The MarSec Schema

Beyond JSON‑LD: Structured Data for Every Platform (Website, Social, Video, Podcasts, Reviews)

JSON LD is wonderful. It is the W3C standard for structured data on websites. It works with Google, Bing, and most search engines. But your brand lives far beyond your website. LinkedIn does not read your JSON LD. Twitter (X) does not. YouTube does not. Podcast apps do not. G2 does not. Each platform has its own structured data language. Some are markup formats. Some are API feeds. Some are simply well formatted bios and descriptions that platforms parse. If you only implement JSON LD, you are leaving 80% of your digital footprint unstructured. And unstructured means un retrievable. This post is a field guide to structured data across every major platform type.

Latest Posts

The Trust Auditor: Training Non‑Technical Teams to Protect Narrative Integrity

You have a narrative ledger. You have structured data. You have monitoring tools.
But the person updating your LinkedIn company page is an intern. The person responding to G2 reviews is a customer support agent. The person writing your podcast descriptions is a content coordinator.
If these team members do not understand narrative integrity, your infrastructure is useless.
The strongest cybersecurity strategy does not start with a firewall. It starts with humans: aware, aligned, resilient. The same is true for narrative security.
You need to train every person who touches your digital footprint to be a trust auditor.

May 26, 2026 No Comments

The Distributed Content Architecture: Managing Fragments Across Your Entire Digital Footprint

Your brand is not a single narrative. It is thousands of fragments distributed across dozens of platforms, each with its own structure, each with its own retrieval logic.
A podcast episode mentions your product. A Reddit comment describes your service. A review site user posts a photo of your packaging. A partner’s LinkedIn article quotes your CEO. A forum thread links to your documentation.
Each fragment is a data point for AI retrieval systems. Each fragment can be accurate or distorted. Each fragment contributes to your trust density or detracts from it.
You cannot control every fragment. But you can architect a system that makes accurate fragments more likely and distorted fragments less damaging.
This is distributed content architecture.

May 26, 2026 No Comments

Optimizing for Social AI: How Recommendation Engines Discover Your Brand

Social media algorithms are AI agents.
They read your content before humans do. They extract entities. They categorize your brand. They decide whether to surface your posts to followers or suppress them.
But unlike LLM based assistants, social AI agents have a different objective: maximize engagement and time on platform. They are not trying to answer questions accurately. They are trying to predict what content will keep users scrolling.
This changes how you optimize.
Optimizing for Google’s search AI is about verifiability and relevance. Optimizing for LinkedIn’s feed AI is about engagement prediction and entity coherence.
You need both.

May 26, 2026 No Comments

The Multi‑Platform Structured Data Stack

Think of structured data as a stack, not a single tool.

Layer 1: Website structured data (JSON‑LD, Microdata, RDFa)
Layer 2: Social platform markup (Open Graph, Twitter Cards, oEmbed)
Layer 3: Platform‑specific metadata (LinkedIn company page fields, YouTube video schema)
Layer 4: Content API feeds (podcast RSS, review site product feeds)
Layer 5: Natural language structure (consistent entity naming in bios, descriptions, alt text)

Most organizations stop at Layer 1. The organizations that win go to Layer 5.

Layer 1: Website Structured Data (JSON‑LD is not the only option)

Yes, use JSON‑LD. But also consider:

Microdata (older but still parsed): Embed schema directly in HTML attributes. Useful for email signatures, simple pages.
RDFa (more verbose but very expressive): Used by some enterprise CMS and government sites.
Speakable schema (for audio content): Tells assistants which parts of your page are suitable for text‑to‑speech.

Tools beyond JSON‑LD generators:

Schema App: Enterprise‑grade structured data management across many pages.
RankMath (WordPress) or Yoast SEO: Generate JSON‑LD plus Open Graph and Twitter Cards.
Google’s Structured Data Testing Tool and Rich Results Test: Validate all types.

But again, Layer 1 is just the beginning.

Layer 2: Social Platform Markup

Every major social platform uses Open Graph (OG) tags. Some have additional proprietary tags.

Open Graph basics (Facebook, LinkedIn, Pinterest, Slack, iMessage):

og:title, og:description, og:image, og:url, og:type
og:site_name, og:locale

Twitter Cards (X):

twitter:card (summary, summary_large_image, player, app)
twitter:site, twitter:creator, twitter:title, twitter:description, twitter:image

oEmbed (used by many platforms for rich embeds):

Not a tag you implement on your page, but an API endpoint you provide.
Platforms like YouTube, Instagram, and X use oEmbed to generate embed code.

Tools for Layer 2:

Open Graph Debugger (Facebook): See how your page appears when shared. Also tests Twitter Cards.
Twitter Card Validator: Specifically for X.
oEmbed Sandbox (if you build your own oEmbed endpoint).
Social Share Preview browser extensions (many free).

Implementation tip: Most CMS plugins (Yoast, RankMath) generate OG and Twitter tags automatically from your page metadata. But manually verify with the debuggers.

Layer 3: Platform‑Specific Metadata

Each platform has its own fields that function as structured data.

LinkedIn Company Page:

Fill EVERY field: tagline, description, specialties, website, industry, company size, headquarters.
These become entities in LinkedIn’s internal knowledge graph.
Tool: LinkedIn’s native page editor. No external tool needed, but audit monthly.

YouTube Channel and Videos:

Channel keywords, description, links
Video title, description, tags, category, subtitles (transcripts are structured data for speech)
Tool: YouTube Studio analytics shows how your metadata performs.

TikTok and Instagram:

Bio text (use canonical entity names)
Hashtags (these are lightweight entity markers)
Alt text on images (Instagram allows custom alt text — use it)
Tools: Later, Buffer, or Hootsuite for consistent bio management across profiles.

Podcast Platforms (Apple, Spotify, Overcast):

RSS feed tags: <itunes:summary>, <itunes:keywords>, <itunes:category>, <googleplay:description>
Podcast episode titles and descriptions must be entity‑consistent.
Tools: Transistor, Buzzsprout, or Captivate generate RSS with proper tags. Use Podcast Index verification tool.

Review Sites (G2, Capterra, Trustpilot):

You often cannot directly edit structured data, but you can claim your profile and fill out every field.
Consistent product names, categories, and descriptions across review sites are essential.
Tools: ReviewTrackers or Trustpilot Business to manage listings.

Layer 4: Content API Feeds

For platforms that accept API feeds, you can push structured data directly.

Google Business Profile (formerly GMB):

API to update name, address, phone, categories, attributes, posts.
Tool: Reputation.com or Maps.Marketing for bulk management.

E‑commerce platforms (Amazon, eBay, Etsy):

Product feeds (XML, CSV, API) with exact fields for title, description, category, brand.
Tools: Feedonomics, GoDataFeed, or Lengow.

Knowledge Graph / Panel APIs:

Google Knowledge Graph API: Not for you to push, but to see what Google knows about you.
Schema.org sameAs references help connect your entities across platforms.

Layer 5: Natural Language Structure (The Forgotten Layer)

When no structured format exists, consistent natural language is your only option.

Bios and descriptions on platforms like Reddit, Quora, Medium, Substack, Discord, Slack:

Use your canonical entity name exactly as it appears on your website.
Use consistent taglines.
Repeat your primary category term.

Image alt text across all platforms:

Alt text is structured data for vision‑based AI agents.
Include your entity name and key capability where natural.

Video and podcast transcripts:

Transcripts are machine‑readable text that LLMs use.
Ensure transcripts use canonical entity names and consistent claim language.
Tools: Otter.ai, Rev.com, or Descript for transcripts.

Social media posts (organic, not just ads):

Every post is a data point for platform AI.
Use consistent hashtags (which act as entity markers).
Repeat core claims across posts (not copy‑paste, but thematic repetition).

A Cross‑Platform Structured Data Audit Workflow

You cannot audit everything monthly. Prioritize.

Weekly:

Check Open Graph and Twitter Cards for your latest blog posts using debuggers.
Review LinkedIn company page fields (5 minutes).

Monthly:

Use Schema App or Google Search Console to audit website structured data.
Spot‑check two social bios (e.g., Instagram and TikTok) for entity consistency.
Review your podcast RSS feed using Podcast Index validator.

Quarterly:

Run a full extraction audit on your website (using Google Natural Language API or similar).
Manually check top 5 third‑party listings (Crunchbase, G2, Trustpilot, Google Business, Wikipedia if exists).
Audit video transcripts for entity consistency (choose 3 recent videos).

Annually:

Deep audit of all 20‑30 platforms where your brand appears.
Update your narrative ledger with any new platform fields.

Tools Summary (Beyond JSON‑LD)

Platform Type	Tools
Website structured data	Schema App, RankMath, Google Rich Results Test
Social markup	Open Graph Debugger, Twitter Card Validator
LinkedIn	Native page editor + LinkedIn API for automation
YouTube	YouTube Studio, TubeBuddy (for metadata templates)
Podcasts	Transistor, Buzzsprout, Podcast Index validator
Review sites	ReviewTrackers, Trustpilot Business
Image alt text	Airtable to track alt text across platforms
Transcripts	Descript, Otter.ai, Rev
Multi‑platform consistency	Brand24, Mention, Apify for custom scraping
Knowledge graph	Neo4j, Diffbot, Google Knowledge Graph API