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Top 8 Points - Improving your SEO with conceptual models - Mark Williams-Cook

SearchNorwich talk frame: speaker, "2Tb of data, 90,000,000 queries" slide

Here are the top 10 important points from Improving your SEO with conceptual models - Mark Williams-Cook

Video: https://www.youtube.com/watch?v=_AQ9UDqES80

Image Credits: searchnorwich.org

Topics Discussed

Conceptual Models for SEO

Google's Optimization Goal

Algorithm Updates and the Meta

Site Quality Score (I loved this one - Talks about how brand matters for SEO)

AI Content and the Site Quality Problem

Google Predicts Click Probability

Impact of the Helpful Content Update

SEO Game Strategy

Conceptual Models for SEO

Advanced SEO is about building conceptual models - stitching together knowledge of how search works to understand what drives rankings, rather than focusing solely on individual tactics.

Google's Optimization Goal

While Google tells SEOs to create "helpful content," it's real goal balances relevance with its need to make vast amounts of money. The resulting algorithm reflects this dual target.

Algorithm Updates and the Meta

Google’s updates are like a “meta” in gaming: SEOs identify what works (the meta), exploit it, and Google changes the rules to realign results. This cycle repeats continuously.

SearchNorwich talk frame: speaker beside a complex data-flow diagram

Site Quality Score

Google uses a Site Quality Score (0 to 1) at the subdomain level to determine rankings and eligibility for features like rich snippets. This score combines brand signals like branded search volume, anchor text mentions, and CTR.

SearchNorwich slide: bar chart of subdomains by site_quality score

Consensus and Query Classifiers

Google calculates a consensus score for content (agree, contradict, or neutral) to determine reliability. Specific query classifiers like “is debunking” or “YM YL” (Your Money, Your Life) trigger stricter algorithms.

SearchNorwich slide: frequency chart of semantic query classes

Ranking vs Post-Ranking Adjustments

There’s a distinction between “ranking” and “post-ranking”: Google doesn’t directly use CTR in initial ranking, but post-ranking adjustments consider how users interact with SERPs to refine results.

SearchNorwich slide: Sistrix visibility for Causal.app AI content spike and drop

AI Content and the Site Quality Problem

AI content caused Google's site quality prediction model to fail, as AI-generated content often initially scores high. This led to the Helpful Content Update, which now heavily favors authoritative and well-known brands.

SearchNorwich slide: high SEO metrics, low brand metrics punished by HCU

Google Predicts Click Probability

Google has a model that predicts click-through rates for search results, based on factors like title tags. While CTR isn’t a ranking factor, performing better than predicted impacts visibility.

SearchNorwich slide: JSON with click_age_probability and site_quality fields
SearchNorwich talk frame: speaker with domain site-quality score list

Impact of the Helpful Content Update

The update penalized sites with high domain authority (SEO-focused) but low brand authority (unrecognized brands), reinforcing Google's focus on trust and brand recognition.

SearchNorwich slide: "There is a Site quality score patent"

SEO Game Strategy

Like optimizing games such as Theme Park, SEOs should balance “documented” (title tags, content) and “undocumented” (user signals, brand metrics) strategies to align with Google’s ever-changing meta.

These points summarize the core themes around advanced SEO strategies, algorithm behavior, and Google's priorities.

First published on LinkedIn on Dec 17, 2024, 2:07 PM UTC (original). Kept here in full so it stays available; the media are this site's copies of the ones on LinkedIn, also in Venkata Pagadala - Universe.

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