The #SEOchat on Twitter was run by “Brian Dordevic.” These tweets are jam-packed with information, yet you can miss them because of how swiftly they emerge and go.

Brian Dordevic is a #WebDesign & SEO Expert and the President of @AlphaEfficiency & AthenaSocieties. He is passionate about: #SEO #GoogleAds #WebDesign #JavaScript

I don’t think it was as much adapting and changing in the immediate but to me this was a big step forward in google getting more specific in what it was able to serve #seochat

Mordy Oberstein 

A1 Shifted to keyword planning based on what content might rank higher with AI determining rank.

More concise, less meaningless words for long tail keyword ideas

Sweepsify 

A1: There isn’t really anything to optimize as it aims to emulate our natural language.

I was still “fresh” so it didn’t affect at all my performance.

For sure, it helped a lot with ranking compared to pre-BERT.

Marco Giordano

A2 Not really affected. Have seen others getting decimated, but hard to say why, since we also have HCU rolling out. Some of these sites had a lot of easily detectable AI content. #SEOChat

Testing Stuff

I’ve seen a lot of back and forth volatility but nothing that seems long term (I think it was the HCU not the LSU) #SEOchat

Mordy Oberstein 

A2: Zero effect, didn’t check in detail as I have many borrowed properties.

I think it was the usual scare strategy!

Marco Giordano

A3: Give us a multiple choice option for this one ??

I think that amplification via news outlets, trusted industry sources, and other Google properties such as Scholars will play a bigger factor in determing link quality.

Sweepsify

I have always and will always not be fond of link building #SEOchat

Mordy Oberstein

A4: Semantic Clustering is one example cc

@LeeFootSEO Entity Extraction via pertained models is my most common use case though. Nowadays, I mostly use Analytics and rule-based approaches instead because they are 9/10 the best choices for many problems.

Marco Giordano

A4 Does training your content tools count?

Using machine learning to generate meta descriptions atm Working on many more use cases

Sweepsify

A4: Keyword research and XML sitemap audits In a nuthshell, I’m using it for descriptive analysis and especially pure analytics

Simone De Palma

Language structure. It should be “easy” (nothing is easy) to profile language structure. I think they already do for things like “first hand experience when reviewing a product” #SEOchat

Mordy Oberstein

A5: syntax as already said by Mordy.

Some patterns are not natural for most of us or can be too “off”.

There are other alternatives but I think this one is among the quickest.

The question is: will they really do it? We don’t know.

Marco Giordano

A5: A startup is already claiming they can do it https://siliconangle.com/2022/12/16/startup-says-can-reliably-detect-ai-generated-content/… I think Google will monitor these startups and then deploy their own internal tools

Sweepsify 

That is all for the section of SEO CHAT


Jeremy Rivera

Jeremy Rivera started in SEO in 2007, working at Advanced Access a hosting company for Realtors. He came up from the support department, where people kept asking "How do I rank in Google" and found in the process of answering that question an entire career. He became SEO product manager of Homes.com, went "in-house" at Raven Tools in Nashville in 2013. He then worked at several agencies like Caddis, 2 The Top Design as an SEO manager and then launched a 5 year freelance SEO career. During that time he consulted for large enterprise sites like Smile Direct Club, Dr. Axe, HCA, Logan's Roadhouse and Captain D's while also helping literally hundreds of small business owners get found in search results. He has authored blog posts at Authority Labs, Raven Tools, Wix, Search Engine Land. He has been a speaker at many SEO conferences like Craft Content and been interviewed in numerous SEO focused podcasts.