🐹 Hamsterdam Part 64: Weekly SEO & AI News Recap (6/24 to 6/30, 2024) – (N64 Nostalgia Edition 🕹️)
By Ethan Lazuk
Last updated:
A weekly look-back at SEO & AI news, tips, and other content shared on social media & beyond.
Opening notes, thoughts, and musings:
- Welcome to another week of Hamsterdam! 🐹
- I’ve figured out how to use WP’s full emoji suite. Expect greatness. 🔥
- I appreciate you being here, and look forward to sharing the week’s news! 🙌
- Fancy a longer read? Check out the Hamsterdam Marketing article from this week:
- 🦄 “Unicorn” Clicks & the Magic of Etymology for SEO Research
- Bonus: I’ve created a page with my TikTok finds of the week (a little of everything)
We also deliver! — Check out the Hamsterdam newsletter. Hot and ready in 30 minutes or less 🍕, or sent out every Sunday. (One of the two.)
If you’re in a rush, jump down to the news portion. 🗞️
Or continue reading for two vocabulary lessons, this week in SEO Nintendo history 🕹️, plus an introduction. (Don’t forget to click the dropdowns.)
And we’re off …
🧑🎨 Marketing word of the week: “Guerrilla marketing”
Guerrilla marketing is an advertising and publicity strategy that attempts to maximize exposure for a product or service using innovative, unconventional, and/or low-cost methods.
Elements of guerrilla marketing include creativity, imagination, and originality. These can compensate for a lack of a large marketing budget or abundant resources.
However, big brands do it, too.
You might’ve heard Jay-Z’s music closing out this year’s Google I/O event.
However, back in 2010, Bing teamed up with Jay-Z to create Decoded, an interactive marketing campaign that involved a scavenger hunt and a mix of art and technology.
🚨 ⬇️ Click to continue reading about examples of guerrilla marketing tactics, plus my proposed name change (if you want 😎).
While guerrilla marketing sounds cute, the origins come from guerrilla “warfare,” a military strategy that involves unconventional tactics. Thus, I’m proposing it’s high-time we relabel it. (For the record, I’m not anti-guerrilla. 🦍 Just not big on promulgating war motifs. 💐 ✌️)
We could describe guerrilla marketing campaigns as scrappy, thrifty, or resourceful.
However, I personally like the term “Mild West Marketing.”
This would be an homage to Banksy, the underground artist who uses unconventional placements and thought-provoking imagery for social commentary — “The Mild Mild West” was one of his first well-known pieces, a mural created in 1997 in Bristol, England. 🧸
It’d also be a play on the words “Wild West,” an era in U.S. history (post-Civil War) defined by expansion and ingenuity in less-regulated environments of the western frontier:
Where we also had the preexistence of thousands of years of indigenous culture:
(By the way, if you’re into cultural history and haven’t checked out Daniel J. Boorstin, I recommend his work, particularly “The Americans: The Democratic Experience.”)
The goals of mild west marketing (our new name for guerrilla marketing) are to grow awareness for a business or brand while also differentiating it from its competitors and connecting with potential customers in a memorable way.
Notable examples of mild west (guerrilla) marketing tactics include:
- Street marketing (street art)
- Ambient marketing (placing ads in unconventional places, creating awareness by interrupting the flow)
- Ambush marketing (taking advantage of an existing audience for another product or service; but since this one is also tied to violence, let’s relabel it “symbiotic marketing,” a term from biology where one species either benefits from another without harming or benefitting it (commensal) or both benefit (symbiotic). There’s also parasitic, a relationship we SEOs know from “site reputation abuse” spam.)
- Projections (hidden projectors on high-rise buildings)
- Experiential marketing (creating immersive experiences in real-life settings)
- Viral marketing (socially viral content — good luck planning that!) 😅
For guerrilla marketing — oops, see how hard it is to relabel something! — for mild west marketing to be effective, above all, it has to have authenticity.
Consumers are smart. They appreciate what’s clever. They see through what’s obvious.
Another necessary component, of course, is to have a distinctly recognizable brand. (Did I mention SEO can help establish, sustain, and grow that brand. More in our introduction below.) 💪
⛷️ AI word of the week: “Gradient descent”
This week’s vocabulary being “G” words, we might be expected to go with “generative AI.”
However, gradient descent is pretty cool. 🤗
Recall in last week’s recap how we featured an interview with Perplexity’s CTO, Denis Yarats, who was on a Weights & Biases podcast called “Gradient Dissent.” Those words will take on more context for us shortly.
Gradient descent is an optimization algorithm that is fundamental to machine learning — but also “older—much, much older,” as Google reminds us, with roots in calculus from centuries ago.
Gradient descent works by iteratively seeking the minimum value of a mathematical function. In machine learning, that function is a loss function (cost function), or the model’s error, as measured by the distance from the ideal output (based on training data) to the model’s actual output. 🎢
To use an analogy, think of gradient descent like a hiker in a fog. 🥾
They’re unable to see the full landscape 😶🌫️, but they can feel below their feet one step at a time which direction is up or down. 🗻
The hiker moves down toward the nearest valley (local minimum). However, their ideal destination (though perhaps impossible to reach) is the lowest point of the landscape overall (the global minimum) representing a perfectly trained model.
In mathematical terms, the gradient is the steepness of the hiker’s steps. It’s a vector that points in the steepest direction of a function at a particular point, either positive or negative. As its name implies, gradient descent is about finding the negative, or descending, direction.
🚨 ⬇️ Click to continue reading about parameters, backpropagation, and types of gradient descent (if you want 😎).
The size of the step taken in each iteration during gradient descent is determined by a hyperparameter called the learning rate (a value set before training).
Have you heard of neural networks having parameters? They’re often described as being like little knobs that get turned to adjust a model.
Well, parameters actually refers to weights (strengths of connections between neurons) and biases (unaltered baseline activation levels for each neuron).
Backpropagation is an algorithm that neural networks use to compute the gradients needed for gradient descent. With respect to the loss function for each parameter (weight and bias), backprop gives the direction and magnitude of change needed.
That’s the turning of the knobs, so to speak.
The gradient descent algorithm then uses the gradients computed with backprop to update the model’s parameters and minimize its loss function. The larger the learning rate, the larger the updates to the weights and biases (steeper the descent).
There are different approaches to the gradient descent method.
In stochastic gradient descent (SGD), the gradient is computed using a random subset (small batch) of the data, rather than calculating the gradient over an entire dataset.
SGD can introduce noise, but it also speeds up learning (accelerating convergence, or the set of model parameters (weights and biases) that result in the minimum value of the loss function) and helps avoid getting stuck in local minima (solutions that may appear to be the lowest but aren’t the lowest overall).
Momentum can be added to gradient descent to help the algorithm navigate through areas with small but consistent gradients (think of a ball rolling down a hill, hitting a flat spot, but continuing to roll with momentum).
Momentum adds a fraction of the previous update vector to the current update (like taking the history of the past iteration into account).
To sum it up, think of gradient descent as an algorithm used to optimize machine learning models and neural networks (but it has deeper roots in calculus from centuries ago).
Gradient descent guides a model towards better performance by gradually reducing its error (loss function) through incremental adjustments to parameters (weights and biases), taking steps in a negative direction toward the best local minimum (and ideally a global minimum).
Ain’t nuthin’ but a G thang. 🐕
👾 Nostalgic history: Nintendo 64 (1996)
We ordinarily learn SEO history in this section, but being this is Part 64 of Hamsterdam, let’s celebrate with some Nintendo 64 history. 🎉
Nintendo 64 was released in the U.S. market in 1996. It was the third major video game console from Nintendo (and the first console in my household). 🕹️
You can relive the era in this CBS local news story:
The N64 project began at Nintendo three years earlier as “Project: Reality” (1993), aimed at taking gaming further into the 3D realm.
On that point, the name “N64” comes from the console’s 64-bit CPU and GPU (the type of graphics card some ML models run on today).
Prior to N64, Nintendo had SNES (Super Nintendo Entertainment System), a 16-bit console.
Here’s a graphics comparison, highlighting the 3D aspects of N64 game play:
🚨 ⬇️ Click to continue reading about N64 cartridges, game titles, plus a modern comparison (if you want 😎).
One quirk of N64 was Nintendo’s decision to go with cartridges over CDs. Their argument was the cartridges’ practicality and better loading times …
📢 PSA: don’t blow into your game cartridges.
As AI Overviews summarizes below, moisture and electronics don’t jive 🔌 😅 ⚡️:
No sweat, I’ve got your cred, sources 🤛:
Cartridges aside, N64 had several legendary games. 🙌
Super Mario 64 came with the console, as I remember it. (More on Toys-R-Us in the recap later.)
Other bangers included GoldenEye 007 🔫, Star Fox 64 🦊, and Star Wars: Shadows of the Empire ☄️. (There was also a game about a wizard with a green hat or something.) 🧙
But they’re all eclipsed by Mario Kart 64. No arguments. 🍌 🏁
My N64 is currently sitting in a cabinet in our kitchen, but if you have an iPhone, you can use a simulator and … 🤫
For comparison, here’s how Mario Kart 8 Deluxe looks on Nintendo Switch today:
Interestingly, it’s the same price as Super Mario 64 was in 1996, per the ad earlier.
🌐 Introduction to week 64: Perspectives
Back in January, I wrote a blog post about Google’s Perspectives filter and carousel.
A few months later, I had to rewrite most of it and cross out the “filter” part, as Google had replaced it with a “Forums” filter.
More broadly, though, the idea of perspectives (and different types of content to build a brand around) feels like it’s picking up steam as a topic in the SEO realm.
Or as OGs might say: it’s called “marketing.” 🤯
That said, as I’m sure was true for some other folks, my introduction to SEO was focused on relevance signals, not users.
Mike King referenced something in an iPullRank webinar this week that struck a nostalgic chord:
“So this one is a bit of a funny one to me because, you know, I’ve been in SEO since back when you would bold every instance of your target keyword on the page or you would italicize it or whatever because those were all different semantic signals to indicate to Google like this is an important aspect of the page”
– Mike King, “The Google Algo Leak” (38:32 mark). (My formatting of the YouTube transcript.)
I was taught that in my nascent days as a content strategist.
I was even demanded to put long-tail keywords in content verbatim, even when they didn’t fit the syntax!
(Sentence structure … I’ve been reading more about linguistics lately, so I’m on that kick. I’ve included a cool presentation on the topic later in the recap, as well.)
Funny story on that, real quick: a client (not an account I worked on, for the record) once came into the agency to talk about their website. “Would anyone understand this if they read it?”
😳 🤦
It wasn’t until I started working at a full-service agency and was introduced to different marketing channels, larger clients, and a manager who read Google’s webmaster guidelines that things changed (and my interest in SEO really started).
I don’t mind that it’s more challenging today to report on organic visibility and conversions, given the diversity of user journeys across search and AI agents. (I’ve found clients are generally ok with that, too, if explained in a holistic context, and they see sales.)
I want to create stuff that people want to engage with, and help businesses do the same.
Which brings us back to this idea of perspectives, and marketing.
This week felt like it had a lot of good discussions, or maybe I just noticed them more. 🤷
Either way, here’s a review (mostly chronological):
I wandered into iPullRank’s webinar, “The Google Algo Leak,” a few minutes late, but caught most of it.
It went in-depth on the API Content Warehouse, with information I found interesting and valuable.
Here’s an excerpt from near the end:
“Effectively build a brand around what you’re trying to do so that they recognize your brand and they know that you’re the result that they need to click on and stay on.”
– Mike King (1:03:16 mark). (My formatting of the YouTube transcript.)
(Of course, I encourage you to check out that webinar and the other resources I’ll be mentioning here in full to get the entire context.) 😁
But my day didn’t end there.
Immediately after that, I attended another live broadcast on Zoom called “APL: WTF is Going on with SEO?” featuring John-Henry Scherck.
I wasn’t familiar with AudiencePlus prior, but I saw John-Henry reference the event in a tweet. (I didn’t see the recording link, but I’ll add it if it becomes available. Until then, here’s more AudiencePlus content you can check out.)
I also found that APL broadcast to be full of valuable information.
Listening to those two discussions back to back was also super interesting.
The topic of the leak was discussed from different perspectives, for example, but my takeaway was quite clear:
Do great marketing.
It didn’t stop there, either.
The Google Search Central team dropped a SOTR podcast episode with Elizabeth Tucker. (The video’s description on YouTube links to a 2019 BERT paper from Google AI Language, if that tells you something.)
Here’s an excerpt:
“Getting those insights from people who are actually using Search at an everyday level to do important tasks, that is one of the superpowers from our UXR team. From our Data Science team, we get these broad scale measurements, so we can slice and dice to figure out quantitatively how can we identify where we’re not doing well. When we run an experiment, how can we tell whether we’re making things better or worse? Both work together really synergistically to help us understand and improve the experience for people who come to Google.”
– Elizabeth Tucker, SOTR Ep. 76 (6:18 mark).
In a similar vein, I also stumbled on a blog post from Camille Cunningham at Yoast, “Is OSO, organic search optimization, the new SEO?“
Here’s an excerpt:
“This shift might cause you some worries regarding time management, but it also means that you can spend less time diving into data as this is becoming less important. So save time by obsessing a bit less over the numbers and invest that time in researching your audience and creating new (and fun) ways to reach them.”
– Camille Cunningham, Yoast
That post is a little higher level, but the point goes back to the previous idea of working “synergistically” with qualitative and quantitative data as part of great marketing.
Then, Marie Haynes put out an insightful post this week called “Does Google know if content is accurate?” It also has a video in it where she looks at web content through a searcher’s POV, which I recommend watching, as well.
In one example from the article, she mentions ideas like:
“experiment with different types of content on this page”
– Marie Haynes, “Does Google know if content is accurate?”
While in the video, she explores several topics, including brand preferences.
On that note, there was also a great post this week from Jason Barnard in SEL, building on a concept espoused by Bing’s Fabrice Canel of the “perfect click”:
Here’s a line from the article:
“The key to optimizing for Google’s AI Overviews: Build the traditional marketing funnel.”
– Jason Barnard, SEL
And to round us out (pun intended), here’s an SE Ranking webinar with Julia McCoy and Barry Schwartz:
Here’s an excerpt from one of Julia’s answers:
“We’re looking at this from a brand perspective, and I think that’s a way every publisher can win right now is how do I make my brand last longer, go further, build more trust. You can’t go wrong no matter what is happening with search if you ask that question, ‘How do I get my brand to resonate more with my audience?’”
– Julia McCoy (26:33 mark). (My formatting of the YouTube transcript.)
We’ve just reviewed a variety of authoritative perspectives relevant to SEO strategy.
One thing we learned for sure: webinars are a ranking factor.
No, I’m kidding! (Traffic diversity isn’t a ranking factor.)
It’s just great marketing.
Or as OGs might say: that’s called “SEO.”
Buckle up for a full week’s recap, and enjoy the vibes:
Thank you for supporting Hamsterdam and the cause of SEO & AI learning.
Missed last week? Don’t worry, I got you! Read Part 63 to catch up.
🌟 Other great sources of weekly SEO news:
- The SEO Weekly – Garret Sussman, iPullRank
- SEOFOMO – Aleyda Solis
- Weekly Video Recaps – Barry Schwartz, SER
- Weekly SEO News YouTube channel – Olga Zarr, Seosly
- Niche Surfer – Yoyao Hsueh
Time for our weekly review of SEO social posts, articles, & more …
⚡️ Quick summary:
- Google is bringing back page 2 (doing away with infinite scroll)
- Google’s June 2024 spam update concluded after 7 days (core update incoming – just a guess, based on an observation from this older article that I need to update)
- Gary Illyes gave a number of tech SEO tips on LinkedIn around (soft) 404s (see technical section)
- 🔥 Pick of the week: Google Search Central SOTR podcast with Elizabeth Tucker on search quality (be sure to check out the links in the description! Several gems) 💎
- 🐿️ Sneaky pick: “What Happened to People Magazine?” by Anne Helen Petersen, giving a more cultural/academic perspective on (debatably) search engine-first content — while the author isn’t an SEO but is writing about SEO (and I didn’t see any SEOs quoted …), I find value and even inspiration in
all(ok, most) outside opinions) 🤔 - 🧨 Dynamite bonus pick: Doug Turnbull’s 50 things AI engineers should know about search (must read) (h/t Dawn Anderson on LI)
- And ICYM the introduction above, those are all great sources to check out, too!
- And there’s lots more below!
⏩ Jump to a section:
- News, Google updates, & SERP tests
- SEO tips & tidbits
- Fundamentals & resources
- Articles, videos & case studies
- Local SEO
- Technical SEO
- Content marketing
- Local SEO
- Data analysis & reporting
- AI, LLMS, & machine learning
- Miscellaneous & general posts
- Older stuff that’s good!
Or keep scrolling to see it all.
Now, let’s step inside the white flags of Hamsterdam …
📰 SEO news, Google updates, SERP tests & notable posts
Notable updates or news related to Google Search or related SEO topics.
🍟 SEO tips & tidbits
Actionable tips, cool tidbits, and other snackable findings and observations that can be teaching moments.
Excerpt (from the Wix guide): “Introduced by Google back in 2012 (although now adopted almost universally by other search engines as well), knowledge panels do a lot more than display information about a person or brand. They’re a way to connect entities so that search engines can understand how these concepts are related to each other.”
Essential information, concepts, or resources to learn about SEO or AI.
Longer-form content pieces shared on social, in newsletters, and elsewhere.
🧑💻 Technical SEO
Everything from basics to advanced moves (and also tools).
✍️ Content marketing
From what is helpful content to user journeys and beyond.
What Happened to People Magazine? – Anne Helen Petersen, Culture Study
📍 Local SEO
From Google Business Profiles or reviews and more!
Local Search Is Evolving, Here’s Why You Need to Pay Attention – Mike Blumenthal, Near Media
📊 Data analysis & reporting
Showing that what you’re doing is helping.
🤖 AI, machine learning, & LLMs
News related to models, papers, and companies.
Excerpt: “Evaluation methods all have different biases. In human evaluators we have issues dealing with non-experts, people getting exhausted, people preferring earlier results as more relevant than later results, etc … In clickstream based judgments, we have other issues! We only get labels for results the search system returns in the top N (stuff that can be clicked on). And we deal with people’s lizard brains clicking on irrelevant, spicy pictures. … Combining and weighing different fields is important. Fields in search play different roles, and need to be tokenized and scored differently. Like prioritizing a title match over something buried deep in a body … Search exists in an ecosystem – one of the best search hacks is to convince our users to SEO their content for search. They’ll tune their content towards our search, rather than us needing to tune their algorithm for their bad content. …” — and lots more! Note: h/t Dawn Anderson (on LI)
What are AI Agents?- Agents in Artificial Intelligence Explained – Navan
License to Call: Introducing Transformers Agents 2.0 – Aymeric Roucher, Lysandre, Pedro Cuenca, Hugging Face
🤔 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!
Toys ‘R’ Us AI-Generated Ad – Perplexity Team
The AI Era: Expanding marketing and creative potential – Vidhya Srinivasan, Think with Google
Note: Check out the tools linked in the article. Pretty cool! (Btw, for another perspective, check out this scene from Season 2, Episode 7 of The Wire (2003): “Can’t get hurt if you ain’t working.”
Four Main Linguistic School of Thought by Echavez, Cristy Joy
How Generative AI is impacting Developer Productivity? – Aravind Putrevu, (Middleware) Dev.to
📱 Mobile product page design 101 – Oliver Kenyon, ConversionMail
💎 Older stuff that’s good!
Not everything I find worth sharing is new as of this week, so these are gems I came across published in the past.
BERT: How Do Vectors Accurately Describe the Meaning of Words? – Gerhard Paaß, Lamarr Institute
Design systems 102: How to build your design system – Chad Bergman, Figma
Great job making it to the end. You rock! 🙌
🤝 Want help with your SEO strategy?
I’m an independent SEO consultant focusing on custom audits and holistic strategies for brands. Don’t hesitate to reach out, or visit my about page for more information.
Let’s connect!
Hit me up anytime via text or call at 813-557-9745 or on social or email:
Cheers! ✌️
Leave a Reply