Dave Ojeda

Semantic Web Enthusiast, Knowledge Graph Geek & Structured Data Wrangler. Schema Markup, SEO & data is my day job and herding kids is my love! DM is open to all

[Dave Ojeda @daveojeda]

I waited for today to announce the launch of my Schema Markup consulting website:

https://t.co/lSLBxMIAyh

It is the anniversary of when I started in SEO. Felt like the perfect day to do it.

Working on some content & resources for the near future.

RTs welcome!

[nick Ξubanks @Nickeubanks]

After answering a lot of questions over and over again for new hires / junior team members for my GenAI video agency, I got smart and just built a training course.

I mentioned to another agency friend and he asked for it.. and I realized that this is probably a pretty common need, so...

Here it is: https://t.co/J5ZCwy0DpP

[Dave Ojeda @daveojeda]

@patrickstox Good luck on your next project! And thanks for everything you did at ahref

[Dave Ojeda @daveojeda]

@kensavage @tankots What about a foot pedal?

[Dave Ojeda @daveojeda]

@ech0_speaks @datemeT Here’s the link:

https://t.co/A2koRCZ6yY

[Dave Ojeda @daveojeda]

@tibo_maker backlink

[Dave Ojeda @daveojeda]

@RyanJones Or make it part of this cool product I know of @SERP_recon 😉

[Suganthan Mohanadasan @suganthan]

Google has published official WebMCP documentation on https://t.co/VwJhTvnRSb and confirmed an origin trial in Chrome 149. This is Google getting serious about shipping it. You can either live in denial or start learning this stuff quickly. The choice is of course yours.

Here is my guide: https://t.co/qEpvEnC6Oc

[Dave Ojeda @daveojeda]

@kensavage @NickLeRoy Will send you an email as well instead of dms

[Dave Ojeda @daveojeda]

@SynabunAI @kimmonismus You mean 15M :-)

[Dave Ojeda @daveojeda]

@benwills Can I assume you will be putting your videos up here:

https://t.co/bVWmErmQ28

[Dave Ojeda @daveojeda]

AI news of the year!

[Andrej Karpathy @karpathy]

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

[Ryan Jones @RyanJones]

There's been a lot of talk about commodity content since that latest Google presentation. No, they're not analyzing your prose when they talk about content quality. It's all statistics and NLP. So, I built this prototype to explain it. It's based on research papers I've read.

https://t.co/W3HO8OTuyR

[Dave Ojeda @daveojeda]

@bernardjhuang @clearscope Big congrats! Good luck on your next adventure!

[Dave Ojeda @daveojeda]

Grab it on Amazon

https://t.co/rRZfZaHTGP

[Dave Ojeda @daveojeda]

Hot off the presses! Looking forward to setting aside some of the weekend to read @Nickeubanks new book “The Last Moat”

In this face paced AI world distribution is not just the an advantage it might be the only one left.

[Dave Ojeda @daveojeda]

As always @suganthan knows how to dig deep into a subject. This time about Schema Markup. Excellent work!

https://t.co/NrS9OUIgoW

[nick Ξubanks @Nickeubanks]

It's ALIVEEEEE

https://t.co/KbFj4NEhS4

[Dave Ojeda @daveojeda]

@benwills is old school SEO which means he digs deep into data. Loved using his tool back in the day and excited to check this out!

[Ben Wills @benwills]

I spent the last 3 weeks running what might be the most comprehensive LLM ranking factors analysis to date.

29,562 unique domains tracked and scored across 145 industries, 1,595 buyer personas, and 105k+ ChatGPT prompts. Over 500TB of data, and 12 external signals correlated against rank-weighted LLM recommendation scores.

This is a large-scale correlation study: what external signals actually predict whether a brand gets recommended by ChatGPT, across 145 industries and 1,595 buyer personas.

--

Research Process

145 industries from 500 candidates. 11 personas each (10 targeted + 1 neutral). 25 runs per persona, rank-weighted scoring. 29,562 unique domains tracked.

Data collected:
- Common Crawl: 1.15B pages, domain mentions + phrase co-occurrences
- Reddit: 5B+ posts and comments scanned
- Google Search: 15,697 queries, top 100 results; 1.5M+ results captured
- SERP HTML: parsed for outbound links and phrase presence
- Wikimedia: 300M+ Wikidata entities + Wikipedia citations
- Backlinks (Common Crawl Web Graph): PageRank + Harmonic Centrality; 4B+
- Top Site Homepages: parsed for persona-specific phrases

--
Analysis Process

13 signals per domain. Spearman ρ vs. LLM recommendation score, per-industry and globally. R² shows variance explained. Lift measures over-representation in the top 10% most-recommended domains. Tiered: Dominant (ρ ≥ 0.30) down to Baseline (< 0.05).

--
Key Findings

SERP appearances, SERP rank, and outbound links from search results pages are the three strongest signals. Traditional SEO is the dominant measurable influence on LLM recommendations.

Backlink authority (PageRank, Harmonic Centrality) follows. Combined, these point to one thing: established search authority drives LLM visibility.

Signal hierarchies vary by industry. Wikidata dominates in established categories (hotels, ERP, furniture). Reddit drives community-driven ones (enterprise AI, live entertainment). No universal strategy.

80–85% of recommendation variance is inside the model. All external signals combined explain under 20%. You cannot infer LLM visibility from search rankings; you have to test it directly.

--
The Two Conclusions That Matter

1. SEO is the foundation. OpenAI is using search data today and building their own index. As that matures, the connection between search authority and LLM visibility deepens. Traditional SEO principles are not obsolete, they're the starting point for LLM visibility too.

2. Persona is the measurement unit. The #1 airline for a frequent flyer is a different site from the #1 for a student flying abroad. Same model, same industry, different person, different result. You don't have one LLM rank, you have a rank per buyer segment. Monitor by persona or the number is meaningless.

--
Full Report and data for all 145 industries and 1,595 personas available here:

https://t.co/z7885bCWnY

[Suganthan Mohanadasan @suganthan]

When you ask a browser agent to extract something from a site, it loads the page, takes a screenshot, uses a vision model to figure out your layout, content, and buttons. Then it clicks. Then it screenshots again to check whether anything happened.

Complex. Expensive. Slow. Wrong about half the time.

What if your site could just hand the agent a set of tools, and it called them directly? No screenshots, vision model or guess work?

Enter WebMCP.

Plenty of articles tell you it exists. Almost none show you how to actually wire it into your site.

So I did it and wrote a step by step so you can do it too.

https://t.co/qEpvEnC6Oc

[Suganthan Mohanadasan @suganthan]

Technical SEOs, your final boss fight is here.

Introducing Keyword Hunt, a technical SEO puzzle by @snippet_digital

20 keywords are cloaked across the site using real technical SEO, AI SEO, and edge engineering.

The first 10 to crack get permanent Elite status in the Hall of Fame.

Happy hunting: https://t.co/s9PsQw6dDu