Ethan Lazuk

SEO/GEO & marketing professional.


Hamsterdam Part 45: SEO News Recap from 2/12 to 2/18, 2024

By Ethan Lazuk

Last updated:

A weekly look-back at SEO news, tips, and other content shared on social media & beyond.

Hamsterdam Part 45 SEO News Recap with quote from Danny Sullivan
Quote source: Google Search Liaison on X

Opening notes:

This week’s recap has a lot of great articles.

The introduction is about how Google Search is constantly testing, tying in a recent quote from Danny Sullivan plus a couple of Google Cloud articles relevant to how Search works.

I published a new blog post this week about alternative sources of content ideas beyond keyword research.

Wuffiyah hadn’t visited us in a while, so we took a rainy walk yesterday. Here’s a photo:

Wuffiyah walking in Lake Eola on a rainy day.

*Feel free to jump down to this week’s recap, or continue for an introduction and summary of the week’s news!

Introduction to week 45: “better for people”

How often do you update your website or its content?

“In 2022, we ran over 800,000 experiments that resulted in more than 4,000 improvements to Search.”

That’s a line from Google Search’s How Search works page about rigorous testing.

Specifically, it mentions 4,725 launches.

Google cartoon image showing comparison of search results.
Source: Google

Now, those were just tests that went live.

“Of the proposed changes this past year, many never went live, because unless we can show a change actually makes things better for people, we don’t launch it.”

In 2022, Google Search also ran 13,280 live traffic experiments involving real users.

“We enable the feature in question to just a small percentage of people, usually starting at 0.1%. We then compare the experiment group to a control group that did not have the feature enabled. We look at a very long list of metrics, such as what people click on, how many queries were done, whether queries were abandoned, how long it took for people to click on a result, and so on. We use these results to measure whether engagement with the new feature is positive, to ensure that the changes we make are increasing the relevance and usefulness of our results for everyone.” [Highlights added.]

What are these live experiments?

They’re the kind of things we share on social and Barry Schwartz reports in SERoundtable.

Search results on Search Engine Roundtable.

Perhaps the most notable experiment at the moment is Search Generative Experience (SGE).

Google announced SGE in May 2023, yet by January 2024 (8 months later), Google was still describing SGE as a “testbed for bold new ideas.”

As we can infer from the How Search works page (hopefully we’ll get 2023 data soon!), Google won’t push live a change unless it believes it will “actually make things better for people.”

As Roger Montti points out in a recent SEJ article about SGE:

“One of Google’s guiding principles for the use of AI is to only use it once the technology is proven to be successful and is implemented in a way that can be trusted to be responsible and those are two things that generative AI is not capable of today.”

He goes on to explain about Google’s use of AI in the background for years, including since 2015 with RankBrain.

On that front, I came across a pair of articles in Discover this week from Google Cloud that provide some information relevant to how Google Search works:

They specifically speak to the use of RAG (retrieval augmented generation), or information retrieval plus LLMs, in enterprise products like Vertex AI Search, “a fully managed platform for developers to build Google-quality search experiences for websites, structured and unstructured data.”

As SEOs, we often have to read between the lines, whether it’s in patents, Google Research papers, or, in this case, Google Cloud enterprise products.

Whether or not the technologies described in those articles are used exactly the same way in Google Search today, what matters is grasping their concepts for contextual knowledge.

Here are a few notable excerpts from both parts:

“Another common misconception is that semantic search is a relatively new innovation that has gained popularity with the rise of LLMs. While semantic search may be among the current hot topics, it’s actually the result of years of research and development. Google has been at the forefront of semantic search development for nearly a decade, starting with a strategic decision to invest in developing its family of custom, in-house AI processors back in 2013 — the Tensor Processing Unit (TPU). …”

“Beyond our expertise in semantic search, we have also spent over 25 years advancing keyword-based (or token-based) search technology. Vertex AI Search builds on this by providing a hybrid search engine that simultaneously performs both keyword and semantic searches for each query. The results are then merged and re-ranked based on their respective scores, combining the best aspects of both search approaches to fill in the gaps left by each. …”

“Approximate nearest neighbors (ANN) algorithms like ScaNN are proficient at quickly retrieving results in semantic search, but they are not as strong at scoring and ordering them precisely. Anyone who has ever used Google Search knows how important it is for the top results to be the most relevant to our queries and carefully sorted by relevance. …”

Hybrid search in Vertex AI Search from Google.
Source: Google

“That’s why modern semantic search engines use a two-stage retrieval approach to generate results. First, they use an ANN retriever to do a quick first pass and bring up results, and then apply a re-ranking model to fine-tune the results and make sure the most relevant ones are at the top — all in milliseconds. …”

The two staged retrieval approach from Google.
Source: Google

“At Google, we have been utilizing Knowledge Graph in Google Search since 2012, helping add more context to search queries by providing information about things, people, or places that Google already knows about. Google Search leverages Knowledge Graph to tap into its existing intelligence and understanding of the web to find and return results related to a user’s search query, such as landmarks, celebrities, cities, geographical features, movies, and more.”

Document and query annotation with Knowledge Graph relationships on Google
Source: Google
– Google Cloud, Your RAGs powered by Google Search technology, Parts 1 & 2

There are a few takeaways from all of this so far:

  • Google Search runs a lot of tests.
  • Google has a long history of using AI and semantic search technologies.
  • Updates to Google Search are for users’ benefit (for “everyone”).

When Danny Sullivan (Google Search Liaison) said this week that:

“Virtually everything someone asks about what Google wants, the touchstone is “Is this what your reader / audience wants?” Because that is what Google wants.”

“That’s the big picture. We want our systems to show content that people think will be satisfying. When they land on a page, they go “Yes! This is exactly what I want!” (And yes, our systems aren’t perfect. Yes, there’s unsatisfying content that can surface. It’s all something we’re working very hard to improve on).” [Highlights added.]

We can understand the impulse for that, as well as appreciate the myriad of ways that Google Search’s hard work “to improve” may be getting applied.

We can embrace this ourselves as SEOs.

Though I’m an independent consultant today, I spent 8+ years at agencies, and one consistent theme was a preference for new content rather than updating existing content.

Source: Yarn

However, newer websites or brands aside, I almost always make existing content optimization 50% or more of a content strategy.

On my website, I even take this to a crazy level. It’s not unusual for me to publish a blog post and then make 100+ revisions in days after.

But as I wrote about recently in a blog post (which I’ve already updated a ton), the question isn’t “Is this change good for SEO?” but rather “Is this change good for users, and how can we help Google’s ranking systems understand and reward us for it?”

One way to figure that out is to test, test, and test again.

Of course, it helps to keep track of when and where a change was made, so you can know if you’re moving in the right direction. 😉

Sometimes tests also have unintended consequences, as well.

Yet, from all of that testing, we can piece together themes.

One of the themes I’ve learned for my blog, for example, is to first write a post, then restructure it, usually by moving most of the introduction down to a conclusion.

Stay curious, buckle up for a full week’s recap, and enjoy the vibes:

Summary of the week’s SEO news and content

  • Danny Sullivan as Google Search Liaison on X gave suggestions for evaluating a traffic drop; also talked about misconceptions from the last helpful content update’s impact plus the system’s timing
  • OpenAI unveiled Sora AI model to create realistic video from text; also talk of a “web search product”
  • Google Search Console made some design changes; breaking a favorite Chrome extension of mine, but it’s back 🙂
  • European searchers may notice “more visual and entity focused results” on Google Search, given the legal environment
  • LOTs of talk about E-E-A-T, including new and updated posts
  • Enjoy!

Missed last week? Don’t worry, I got you! Read Part 44 to catch up.


Thank you for supporting Hamsterdam and helping make SEO accessible to all!

Ok, time for (home)work.

The Big Lebowski is this your homework Larry scene.

Jump to a section of this week’s recap

Or keep scrolling to see it all.

Also, feel free to support content you find valuable with a like, follow, or friendly comment.

Now, let’s step inside the white flags …

Top posts

These are highlights of news items, tips, or other content for the week. Great for when you just want a quick recap!

SEO news, Google updates, & SERP tests

These are newsworthy events in the SEO world, search engine updates, or SERP tests to be aware of from the last week.

SEO tips & tidbits

This section has actionable tips, cool tidbits, and other findings and observations that can be teaching moments.

SEO (and AI) fundamentals & resources

If you’re new to SEO, this section is for you and includes essential information, concepts, or resources to learn more.

The SEO checklist for beginners – Yoast

Yoast SEO checklist for beginners.

Articles, videos, case studies & more

These are longer-form content pieces shared on social and elsewhere.

Darwinism in Search: 10 Blue Links to Generative AI – Leanne Summers with Jason Barnard, Kalicube

Kalicube Darwinism in Search article.

Local SEO

If you’re into local Search, this section is for you!

Technical SEO

Everything from basics to advanced techniques.

Content marketing

What’d SEO be without helpful content?

Tools, AI & reporting

Here’s a recap of AI news, SEO tool updates, new tools, along with tips for reporting on data.

Humor

Humor is subjective; these are funny!

General Marketing & Miscellaneous

This is for great content that isn’t necessarily SEO or marketing-specific. PPC, PR, dev, design, and social friends, check it out!

Is user experience a machine learning problem? – Vednt Mathur, Bootcamp

Is user experience a machine learning problem? article.

Does anyone truly understand how AI works? – ai.explored (TikTok)

AI godfather video on TikTok.

Great job making it to the end. You rock!

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I’m an independent strategist and consultant based in Orlando, Florida, focusing on holistic SEO strategies for brands. Currently, I’m taking new clients for 2024!

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