overviews"
}
}{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [{
"@type": "Question",
"name": "Does FAQ schema still work in 2026?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Yes for AI citations, no for SERP rich snippets. Google deprecated the FAQ rich snippet in May 2026, but ChatGPT, Perplexity, Claude, and AI Overviews all still parse FAQPage JSON-LD to extract and cite content. Keep it in your code."
}
}, {
"@type": "Question",
"name": "How many questions should an FAQPage schema include?",
"acceptedAnswer": {
"@type": "Answer",
"text": "5 to 7 questions hits the sweet spot. Each question 30 to 60 words in the answer. All questions must be visible to the user on the page or Google will flag it as a structured data violation."
}
}]
}{
"@context": "https://schema.org",
"@type": "BreadcrumbList",
"itemListElement": [{
"@type": "ListItem",
"position": 1,
"name": "Home",
"item": "https://softechinfra.com/"
}, {
"@type": "ListItem",
"position": 2,
"name": "Blog",
"item": "https://softechinfra.com/blog"
}, {
"@type": "ListItem",
"position": 3,
"name": "Schema Checklist",
"item": "https://softechinfra.com/blog/14-point-schema-checklist-ai-overviews"
}]
}name, url, logo, sameAs (your social profiles), founder, address. We always include LinkedIn, X, YouTube, and a founder Person object linking out to our founder's personal site — the more entity signals, the better Google's knowledge graph understands you.
### 5. Person — for every author
Every blog author gets a Person schema. AI engines use the Author entity to attribute content and weigh credibility. Without it, "Softechinfra Team" is anonymous and rankings suffer.
{
"@context": "https://schema.org",
"@type": "Person",
"name": "Vivek Kumar",
"url": "https://softechinfra.com/team/vivek-kumar",
"sameAs": [
"https://viveksinra.com",
"https://linkedin.com/in/viveksinra",
"https://twitter.com/viveksinra"
],
"jobTitle": "Co-Founder & CEO",
"worksFor": {
"@type": "Organization",
"name": "Softechinfra"
}
}{
"@context": "https://schema.org",
"@type": "HowTo",
"name": "How to Set Up WhatsApp Business API for an Indian SMB",
"totalTime": "P4D",
"estimatedCost": {
"@type": "MonetaryAmount",
"currency": "INR",
"value": "12000"
},
"step": [{
"@type": "HowToStep",
"name": "Verify Facebook Business Manager",
"text": "Create a Facebook Business Manager account and verify your business with GST + PAN."
}, {
"@type": "HowToStep",
"name": "Connect WhatsApp Business Account",
"text": "Inside Meta Business Manager, add WhatsApp Business Account, verify your business phone number."
}]
}provider, serviceType, areaServed, and links to relevant case studies. Google treats Service schema as a strong entity signal for local + AI search.
### 9. Review and AggregateRating
If you have 5+ legitimate client reviews, AggregateRating with ratingValue and reviewCount becomes one of the strongest AI Overview signals for service buyers. Fake or scraped reviews trigger penalties — only use this if reviews are real and verifiable.
### 10. Speakable — voice and NotebookLM
Speakable schema marks specific page sections as suitable for text-to-speech extraction. Initially designed for Google Assistant, it became relevant again in 2025 when NotebookLM-style audio overviews emerged as a distribution channel.
{
"@context": "https://schema.org",
"@type": "WebPage",
"name": "The 14-Point Schema Markup Checklist",
"speakable": {
"@type": "SpeakableSpecification",
"cssSelector": [".blog-stats-grid", ".speakable-tldr", "h1", "h2"]
}
}<div class="speakable-tldr"> and you are done.
### 11. VideoObject — for embedded video
Every embedded YouTube or self-hosted video on a content page gets VideoObject schema. It tells AI engines what the video is about and where in the timeline the key moments live. Especially useful for AI Overview video carousels.
### 12. Course
Edtech and training pages get Course schema. Our in-house product PenLeap uses Course schema heavily for its exam-prep modules — each module becomes a discoverable entity. For Softechinfra services this is mostly relevant on workshop and training landing pages.
### 13. SoftwareApplication — for tool reviews and SaaS
If you write about a software tool, wrap each named tool in SoftwareApplication schema with applicationCategory, operatingSystem, and offers. AI engines pull these into comparison answers verbatim.
### 14. ImageObject and the visual entity layer
Every important image on a page (the hero, charts, screenshots) gets ImageObject schema with contentUrl, creator, creditText, license. This is part of Google's Image Discovery infrastructure but increasingly fed into AI Overviews for visual answers.
## The DIY ship plan (3 days)
Pre-flight checklist before you start the dev push:
- You have admin access to your CMS or _document file (Next.js, Astro, WordPress)
- You can validate at Google Rich Results Test on staging URLs
- You have author bio data (real photo, LinkedIn URL, X handle, role) for every Person schema
- You have 5 to 7 real customer questions per priority page (pulled from sales call notes)
- You have your Organization sameAs list ready (LinkedIn, X, YouTube, founder personal site)
dateModified: 2026-04-03 but you have not touched the page, AI engines down-weight the freshness signal once they realize you are gaming it. Only update dateModified when you actually update content.
## A real example
A 14-person Coimbatore textile-tech SaaS client came to us with 38 blog posts and zero schema. Indexed in Google, never cited in AI Overviews. We shipped the 5 priority schemas across the whole site in a single 6-hour push, validated everything, and pinged the Google Indexing API. In 4 weeks, they appeared as a cited source in 7 AI Overview answers for their target queries. No content changed. Schema alone, 4 weeks. This is the cheapest GEO lever we know.
## FAQ
### Does schema help if my content is bad?
No. Schema amplifies the signal of good content; it does not invent signal. A thin or unhelpful page with full schema will not be cited. Fix the content first, schema second.
### Should I use JSON-LD or Microdata?
JSON-LD only. All major AI engines (Google, Bing/ChatGPT, Perplexity, Claude) parse JSON-LD reliably. Microdata and RDFa are legacy formats — we have removed them from every client site we work on without any measurable loss.
### Where do I put the JSON-LD block on the page?
<head> is best for AI extractors and matches Google's recommendation. Some teams put it before </body> for build-system reasons; it works but <head> is cleaner. Never put it inside <noscript>.
### How often does Google re-parse my schema?
Every Googlebot crawl. For a fresh post, that is hours. For an old page, it can be weeks. Use Google Search Console's URL Inspection to force re-crawl on a critical page.
### What is the single highest-impact schema to ship today?
FAQPage with 5–7 real customer questions on your top 10 pages. Half a day of work, immediate AI citation lift, near-zero downside.
### Do I need schema if I use a CMS that ships some by default?
Probably yes. WordPress + Yoast ships limited Article schema and basic Organization. Most CMSes miss FAQPage, HowTo, Speakable, and Service entirely. Audit what your CMS emits with Google's Rich Results Test, then layer in the gaps with a custom snippet.
### Does Schema.org's spec change frequently?
Yes, twice a year typically. Most changes are additive (new types). The 14 in this list are stable as of May 2026 and unlikely to change before 2027. Subscribe to the Schema.org release notes if you ship schema professionally.
Want All 14 Schemas Implemented Site-wide?
We audit your current schema, ship the 14 priority types end-to-end, validate at Rich Results Test, ping the Indexing API, and hand over a maintenance doc. Fixed scope, 3 working days for a 50-page site, ₹45,000 for Indian SMBs. Includes a 30-day re-check after the first AI Overview citations land.
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