SEO
7 Insights Into How Google Ranks Websites via @sejournal, @martinibuster
Google’s algorithm is built around understanding content and search queries and making the answers accessible to users in the most convenient manner.
These seven insights show how to develop a winning SEO and content strategy by leveraging what we know about Google’s algorithms.
The following are insights developed by studying patents and research papers published by Google itself.
Insight 1: Follow the Correct Intent
There are some content writing systems that mine the top-ranked websites and provide content writing and keyword suggestions based on the analysis of the top ten to top thirty webpages.
Some people who have used the software have told me that the information isn’t always helpful. And that’s not surprising because mining all of the top-ranked webpages in any given search results page (SERP) is going to result in a noisy data set that’s inaccurate and is of limited usefulness.
One of the issues with identifying user intent is that almost every query contains multiple user intents.
Advertisement
Continue Reading Below
Google solves this problem by showing links to webpages about the most popular user intents first.
For example, in a research study about automatically classifying YouTube channels (PDF), the researchers discuss the role of user intent in determining which results to show first.
In the below quote, where it uses the word “entity,” it’s a reference to what you normally think of as a noun (a person, a place, or a thing):
“A mapping from names to entities has been built by analyzing Google Search logs, and, in particular, by analyzing the web queries people are using to get to the Wikipedia article for a given entity…
For instance, this table maps the name Jaguar to the entity Jaguar car with a probability of around 45 % and to the entity Jaguar animal with a probability of around 35%.”
In plain English, that means researchers discovered that 45% of people who search for Jaguar are looking for information about the automobile and 35% are looking for information about the animal.
Advertisement
Continue Reading Below
That’s user intent that is segmented by popularity.
The takeaway here is that if your content is about selling a product and the top-ranked pages are about how to make that product then it may be possible that the popular user intent for that keyword is how to make that product and not where to buy that product.
That insight may mean that new content is needed to target the underlying “how to make” latent question that is inherent in that search query.
Insight 2: Link Ecosystem Has Changed
Blogging was at an all-time high twelve years ago. Many people were going online to churn out content and link out to interesting websites.
Aside from the recipe niche, that is no longer the case and that may be affecting the link signal that Google uses for ranking purposes. This is super important to think about.
Fewer People Searching for WordPress
There are fewer and fewer people searching for WordPress every year. This indicates that WordPress is declining in popularity in the general population.
The search volume for the keyword “WordPress” has declined by 71% since September 2011.
Fewer People Searching for Blogs
It’s not just WordPress usage that is going down. There are also fewer people searching for blogs, with a pattern that mirrors the decline in searches for WordPress.
The Link Ecosystem in Decline
There may be many reasons why blogging has declined in popularity.
It could be social media or it could be the introduction of the iPhone and Android changed how the public interacts online.
The Link Ecosystem Has Declined
One thing that is indisputable is that fewer people are blogging and the link ecosystem has suffered a strong decline. What caused it is beside the point.
Advertisement
Continue Reading Below
Gary Illyes of Google confirmed that the motivation for turning the nofollow link attribute directive into a hint was so that Google can use those links for ranking purposes.
“Yes. They had been missing important data that links had, due to nofollow. They can provide better search results now that they consider rel=nofollowed links into consideration.”
It’s not unreasonable to consider the use of nofollow links for ranking purposes was done because there are fewer natural links being generated.
With fewer links being naturally generated, it is highly likely that it’s going to affect how websites are ranked and that Google would be increasingly selective about the links it uses.
Today, it is increasingly clear that link strategies that rely on blog links are more easily detected as spam since fewer people are creating blogs.
The takeaway here is that when creating a link building strategy, it’s important to be aware that the link ecosystem is in decline.
Advertisement
Continue Reading Below
That means that freely given natural links are also in decline.
Link strategies must be more creative in terms of identifying who is left linking to websites and understanding why they are linking to websites.
Takeaway About Links
The time for being selective about getting links from so-called “authority” sites is long past.
Get what you can get as long as it is natural and freely given by any relevant website.
Insight 3: Link Drought Link Building Strategy
Because there are fewer natural links being freely given it’s time to rethink the race to obtain the right anchor text and massive amounts of links.
While a freely given link with a relevant anchor text is useful it’s rarely going to happen naturally.
So maybe it’s time to move away from old traditional link building focused on anchor text and guest posting (which today means paid links).
Instead, it may be useful to cultivate links from news and magazines, relevant organizations, and some educational organizations.
Advertisement
Continue Reading Below
Now more than ever it’s time to focus on outreach regardless of whether the outreach results in links. Just take the traffic.
Insight 4: Search Results Show What People Want to See
Ever walk down a supermarket cereal aisle and note how many sugar-laden kinds of cereal line the shelves? That’s user satisfaction in action. People expect to see sugar bomb cereals in their cereal aisle and supermarkets satisfy that user intent.
I often look at the Fruit Loops on the cereal aisle and think, “Who eats that stuff?” Apparently, a lot of people do, that’s why the box is on the supermarket shelf – because people expect to see it there.
Google is doing the same thing as the supermarket. Google is showing the results that are most likely to satisfy users, just like that cereal aisle.
Sometimes, that means showing newbie 101 level answers. Sometimes that means showing something incredibly racist and sad.
For example, in 2009, Google had to apologize for showing an image of Michelle Obama that was altered to resemble a monkey every time someone searched on her name.
Advertisement
Continue Reading Below
Why did Google show that result? Because most people searching on the name Michelle Obama were the kind of people who were satisfied seeing an image of her that resembled a monkey.
Click-through rates and other metrics of user satisfaction indicated that’s what people wanted to see. So Google’s user intent algorithm gave it to them.
Remember those sugar-laden cereals in the supermarket? That’s what those kinds of results are. It’s what I refer to as a “Fruit Loops algorithm,” a popularity-based algorithm that gives users what they expect to see.
Satisfying user intent is what Google means when they talk about showing relevant results. In the old days, it meant showing webpages that contained the keywords that a user typed. Now it means showing the webpage that most users expect to see.
Essentially, the search results pages are similar to the cereal aisle at your supermarket. That’s not a criticism, it’s an observation.
Advertisement
Continue Reading Below
I think it’s useful to think of the search results as a supermarket aisle and considering what kind of “cereal” is most popular. It may influence your content strategy in a positive way.
Insight 5: Expand the Range of Content
Google’s search results are biased to show the content that users expect to see.
This is why Google shows YouTube videos in the search results. It’s what people want to see.
It’s why Google shows featured snippets, it’s what satisfies the most people today who use mobile phones.
It’s not entirely accurate to complain that Google’s search results favor YouTube videos. People find video content useful, particularly for the how-to type of content. That’s why Google shows it.
It’s a bias in the search results, yes. But it’s a reflection of the users’ bias, not Google’s bias.
So if the user has a bias that favors YouTube videos, what should your online strategy response be?
Advertisement
Continue Reading Below
Write more content and build links to it? Or is the proper response to shift to the kind of content users want, in this case, video?
So if you see the search results are favoring a certain kind of content, pivot to producing that kind of content.
Learn to read the room in terms of what users want by paying close attention to what Google is ranking.
Insight 6: Drops in Ranking and NLP
Drops in ranking can sometimes be explained by a shift in how Google interprets what users mean when they search for something.
Google is increasingly using Natural Language Processing (NLP) algorithms which influences what Google believes users want when they search for something.
For example, I witnessed a near rewrite of what kind of content ranked at the top in a certain niche. Informational content zipped to the top, commercial content dropped to the bottom of the top 10.
There was nothing wrong with the commercial sites that dropped, other than how Google understood user intent changed.
Advertisement
Continue Reading Below
Trying to “fix” the commercial sites by adding more links, disavowing links, or adding more keywords to the page is unlikely to help the rankings.
Fixing something that isn’t broken never helps.
That’s why sometimes, it’s a good idea to study the search results first when diagnosing why a site lost ranking.
There might not be anything to fix. But there may be changes needing to be considered.
If your site has dropped in rankings, review what Google is ranking.
If the kinds of sites still ranking feature different content (focus, topic, etc) then the reason why your site dropped may not be about something that’s wrong.
It may be about something that needs changing.
Insight 7: Click Data Helps Determine User Intent
This is why I use the phrase “Fruit Loops Algo” to refer to Google’s user-intent-focused algorithm. It’s not meant as a slur. It’s meant to illustrate the reality of how Google’s search engine works.
Advertisement
Continue Reading Below
Many people want Fruit Loops and Captain Crunch breakfast cereals. The supermarkets respond by giving consumers what they want.
Search algorithms can operate in a similar manner.
A Better Definition of Relevance
That’s not keyword relevance to search terms you’re looking at — it’s relevance to what most users are expecting to see.
Sometimes that is expressed in how many links a site receives.
But I’m fairly confident that one of the ways user intent is understood is by click log data.
Here’s a patent filed by Google that discusses using click data to understand user intent, Modifying Search Result Ranking Based on Implicit User Feedback .
“Internet search engines aim to identify documents or other items that are relevant to a user’s needs and to present the documents or items in a manner that is most useful to the user. Such activity often involves a fair amount of mind-reading—inferring from various clues what the user wants.
…user reactions to particular search results or search result lists may be gauged, so that results on which users often click will receive a higher ranking. The general assumption under such an approach is that searching users are often the best judges of relevance, so that if they select a particular search result, it is likely to be relevant, or at least more relevant than the presented alternatives.”
Advertisement
Continue Reading Below
Understanding user intent is so important that Google and other search engines have developed eye-tracking and viewport time technologies to measure where on a search result mobile users are lingering. This helps to measure user satisfaction and understand user intent for mobile users.
Is Google or the User Biased Toward Brands?
Some people believe that Google has a big brand bias. But that’s not it at all.
If you consider this in light of what we know about Google’s algorithm and how it tries to satisfy user intent, then you will understand that if Google shows a big brand it’s because that is what users expect to see.
If you want to change that situation then you must create a campaign to build awareness for your site so that users begin to expect to see your site at the top.
Yes, links play a role in that. But other factors such as what users type into search engines also play a role.
Advertisement
Continue Reading Below
Someone once argued that Google should show results about the river when someone typed Amazon into Google. But that is unreasonable if what most people expect to see is Amazon the shopping site.
Again, Google is not matching keywords in that search query. Google is identifying the user intent and showing users what they want to see.
Key Takeaways
Understand the Search Results
The 10 links are not ordered by which page has the best on-page SEO or the most links. Those 10 links are ordered by user intent.
Write for User Intent
Understand what users want to accomplish and make that the focus of the content. Too often publishers write content focused on keywords, what some refer to as “semantically rich” content.
In 2015 I published an article about User Experience Marketing in which I proposed that focusing on user intent will put you in line with how Google ranks websites.
•What user intent is the content satisfying?
•What task or goal is the content helping the site visitor accomplish?”
Advertisement
Continue Reading Below
Understand Content Popularity
Content popularity is about writing content that can be understood by the widest audience possible. That means paying attention to the minimum grade level necessary for understanding your content.
If the grade level is high, this means your content may be too difficult for some users to understand.
I am not saying that Google prefers sites that a sixth-grader can understand. I am only stating that if you want to make your site easily understood by search engines and the most users, then paying attention to the difficulty of your content may be useful.
Google is not a keyword-matching search engine. Google is arguably a User Intent Matching Engine. Knowing and understanding this will improve everyone’s SEO.
There is a profound insight into understanding this and adapting your search marketing strategy to it.
Use What Is Known About Google’s Ranking Algorithms
Google publishes an astonishing amount of information about the algorithms used to rank websites. There are many other research papers that Google does not acknowledge whether or not the technology is in use.
Advertisement
Continue Reading Below
One can level up their SEO and marketing success by knowing what algorithms Google has admitted to using and what kinds of algorithms have been researched.
More Resources:
Featured image: Master1305/Shutterstock
SEO
How Compression Can Be Used To Detect Low Quality Pages
The concept of Compressibility as a quality signal is not widely known, but SEOs should be aware of it. Search engines can use web page compressibility to identify duplicate pages, doorway pages with similar content, and pages with repetitive keywords, making it useful knowledge for SEO.
Although the following research paper demonstrates a successful use of on-page features for detecting spam, the deliberate lack of transparency by search engines makes it difficult to say with certainty if search engines are applying this or similar techniques.
What Is Compressibility?
In computing, compressibility refers to how much a file (data) can be reduced in size while retaining essential information, typically to maximize storage space or to allow more data to be transmitted over the Internet.
TL/DR Of Compression
Compression replaces repeated words and phrases with shorter references, reducing the file size by significant margins. Search engines typically compress indexed web pages to maximize storage space, reduce bandwidth, and improve retrieval speed, among other reasons.
This is a simplified explanation of how compression works:
- Identify Patterns:
A compression algorithm scans the text to find repeated words, patterns and phrases - Shorter Codes Take Up Less Space:
The codes and symbols use less storage space then the original words and phrases, which results in a smaller file size. - Shorter References Use Less Bits:
The “code” that essentially symbolizes the replaced words and phrases uses less data than the originals.
A bonus effect of using compression is that it can also be used to identify duplicate pages, doorway pages with similar content, and pages with repetitive keywords.
Research Paper About Detecting Spam
This research paper is significant because it was authored by distinguished computer scientists known for breakthroughs in AI, distributed computing, information retrieval, and other fields.
Marc Najork
One of the co-authors of the research paper is Marc Najork, a prominent research scientist who currently holds the title of Distinguished Research Scientist at Google DeepMind. He’s a co-author of the papers for TW-BERT, has contributed research for increasing the accuracy of using implicit user feedback like clicks, and worked on creating improved AI-based information retrieval (DSI++: Updating Transformer Memory with New Documents), among many other major breakthroughs in information retrieval.
Dennis Fetterly
Another of the co-authors is Dennis Fetterly, currently a software engineer at Google. He is listed as a co-inventor in a patent for a ranking algorithm that uses links, and is known for his research in distributed computing and information retrieval.
Those are just two of the distinguished researchers listed as co-authors of the 2006 Microsoft research paper about identifying spam through on-page content features. Among the several on-page content features the research paper analyzes is compressibility, which they discovered can be used as a classifier for indicating that a web page is spammy.
Detecting Spam Web Pages Through Content Analysis
Although the research paper was authored in 2006, its findings remain relevant to today.
Then, as now, people attempted to rank hundreds or thousands of location-based web pages that were essentially duplicate content aside from city, region, or state names. Then, as now, SEOs often created web pages for search engines by excessively repeating keywords within titles, meta descriptions, headings, internal anchor text, and within the content to improve rankings.
Section 4.6 of the research paper explains:
“Some search engines give higher weight to pages containing the query keywords several times. For example, for a given query term, a page that contains it ten times may be higher ranked than a page that contains it only once. To take advantage of such engines, some spam pages replicate their content several times in an attempt to rank higher.”
The research paper explains that search engines compress web pages and use the compressed version to reference the original web page. They note that excessive amounts of redundant words results in a higher level of compressibility. So they set about testing if there’s a correlation between a high level of compressibility and spam.
They write:
“Our approach in this section to locating redundant content within a page is to compress the page; to save space and disk time, search engines often compress web pages after indexing them, but before adding them to a page cache.
…We measure the redundancy of web pages by the compression ratio, the size of the uncompressed page divided by the size of the compressed page. We used GZIP …to compress pages, a fast and effective compression algorithm.”
High Compressibility Correlates To Spam
The results of the research showed that web pages with at least a compression ratio of 4.0 tended to be low quality web pages, spam. However, the highest rates of compressibility became less consistent because there were fewer data points, making it harder to interpret.
Figure 9: Prevalence of spam relative to compressibility of page.
The researchers concluded:
“70% of all sampled pages with a compression ratio of at least 4.0 were judged to be spam.”
But they also discovered that using the compression ratio by itself still resulted in false positives, where non-spam pages were incorrectly identified as spam:
“The compression ratio heuristic described in Section 4.6 fared best, correctly identifying 660 (27.9%) of the spam pages in our collection, while misidentifying 2, 068 (12.0%) of all judged pages.
Using all of the aforementioned features, the classification accuracy after the ten-fold cross validation process is encouraging:
95.4% of our judged pages were classified correctly, while 4.6% were classified incorrectly.
More specifically, for the spam class 1, 940 out of the 2, 364 pages, were classified correctly. For the non-spam class, 14, 440 out of the 14,804 pages were classified correctly. Consequently, 788 pages were classified incorrectly.”
The next section describes an interesting discovery about how to increase the accuracy of using on-page signals for identifying spam.
Insight Into Quality Rankings
The research paper examined multiple on-page signals, including compressibility. They discovered that each individual signal (classifier) was able to find some spam but that relying on any one signal on its own resulted in flagging non-spam pages for spam, which are commonly referred to as false positive.
The researchers made an important discovery that everyone interested in SEO should know, which is that using multiple classifiers increased the accuracy of detecting spam and decreased the likelihood of false positives. Just as important, the compressibility signal only identifies one kind of spam but not the full range of spam.
The takeaway is that compressibility is a good way to identify one kind of spam but there are other kinds of spam that aren’t caught with this one signal. Other kinds of spam were not caught with the compressibility signal.
This is the part that every SEO and publisher should be aware of:
“In the previous section, we presented a number of heuristics for assaying spam web pages. That is, we measured several characteristics of web pages, and found ranges of those characteristics which correlated with a page being spam. Nevertheless, when used individually, no technique uncovers most of the spam in our data set without flagging many non-spam pages as spam.
For example, considering the compression ratio heuristic described in Section 4.6, one of our most promising methods, the average probability of spam for ratios of 4.2 and higher is 72%. But only about 1.5% of all pages fall in this range. This number is far below the 13.8% of spam pages that we identified in our data set.”
So, even though compressibility was one of the better signals for identifying spam, it still was unable to uncover the full range of spam within the dataset the researchers used to test the signals.
Combining Multiple Signals
The above results indicated that individual signals of low quality are less accurate. So they tested using multiple signals. What they discovered was that combining multiple on-page signals for detecting spam resulted in a better accuracy rate with less pages misclassified as spam.
The researchers explained that they tested the use of multiple signals:
“One way of combining our heuristic methods is to view the spam detection problem as a classification problem. In this case, we want to create a classification model (or classifier) which, given a web page, will use the page’s features jointly in order to (correctly, we hope) classify it in one of two classes: spam and non-spam.”
These are their conclusions about using multiple signals:
“We have studied various aspects of content-based spam on the web using a real-world data set from the MSNSearch crawler. We have presented a number of heuristic methods for detecting content based spam. Some of our spam detection methods are more effective than others, however when used in isolation our methods may not identify all of the spam pages. For this reason, we combined our spam-detection methods to create a highly accurate C4.5 classifier. Our classifier can correctly identify 86.2% of all spam pages, while flagging very few legitimate pages as spam.”
Key Insight:
Misidentifying “very few legitimate pages as spam” was a significant breakthrough. The important insight that everyone involved with SEO should take away from this is that one signal by itself can result in false positives. Using multiple signals increases the accuracy.
What this means is that SEO tests of isolated ranking or quality signals will not yield reliable results that can be trusted for making strategy or business decisions.
Takeaways
We don’t know for certain if compressibility is used at the search engines but it’s an easy to use signal that combined with others could be used to catch simple kinds of spam like thousands of city name doorway pages with similar content. Yet even if the search engines don’t use this signal, it does show how easy it is to catch that kind of search engine manipulation and that it’s something search engines are well able to handle today.
Here are the key points of this article to keep in mind:
- Doorway pages with duplicate content is easy to catch because they compress at a higher ratio than normal web pages.
- Groups of web pages with a compression ratio above 4.0 were predominantly spam.
- Negative quality signals used by themselves to catch spam can lead to false positives.
- In this particular test, they discovered that on-page negative quality signals only catch specific types of spam.
- When used alone, the compressibility signal only catches redundancy-type spam, fails to detect other forms of spam, and leads to false positives.
- Combing quality signals improves spam detection accuracy and reduces false positives.
- Search engines today have a higher accuracy of spam detection with the use of AI like Spam Brain.
Read the research paper, which is linked from the Google Scholar page of Marc Najork:
Detecting spam web pages through content analysis
Featured Image by Shutterstock/pathdoc
SEO
New Google Trends SEO Documentation
Google Search Central published new documentation on Google Trends, explaining how to use it for search marketing. This guide serves as an easy to understand introduction for newcomers and a helpful refresher for experienced search marketers and publishers.
The new guide has six sections:
- About Google Trends
- Tutorial on monitoring trends
- How to do keyword research with the tool
- How to prioritize content with Trends data
- How to use Google Trends for competitor research
- How to use Google Trends for analyzing brand awareness and sentiment
The section about monitoring trends advises there are two kinds of rising trends, general and specific trends, which can be useful for developing content to publish on a site.
Using the Explore tool, you can leave the search box empty and view the current rising trends worldwide or use a drop down menu to focus on trends in a specific country. Users can further filter rising trends by time periods, categories and the type of search. The results show rising trends by topic and by keywords.
To search for specific trends users just need to enter the specific queries and then filter them by country, time, categories and type of search.
The section called Content Calendar describes how to use Google Trends to understand which content topics to prioritize.
Google explains:
“Google Trends can be helpful not only to get ideas on what to write, but also to prioritize when to publish it. To help you better prioritize which topics to focus on, try to find seasonal trends in the data. With that information, you can plan ahead to have high quality content available on your site a little before people are searching for it, so that when they do, your content is ready for them.”
Read the new Google Trends documentation:
Get started with Google Trends
Featured Image by Shutterstock/Luis Molinero
SEO
All the best things about Ahrefs Evolve 2024
Hey all, I’m Rebekah and I am your Chosen One to “do a blog post for Ahrefs Evolve 2024”.
What does that entail exactly? I don’t know. In fact, Sam Oh asked me yesterday what the title of this post would be. “Is it like…Ahrefs Evolve 2024: Recap of day 1 and day 2…?”
Even as I nodded, I couldn’t get over how absolutely boring that sounded. So I’m going to do THIS instead: a curation of all the best things YOU loved about Ahrefs’ first conference, lifted directly from X.
Let’s go!
OUR HUGE SCREEN
The largest presentation screen I’ve ever seen! #ahrefsevolve pic.twitter.com/oboiMFW1TN
— Patrick Stox (@patrickstox) October 24, 2024
This is the biggest presentation screen I ever seen in my life. It’s like iMax for SEO presentations. #ahrefsevolve pic.twitter.com/sAfZ1rtePx
— Suganthan Mohanadasan (@Suganthanmn) October 24, 2024
CONFERENCE VENUE ITSELF
It was recently named the best new skyscraper in the world, by the way.
The Ahrefs conference venue feels like being in inception. #AhrefsEvolve pic.twitter.com/18Yjai1Cej
— Suganthan Mohanadasan (@Suganthanmn) October 24, 2024
I’m in Singapore for @ahrefs Evolve this week. Keen to connect with people doing interesting work on the future of search / AI #ahrefsevolve pic.twitter.com/s00UkIbxpf
— Alex Denning (@AlexDenning) October 23, 2024
OUR AMAZING SPEAKER LINEUP – SUPER INFORMATIVE, USEFUL TALKS!
A super insightful explanation of how Google Search Ranking works #ahrefsevolve pic.twitter.com/Cd1VSET2Aj
— Amanda Walls (@amandajwalls) October 24, 2024
“would I even do this if Google didn’t exist?” – what a great question to assess if you actually have the right focus when creating content amazing presentation from @amandaecking at #AhrefsEvolve pic.twitter.com/a6OKbKxwiS
— Aleyda Solis ️ (@aleyda) October 24, 2024
Attending @CyrusShepard ‘s talk on WTF is Helpful Content in Google’s algorithm at #AhrefsEvolve
“Focus on people first content”
Super relevant for content creators who want to stay ahead of the ever evolving Google search curve! #SEOTalk #SEO pic.twitter.com/KRTL13SB0g
This is the first time I am listening to @aleyda and it is really amazing. Lot of insights and actionable information.
Thank you #aleyda for power packed presentation.#AhrefsEvolve @ahrefs #seo pic.twitter.com/Xe3A9MGfrr
— Jignesh Gohel (@jigneshgohel) October 25, 2024
— Parth Suba (@parthsuba77) October 24, 2024
@thinking_slows thoughts on AI content – “it’s very good if you want to be average”.
We can do a lot better and Ryan explains how. Love it @ahrefs #AhrefsEvolve pic.twitter.com/qFqWs6QBH5
— Andy Chadwick (@digitalquokka) October 24, 2024
A super insightful explanation of how Google Search Ranking works #ahrefsevolve pic.twitter.com/Cd1VSET2Aj
— Amanda Walls (@amandajwalls) October 24, 2024
This is the first time I am listening to @aleyda and it is really amazing. Lot of insights and actionable information.
Thank you #aleyda for power packed presentation.#AhrefsEvolve @ahrefs #seo pic.twitter.com/Xe3A9MGfrr
— Jignesh Gohel (@jigneshgohel) October 25, 2024
GREAT MUSIC
First time I’ve ever Shazam’d a track during SEO conference ambience…. and the track wasn’t even Shazamable! #AhrefsEvolve @ahrefs pic.twitter.com/ZDzJOZMILt
— Lily Ray (@lilyraynyc) October 24, 2024
AMAZING GOODIES
Ahrefs Evolveきました!@ahrefs @AhrefsJP #AhrefsEvolve pic.twitter.com/33EiejQPdX
— さくらぎ (@sakuragi_ksy) October 24, 2024
Aside from the very interesting topics, what makes this conference even cooler are the ton of awesome freebies
Kudos for making all of these happen for #AhrefsEvolve @ahrefs team pic.twitter.com/DGzk5FSTN8
— Krista Melgarejo (@kimelgarejo) October 24, 2024
Content Goblin and SEO alligator party stickers are definitely going on my laptop. @ahrefs #ahrefsevolve pic.twitter.com/QBsBuY5Yix
— Patrick Stox (@patrickstox) October 24, 2024
This is one of the best swag bags I’ve received at any conference!
Either @ahrefs actually cares or the other conference swag bags aren’t up to par w Ahrefs!#AhrefsEvolve pic.twitter.com/Yc9e6wZPHn— Moses Sanchez (@SanchezMoses) October 25, 2024
SELFIE BATTLE
Some background: Tim and Sam have a challenge going on to see who can take the most number of selfies with all of you. Last I heard, Sam was winning – but there is room for a comeback yet!
Got the rare selfie with both @timsoulo and @samsgoh #AhrefsEvolve
— Bernard Huang (@bernardjhuang) October 24, 2024
THAT BELL
Everybody’s just waiting for this one.
@timsoulo @ahrefs #AhrefsEvolve pic.twitter.com/6ypWaTGDDP
— Jinbo Liang (@JinboLiang) October 24, 2024
STICKER WALL
Viva la vida, viva Seo!
Awante Argentina loco!#AhrefsEvolve pic.twitter.com/sfhbI2kWSH
— Gaston Riera. (@GastonRiera) October 24, 2024
AND, OF COURSE…ALL OF YOU!
#AhrefsEvolve let’s goooooooooooo!!! pic.twitter.com/THtdvdtUyB
— Tim Soulo (@timsoulo) October 24, 2024
–
There’s a TON more content on LinkedIn – click here – but I have limited time to get this post up and can’t quite figure out how to embed LinkedIn posts so…let’s stop here for now. I’ll keep updating as we go along!