SEO
The 9 Most Important SEO KPIs You Should Be Tracking
If you ask 10 SEOs what their top SEO Key Performance Indicators (KPIs) are, you’ll likely receive 10 different answers.
The reason is that KPIs are situational; they are specific to each type of business.
Accordingly, the following are nine KPIs that can be considered important for a wide variety of online monetization models.
An interesting thing about KPIs is that KPIs aren’t always metrics that show where you are winning. They can also be metrics that show where improvement is needed.
Many people rightly focus on metrics related to winning and focus on improving those in order to increase sales, conversions, and other metrics of winning. It’s a good approach.
But there are also KPIs related to failure, and those can be useful for identifying new areas to find success.
So, this survey reviews KPIs related to success and failure, investigates shortcomings in popular KPIs, and introduces additional KPIs that may not be widely known.
1. Customer Lifetime Value (CLV)
Customer Lifetime Value (CLV) is a metric that measures the earnings each customer brings.
In the context of SEO, CLV helps a business identify which SEO activities result in the greatest positive financial impact.
Jeff Coyle, co-founder of AI-based content strategy SaaS company MarketMuse, is passionate about CLV and feels it is an important KPI for many businesses to be aware of.
Jeff Coyle said this about the CLV KPI:
“My perspective on using CLV and why it connects to core KPI is because it’s a Unifying metric.
I love unifying metrics because all teams, all silos, have to support it.
It forces people who typically focus only on one stage of the funnel to think bigger, to think customer-centric.
So in terms of content, it typically means all teams have to think about the entire funnel, all personas, all levels of expertise of the future and present customers.
An SEO focused on a myopic one keyword to one webpage SEO hack or publishing low-quality content may be able to get lucky with a ranking every once in a while.
But that type of strategy isn’t going perform well with CLV growth.
Similarly, a PPC person or a demand generation marketer who isn’t willing to support full funnel content at awareness stage and all the way down but they should, especially for support and customer content.
They get paid on leads and conversions.
Customer Lifetime Value makes them have to care about all the content. It makes them care about customer success, renewals, support and exponential viral growth.”
According to Jeff, focusing on CLV forces all parts of the company to hone what they do toward keeping the company growing year over year.
2. Content Efficiency
Jeff had one more KPI he wanted to share, and this one is Content Efficiency.
Content Efficiency is a fascinating metric because it’s about optimizing content not just for search engines but for achieving company goals for that content.
Jeff explains it like this:
“My other favorite KPI is content efficiency. It’s about how many content items you publish, how many content items you update and/or optimize versus how often those pages meet their goals and predicted ROI.
Average content teams create content that reaches 10% of their goals, 10% of their content is successful.
I get teams operating 40% or more, where 40% or more of their content achieve their intended goals. That percentage defines good content teams.
Looked at another way, the company with the team performing at 10% Content Efficiency is a company that is spending 10 times what they think they are spending on content to achieve their goals.
How much does content cost? $400 to $500 a page? They only get meaningful results from 10% of that content.
So, their effective cost per successful content motion (publication and updating the content) is like $5,000 for the average team.
For a team operating at peak Content Efficiency, the cost is around $2,500 to $3,000 to achieve their goals.
Using Content Efficiency as a KPI, that’s when people really start wanting to improve their content strategy and transition to data-driven decision making for what to create and what to update.
Content Efficiency is one of the core MarketMuse value propositions. Personalized Difficulty metrics. You know what to build and how much you need to invest to make an impact.”
3. Average Engagement Time
I next asked someone who specializes in analytics, Kayle Larkin, about KPIs.
Kayle is an Analytics and SEM consultant for B2B and ecommerce sites in the U.S., Canada, Europe, and Asia, as well as a Content Writer here at Search Engine Journal.
She shared about a KPI available in Google Analytics 4 that tracks user engagement with a website, something that can be difficult to accurately measure.
Kayle shared:
“GA4 (Google Analytics 4) improved our ability to measure whether or not a user engaged with the website.
Average engagement time tells us the average length of time that the site had focus in the user’s browser. That means the user was most likely looking at it.”
4. Conversion Goals By Percent-Based Metrics
Kayle next advised reviewing KPIs as percent-based metrics:
“The most important KPI is conversions/goals. Which should only be that which makes your company money.
However… Don’t forget to look at goals by percent-based metrics, not solely raw event values.
Because if your traffic is increasing, the number of goals will naturally increase too.
But, if the goal conversion rate (expressed as a percentage) is dropping then maybe the organic campaign is not as efficient as it could be.
Or, on the flip side maybe traffic is decreasing but goal conversion rate is increasing because you’re better focused/speaking to your target audience.”
Those two are the main KPIs from an “Is this organic strategy performing well over time?” viewpoint.
5. Accurate Search Visibility KPIs
Next, I asked Cindy Krum, and she shared two KPIs that are proprietary to her company, MobileMoxie.
The KPIs she shared are improvements to accurately assessing search visibility.
Most search ranking reports operate on the old model of 10 blue links. But, the search results are not 10 blue links anymore, they’ve evolved.
Cindy shows how there are more accurate KPIs to track that will give a better idea of search visibility.
Cindy shared metrics that provide a more accurate view of the search engine results pages (SERPs):
“At MobileMoxie, we are looking more and more at metrics that tell the story of the SERP – especially on important head terms.
We know that ranking in ‘Position 1′ isn’t what it used to be, so in our toolset we also look at things that give us more information about the ranking, such as ‘Pixels from the Top.’
We also compare the ‘Traditional Rank’ with ‘Actual Rank’.
Traditional Rank is what SEO’s are used to using, which excludes things like PPC, Knowledge Graph, and other Google assets in the SERPs.
So, what we do is compare Traditional Rank with Actual Rank, which counts everything in the SERPs that can push an organic ranking down, including PPC, Knowledge Graph, Answers, and other Google elements in the search.
This comparison tells us more about the value of each ranking and how visible a search position really is to a searcher.”
6. Brand Visibility In Search KPIs
Cindy next shared another metric that tracks brand visibility in a way that includes all of a brand’s assets, particularly off-site brand assets.
“We have also started caring much more about a brand’s over-all representation in a search result.
That includes how much of the SERP is dominated by brand assets, including content on the main site, and also other content, such as social media profiles and posts, YouTube videos, images, Knowledge Graph results, and everything else that could be a good representation of the brand, and help drive sales and awareness.
For years, SEOs have been optimizing off-site content, and we want them to start getting credit for that work too.
Off-site optimized assets are useful because they crowd competitors out of the SERPs.
So, we developed a score that we call the MoxieScore, that represents how much of a SERP a brand owns.
These are all important KPIs that we care about more now than ever before.”
7. New And Returning Users As KPIs
Jim Hedger, one of the hosts of the popular Webcology podcast, had an interesting take on using new and returning users as a KPI for optimizing web pages for more conversions, particularly for B2B websites.
Many KPIs are situational and depend on the type of site and who the visitors are. This idea about new and returning users as a KPI is no different in that regard.
Jim explains it like this:
“Most of us have clients with varying success metrics but each of those metrics have one thing in common, the site visitor must take a specific action, a conversion event, generally via a click.
Understanding how users get to the conversion event is critical to moving more users towards conversions.
Google Analytics, Google Search Console, and Bing Webmaster Tools can give us relatively good event metrics representing page value in relation to those conversion points.
In Google Analytics, it’s easy to separate site users into new and returning segments.
This gives a wildly different view of which pages in a site are most valuable to which segment of visitors.
Returning users tend to convert at a far higher rate than new users, even though new users tend to heavily outweigh returning users.
New users and returning users tend to enter the website on different landing pages.
Knowing new users are more likely visiting the site for discovery and returning users are frequently visiting to convert, and learning which pages each segment tends to move through on their conversion journey helps SEOs craft content that better suits the site visitor’s intent.
You may be surprised by looking at any KPI while segmenting between new and returning visitors. Since I’ve been doing that, I’ve noticed how very different the actions of each segment are.”
According to Jim, looking at site visitors as a KPI and segmenting the traffic into New and Returning visitors, one will attain a better view of which users are most valuable, and why.
8. Average Time On Site – A Caveat
Average time on site seems like a no-brainer KPI to use for trying to measure the effectiveness of the content on different webpages.
But there are actually some limits to be aware of regarding this KPI that need to be considered before using this as a way to measure the engagement success or lack of success of website content.
Jeff Coyle shared this:
“The average time on site can be a little misleading because if they don’t exclude bounces the data is terrible.”
I asked analytics expert Kayle Larkin about it, and she cautioned that Average Time on Site needs to be justified with data before using it as a KPI.
Kayle said:
“I don’t use Average Time on Site as a KPI so I’d have to see how they’re excluding bounces.
I guess this is one of those where and why things because it’s so situational.
Maybe if it was an affiliate site? Where you want people spending time on your page.
Maybe if they’ve found that people who spend between X and Z time have an increased conversion rate?
Otherwise, I’d ask why is this a KPI? How does this achieve business objectives?”
9. Revenue Per Thousand (RPM) And Average Position
Revenue Per Thousand (RPM) is a way to calculate how valuable your traffic is, particularly for ad-supported websites.
And, Average Position is a keyword ranking metric provided by Google Search Console.
Both of these KPIs can work together for identifying keywords and webpages that need improvement. This is one of those cases where two metrics working together can yield better insights.
RPM KPI
I wouldn’t use this KPI in isolation to determine the effectiveness of a webpage. But, it’s a good way to measure changes over the course of time to evaluate how a change to a webpage affects earnings.
You can do things like make a webpage faster or swap in a different kind of ad unit and through the RPM KPI get an idea of how well or poorly the change affects earnings.
A Google AdSense help page describes it like this:
“Revenue per 1,000 impressions (RPM) represents the estimated earnings you’d accrue for every 1,000 impressions you receive.
RPM doesn’t represent how much you have actually earned; rather, it’s calculated by dividing your estimated earnings by the number of page views, impressions, or queries you received, then multiplying by 1,000.”
Revenue Per Thousand may not seem like an SEO KPI but ad-derived earnings can be tracked to SEO via the RPM metric.
The keyword and traffic choices made on the SEO side will determine the performance on the revenue side.
For example, a common SEO approach is to focus on high-traffic keywords.
But some high traffic keywords don’t have a sales-related intent and this can be reflected in a lower RPM metric.
The most valuable keywords to bid on, for advertising purposes, are the ones with a strong sales intent.
The RPM metric is a good starting point for evaluating which kinds of topics have a good blend of traffic and high earnings.
Average Position KPI
This is a Google Search Console metric that shows the average position of a keyword phrase in the search results.
Google defines this metric like this:
“Average position [Chart only]-
The average position of the topmost result from your site.
So, for example, if your site has three results at positions 2, 4, and 6, the position is reported as 2.
If a second query returned results at positions 3, 5, and 9, your average position would be (2 + 3)/2 = 2.5. If a row of data has no impressions, the position will be shown as a dash (-), because the position doesn’t exist.”
KPIs tend to focus on where a website is winning. And, if the KPI isn’t “winning enough” then the effort is made to improve the KPI scores.
But KPIs that show low performance can be helpful, too.
For the Google Search Console average position report, the keywords at the bottom provide goals for increasing traffic and expanding search visibility.
The first step is to match the low-performing keywords to webpages to see if maybe the page needs an additional paragraph to expand on a topic or maybe a new webpage is necessary.
If Google thinks your website is relevant for a certain keyword but not relevant enough to show it on page one of the search results, then that may be a sign that your website already has one toe on page one of the SERPs for that keyword.
Keywords listed at the bottom of the average position report can be an inspiration for new ideas for growing search visibility.
Top SEO KPIs
The concept of top SEO KPIs seems to me almost not possible to iterate because every business model has different goals. This is why I (and others) say that KPIs are situational.
Marketing Analytics Expert and Canadian Search Awards Judge Alan K’necht makes the observation that because every business is different, each business must begin formulating their KPIs based on their specific goals.
Alan shared:
“Know what you want from your site, then measure that success. See if these successes improve at the same rate or faster than your SEO success.”
These top nine KPIs are not meant to be the absolute top KPIs. They are top because they are worthy of consideration and inspirational for developing your own KPIs that are relevant for your business.
Featured Image: Paulo Bobita/Search Engine Journal
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
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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!
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