consulting

How To Enable Key Moments Snippets In Google Search via @sejournal, @MattGSouthern

Side by side comparison of third party traffic estimates from tools like semrush and ahrefs, built from clickstream panels and extrapolation, versus measured analytics from ga4 and search console based on first party tracking

Warren Hance on LinkedIn: There’s an elephant in the room that needs addressing…. The Misleading…

There’s an elephant in the room that needs addressing…. The Misleading Nature of SEMRush and Similar…
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Diagram mapping schema types such as product, faqpage, breadcrumblist, and videoobject to their rich result features, with notes on connecting the graph by @id and validating before shipping

Mike Ciffone on LinkedIn: #seo #technicalseo #google #richsnippets #schema | 17 comments

LinkRole is a relatively new schema org type that I recommend SEOs keep an eye on.…
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Diagram comparing lexical keyword search, semantic meaning based search, and ai answer engines, showing how each layer matches a query, how each one fails, and what seos optimize for at each stage.

Semantic Search: What It Is and Why It Matters for SEO

Semantic search is how search engines understand human language and intent. Learn how to use it…
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Three panel summary of google guidance on internal links: help discovery with crawlable a href links, signal importance through relevant internal links, and describe destinations with descriptive anchor text, plus practical guardrails

Google Shares Tips To Improve SEO Through Internal Links

Google shares three key tips for effective internal linking to improve SEO and user experience on…
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Hub and spoke internal linking diagram with a central pillar hub linking out to four subtopic spokes that link back, alongside a five step workflow: audit, group into clusters, add contextual links, point spokes at priority pages, recrawl and monitor

How to use internal linking for SEO

Internal links are important for users to navigate between content and pages on your website. In…
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Three step diagram showing how ahrefs, semrush and moz estimate keyword search volume by blending google keyword planner ranges, clickstream panels and serp data through a calibration model into an estimated monthly search number

How does AHREFS and SEMRush and Moz, etc, know the volume of searches for a given keyword/phrase?

It's not like they have backend information that only the search engines have (Bing, Google, etc...)...…
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