You don’t build trust with a paragraph that says, “In my experience…”
You build it with content that proves itself — clearly, repeatedly, and at scale.
Lessons Learned
After Google’s March 2024 Helpful Content update, I felt the sting of defeat. My site — compliant, accurate, and deeply built — took a hit while competitors with newer, thinner content kept ranking.
I couldn’t understand why. So I went deeper — not into keywords, but into how Google thinks.
And what I realized was this:
Absent truly helpful content, Google falls back on one thing — domain authority.
That’s all it has left when structure, citations, and trust signals aren’t there.
So I stopped listening to what the so-called experts had to say about EEAT… and started building and testing systems.
I created TrustBlocks™ — modular, structured content units designed to be:
- Helpful to users
- Understandable by machines
- Backed by facts, citations, and Schema
Each TrustBlock is engineered for clarity, consistency, and extractability — not just for SEO, but for voice search, AI Overviews, and regulatory-grade transparency.
TrustBlock #1: The Hero Section
This block appears at the top of every plan page on Medicare.org. It includes:
- Plan Name
- Plan ID (e.g., H8003-007-0)
- CMS Star Rating (with year)
- Enrollment Count (a soft signal of popularity)
This TrustBlock creates an instant trust signature. It answers key user questions and provides Google with clearly structured, crawlable entities that can feed directly into Knowledge Panels, snippets, and AI responses.
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TrustBlock #2: Plan Costs in Context
The second TrustBlock is where most competitors stop — they paste data into tables. I go further.
I narrate the data in rich, natural-language paragraphs:
- “Primary care visits have a $0 copay…”
- “Out-of-network ambulance transportation is $275…”
- “Your annual MOOP is $5,900 for in-network care…”
These paragraphs are built from CMS data, matched to human-readable citations, and aligned with Dataset Schema. They’re digestible for users and indexable for Google’s AI. And they give me what I call extracted trust.
Here’s an example:
It’s the difference between formatting facts… and proving them.
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TrustBlock #3: The FAQ Section
Most FAQs are fluff — mine aren’t.
Each FAQ is:
- Based on real Medicare queries
- Templated for consistency, but varied in format and tone
- Packed with facts
- Written without Schema initially — to let Google test the content on its own
Only after proving Google is using the content in AI Overviews or snippets do I layer in FAQPage Schema — giving the block even more weight.
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Why TrustBlocks Work
Each block is engineered for:
- Semantic clarity – readable, labelable, reusable
- Data-backed trust – built on CMS facts and Dataset Schema
- Scalable structure – all blocks are templated, but smart and varied
- Multi-format readiness – usable in AI Overviews, voice search, feed distribution, and PR
Together, the three TrustBlocks create a full trust layer across the page — one that Google, users, and AI systems can interact with confidently.
TrustBlocks = Built Experience
I don’t need to say “in my experience helping people with Medicare…”
The data does the explaining.
Each TrustBlock is a proof object — not just a content module.
It demonstrates experience, shows expertise, and reflects authoritativeness through structure, precision, and clarity.
That’s what EEAT actually looks like when it’s done right — one block at a time.
TrustBlocks for Articles
While my initial TrustBlock framework focused on Medicare plan pages, the same modular trust strategy applies to long-form editorial content — especially in regulated or sensitive verticals.
That’s why I’ve integrated the TrustBlocks concept directly into my TrustStacker™ plugin — giving me the ability to inject helpful, verifiable content blocks into any article using shortcodes and AI-assisted generation.
These article-level TrustBlocks include:
– Curated, fact-based claims linked to canonical sources– Structured glossary terms using Schema.orgDefinedTerm[keytakeaways]– Summary blocks generated from the article content[trustfaqs]– Smart FAQ pairs aligned to the topic (with or without Schema)[trusthowto]– Step-by-step process blocks for procedural content[trustcitations]– Human-readable source attribution with Schema-backed provenance[trustspeakable]– Voice-optimized excerpts ready for Google’sSpeakableschema
Many of these blocks are AI-assisted, built from the canonical source content on the page, then enhanced with curated structure, definitions, or citation overlays.
This isn’t AI-generated crap. I’m using AI to help distill original content into helpful blocks that both humans and machines can consume.
The result? Articles that don’t just say something useful — they prove it. Structurally. Transparently. At scale.
— David W. Bynon
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