SEO
Over $200K Spent. Here’s What I Learned

While it’s relatively easy to learn advertising on Quora, it takes a lot of trial and error to find out what works best. A few tricks can make your work more efficient and your campaigns more effective.
I’ve been using Quora Ads since it began in 2017, spent over $200K advertising for three global brands, and given lectures on how to succeed in it. I’ve managed campaigns on Facebook and Twitter too, so I have a fair comparison of what makes Quora Ads good or bad.
We’ll go through eight valuable Quora Ads takeaways that will save you tens of thousands of dollars in both ad spend and work hours.
Let’s dive in.
The days of super cheap clicks and impressions on Quora are long gone, but it can still be significantly cheaper compared to mainstream platforms like Google, Facebook, or Twitter.
I disclosed some data with the Quora team via a success story and a podcast episode based on my experience from previous employment. I was comparing this to search and display campaigns in Google Ads because the intent of Quora users isn’t far from that.
So back then on Quora Ads, we had:
- 65% lower CPC than comparable Google search campaigns.
- 46% lower CPA than comparable Google search campaigns.
As of now in Ahrefs, I can share the following numbers for comparable campaigns, which are:
- 40–50% cheaper CPC than Facebook.
- 60–95% cheaper CPC than Google’s search campaigns (yes, the difference can be that huge).
These are the cases where Quora is significantly cheaper than other main advertising platforms.
Quora has more expensive CPCs and CPMs (2–6 times) than Google Display Network campaigns, but it still seems like a great deal considering the intent and engagement of Quora visitors. More on this later.
Two main factors that determine how to best structure campaigns on Quora are budget and bid settings. The unfortunate thing is that the budget is set at campaign level, while bidding comes at the ad set level.
Here’s a problem that you can easily run into because of this:

All ad sets were running side by side, with each having an estimated potential reach in the lower millions weekly. As you can see, the CTR of the most pushed ad set isn’t the highest, so engagement signals don’t play a huge role in Quora’s delivery algorithm.
It’s the bid size that makes the biggest difference.
Based on my experience, Quora’s delivery algorithms heavily favor ad sets with higher bids. Running multiple ad sets within one campaign becomes a challenge to optimize the ad delivery.
One solution is to bid the same across all running ad sets within one campaign. But that could create more problems if the targeting differs. It also doesn’t ensure balanced delivery.
I’ve always leaned toward the second solution: run just one ad set per campaign at a given time. It also has its downs, as you have to create and manage many campaigns at once. But it’s the best I could do. Here’s a sneak peek at Ahrefs’ blog promotion campaigns structure:

As you can see, I grouped campaigns by their geo-targeting and device type. This is the only structure that allowed me to properly manage the campaign budget allocation and ad distribution.
I generally recommend creating a separate campaign for each country and device. But I bundled together four countries to make the account easier to manage. The reasons for this were similar CPCs across all those grouped countries, confirming that impressions were being distributed proportionally to each country’s population.
PRO TIP
Fortunately, my Quora account managers were always helpful and dug into such data for me. It’s worth trying to get in touch with them should you ever need data you can’t get yourself.
Quora Ads offers four different types of primary targeting:

Audience targeting and broad targeting are things we can encounter on other platforms too. Nothing too groundbreaking there, so let’s focus on the other two primary targeting types: contextual and behavioral targeting.
You can read what it’s about in the screenshots, so let me jump straight to the best use cases.
In Ahrefs, I most often went for the Contextual -> Topics targeting shown above. It gives us solid control over where the ads are shown. But it pays off to learn how Quora assigns topics to its questions, as that’s far from perfect.
To do this, look up the topic in the search bar and go through the results:

Switch to the “Answer” tab to only see questions, then check the list and inspect all the labels under a few questions after clicking “View question log” to better understand how good or bad of a job Quora does in your niche:

Here’s an example of how broad or irrelevant Quora can go sometimes:

However, in my experience, going a bit more broad with the choice of topics usually performed better than trying to be very specific.
Then we have Behavioral -> Interests targeting:

This type of targeting resembles what we’re used to from Facebook or Google. Quora models the interests of each user and then tries to show them relevant ads.
You get a higher potential reach at the cost of relying on a black box. That generally results in lower engagement but also in lower CPCs since the much more relevant contextual targeting comes with a slightly higher price.
Now that you’re more familiar with the primary targeting types, we can visualize the competitive advantage of Quora Ads:

Both Topics and Interests sub-targeting types are the broadest ones in each category. This is desirable for the purpose of most Ahrefs campaigns.
But my previous company needed much more granular targeting.
The possibility to target each Question (technically individual Quora URLs) was at the top of our targeting arsenal.
Choosing specific questions to bid on with your ads may be the biggest advantage of Quora Ads. You can show your ads to Quora visitors who are thinking about problems your product can solve at that exact moment as they read answers to that question.

You also have complete control over the ad placement, which comes in handy when all the topic labels are too broad for your needs.
But how do we find the right questions to target?
Given that Quora drives an estimated ~114M non-branded clicks from organic search a month, it only makes sense to incorporate some SEO processes into this questions mining task.

There are multiple paths to getting an exhaustive list of Quora question URLs. I’d recommend starting with the most efficient one: using Quora’s own questions suggestion feature after you click on “Bulk add” here:

Then write down at least 10 keywords that best describe your business, products, or problems your audience is trying to solve. The more, the better. Add your competitor brands and products too. If you’ve already done some keyword research for SEO in the past, then this is a piece of cake.

You’ll get a list of questions sorted by weekly views. As you can see in the list below, the matching isn’t perfect, as it shows “stock market” questions based on my “marketing” keyword input. On the other hand, you don’t need to worry about including exact match keywords.

You can select the most relevant questions to target and end the questions research here. But I like to take this one step further and gather organic traffic data for each question. It helps with question prioritization that we’ll discuss in the next point.
So while you’re in the “Questions to target” window, open up Ahrefs’ SEO Toolbar and head over to “Outgoing links” since all the questions in the list are linked through.

Click on the export button, and you’ll get a list of all the URLs there. All that’s left is to filter the list for relevant questions, copy-paste it into Ahrefs’ Batch Analysis tool, and sort the table by organic traffic:

There you have it—organic traffic estimations on top of Quora’s traffic data. I’ll always prioritize questions that get solid organic traffic over what’s currently trending on Quora, as Google tends to be a more sustainable traffic source.
You can now run highly relevant and engaging campaigns, including those that retarget Quora users based on questions they visited in the past. Just copy-paste the input window between Contextual – Questions and Behavioral – Question history.

Organic growth on Quora isn’t easy. But still without putting in too much effort, some of my answers got tens, even hundreds of thousands of views and rank among the top answers:

OK, I cheated a bit. The easiest way to get such numbers is to simply boost your answers with Quora Ads. It provides a unique ad format called Promoted Answers:

Just feed the system with any answer URL, and it will show the answer as an ad throughout the platform based on your targeting:

The best thing about this is the ability to promote any answer. And since we just went through sourcing a list of the most relevant Quora questions, we can leverage it here too. Just go through the answers in the most promising questions and note all answer URLs that positively mention your brand or product.
If you decide to skip the Questions targeting, you can also do a simple search in Google using search operators to filter Quora URLs that mention your brand or product:

I haven’t run these Promoted Answers in a while. But back then, I was getting a cheap CPM at around $1. It seemed to work well for brand awareness campaigns. I’m also convinced that it has an influence on how Quora ranks the answers for a certain question, as you get much more views and upvotes compared to the rest.
To sum it up: Quora is no different than other platforms, and you get the best results if you properly combine both organic and paid marketing. Promoted Answers are an interesting ad format worth experimenting with for increasing brand awareness.
You can learn more about succeeding with your organic efforts in a guide by my colleague, SQ, who took over marketing topics on Quora by storm a few years ago.
One of the earlier points is about Quora Ads being cheaper than other platforms. This, of course, depends on how well managed and optimized your campaigns are because, sometimes, the suggested CPCs are anything but cheap:

First of all, besides brand awareness campaigns, I always go for bidding on the CPC basis. I found it cheaper than bidding on CPM. Also, I have no data about CPA bids, as we don’t use tracking pixels in Ahrefs.
In terms of CPCs, I usually stick to the lower range of the suggested bid. I then readjust the bids based on the impression share it gets. My rule of thumb is keeping the impression share between 10% and 30%, which I found to be the best balance between solid ad delivery and reasonable prices.

I still kept some of my more expensive ad sets below 10% impression share if they easily managed to spend the daily budget, thanks to broader targeting and reach.
Speaking of reach, I found Quora to sometimes report weirdly overestimated potential weekly impressions:

I wrote down a specific case where it kept showing 3,500–15,000 potential weekly impressions in an ad set that only received 400 impressions with 12.5% impression share over six months. It fixed the reach estimation in this case already, so I’m only left with a written note and no screenshot.
But considering we can trust the numbers in most cases, let’s do some quick math with relevant numbers based on Ahrefs’ advertising on Quora.
A campaign with a $50 daily budget and an average CPM of $2.5 will spend the budget after 20,000 daily impressions. That equals 140,000 impressions weekly. A 15% impression share means that our running ad set(s) will need to have potential weekly impressions of at least ~930K, let’s say a million.
That said, Quora claims 300 million+ monthly visitors, but it’s sometimes rather difficult to put together targeting that results in a big enough estimated potential reach. At least in our SEO and marketing niche.
All in all, the vast majority of ad sets I ran recently had a weekly potential reach between 500K and 10M. Otherwise, I wouldn’t be able to achieve the desired performance. You can easily run into a situation where you need to decide what makes the most sense for you:
- Increase bids for higher impression shares
- Broaden targeting for higher reach at the cost of a potentially lower ad relevance
- Keep your campaigns hitting the ceiling and allocate the rest of the budget elsewhere
And this is just the beginning when it comes to scaling up your campaigns.
As explained earlier, the best structured account for optimal ad delivery and effectiveness comes at the cost of being more difficult to manage. Creating new ad sets and running new ads involve a lot of clicking around. There’s no duplicating and controlling ad sets at scale. You have to do them one by one.

Once you get the hang of it, it takes a matter of a few minutes. But it’s still annoying.
Should you only require duplicating, uploading, or editing ads in multiple ad sets at once, then Quora’s ad editor comes in handy.
When I brought this inconvenience up with my account managers, they told me that my approach seemed to be the most efficient indeed. A good thing is that they offered help managing the campaigns if the clicking around ever became too bothersome.
So while account management and scalability in Quora Ads are far from perfect, it at least partially compensates for that with the best customer service I’ve encountered with any advertising platform.
Final thoughts
I’m not a PPC specialist, just a marketer that took the opportunity to learn to run Quora Ads and a few other advertising platforms on the go. I strived to describe only the most important and interesting takeaways that could take a while for even experienced PPC specialists to figure out.
Other than this, there are more similarities to other PPC platforms than differences. That’s why I didn’t even bring up creating ads, for example—there’s nothing special about this on Quora.
So are you going to give it a shot? Do you have any questions? Ping me on Twitter.
SEO
How To Become an SEO Expert in 4 Steps

With 74.1% of SEOs charging clients upwards of $500 per month for their services, there’s a clear financial incentive to get good at SEO. But with no colleges offering degrees in the topic, it’s down to you to carve your own path in the industry.
There are many ways to do this; some take longer than others.
In this post, I’ll share how I’d go from zero to SEO pro if I had to do it all over again.
Understanding what search engine optimization really is and how it works is the first state of affairs. While you can do this by reading endless blog posts or watching YouTube videos, I wouldn’t recommend that approach for a few reasons:
- It’s hard to know where to start
- It’s hard to join the dots
- It’s hard to know who to trust
You can solve all of these problems by taking a structured course like our SEO course for beginners. It’s completely free (no signup required), consists of 14 short video lessons (2 hours total length), and covers:
- What SEO is and why it’s important
- How to do keyword research
- How to optimize pages for keywords
- How to build links (and why you need them)
- Technical SEO best practices
Here’s the first lesson to get you started:
It doesn’t matter how many books you read about golf, you’re never going to win a tournament without picking up a set of clubs and practicing. It’s the same with SEO. The theory is important, but there’s no substitute for getting your hands dirty and trying to rank a site.
If you don’t have a site already, you can get up and running fairly quickly with any major website platform. Some will set you back a few bucks, but they handle SEO basics out of the box. This saves you time sweating the small stuff.
As for what kind of site you should create, I recommend a simple hobby blog.
Here’s a simple food blog I set up in <10 minutes:


Once you’re set-up, you’re ready to start practicing and honing your SEO skills. Specifically, doing keyword research to find topics, writing and optimizing content about them, and (possibly) building a few backlinks.
For example, according to Ahrefs’ Keywords Explorer, the keyword “neopolitan pizza dough recipe” has a monthly traffic potential of 4.4K as well as a relatively low Keyword Difficulty (KD) score:


Even better, there’s a weak website (DR 16) in the top three positions—so this should definitely be quite an easy topic to rank for.


Given that most of the top-ranking posts have at least a few backlinks, a page about this topic would also likely need at least a few backlinks to compete. Check out the resources below to learn how to build these.
It’s unlikely that your hobby blog is going to pay the bills, so it’s time to use the work you’ve done so far to get a job in SEO. Here are a few benefits of doing this:
- Get paid to learn. This isn’t the case when you’re home alone reading blog posts and watching videos or working on your own site.
- Get deeper hands-on experience. Agencies work with all kinds of businesses, which means you’ll get to build experience with all kinds of sites, from blogs to ecommerce.
- Build your reputation. Future clients or employers are more likely to take you seriously if you’ve worked for a reputable SEO agency.
To find job opportunities, start by signing up for SEO newsletters like SEO Jobs and SEOFOMO. Both of these send weekly emails and feature remote job opportunities:


You can also go the traditional route and search job sites for entry-level positions. The kinds of jobs you’re looking for will usually have “Junior” in their titles or at least mention that it’s a junior position in their description.


Beyond that, you can search for SEO agencies in your local area and check their careers pages.
Even if there are no entry-level positions listed here, it’s still worth emailing and asking if there are any upcoming openings. Make sure to mention any SEO success you’ve had with your website and where you’re at in your journey so far.
This might seem pushy, but many agencies actually encourage this—such as Rise at Seven:


Here’s a quick email template to get you started:
Subject: Junior SEO position?
Hey folks,
Do you have any upcoming openings for junior SEOs?
I’ve been learning SEO for [number] months, but I’m looking to take my knowledge to the next level. So far, I’ve taken Ahrefs’ Beginner SEO course and started my own blog about [topic]—which I’ve had some success with. It’s only [number] months old but already ranks for [number] keywords and gets an estimated [number] monthly search visits according to Ahrefs.
[Ahrefs screenshot]
I checked your careers page and didn’t see any junior positions there, but I was hoping you might consider me for any upcoming positions? I’m super enthusiastic, hard-working, and eager to learn.
Let me know.
[Name]
You can pull all the numbers and screenshots you need by creating a free Ahrefs Webmaster Tools account and verifying your website.
SEO is a broad industry. It’s impossible to be an expert at every aspect of it, so you should niche down and hone your skills in the area that interests you the most. You should have a reasonable idea of what this is from working on your own site and in an agency.
For example, link building was the area that interested me the most, so that’s where I focused on deepening my knowledge. As a result, I became what’s known as a “t-shaped SEO”—someone with broad skills across all things SEO but deep knowledge in one area.


Marie Haynes is another great example of a t-shaped SEO. She specializes in Google penalty recovery. She doesn’t build links or do on-page SEO. She audits websites with traffic drops and helps their owners recover.
In terms of how to build your knowledge in your chosen area, here are a few ideas:
Here are a few SEOs I’d recommend following and their (rough) specialties:
Final thoughts
K Anders Ericsson famously theorized that it takes 10,000 hours of practice to master a new skill. Can it take less? Possibly. But the point is this: becoming an SEO expert is not an overnight process.
I’d even argue that it’s a somewhat unattainable goal because no matter how much you know, there’s always more to learn. That’s part of the fun, though. SEO is a fast-moving industry that keeps you on your toes, but it’s a very rewarding one, too.
Here are a few stats to prove it:
- 74.1% of SEOs charge clients upwards of $500 per month for their services (source)
- $49,211 median annual salary (source)
- ~$74k average salary for self-employed SEOs (source)
Got questions? Ping me on Twitter X.
SEO
A Year Of AI Developments From OpenAI

Today, ChatGPT celebrates one year since its launch in research preview.
Try talking with ChatGPT, our new AI system which is optimized for dialogue. Your feedback will help us improve it. https://t.co/sHDm57g3Kr
— OpenAI (@OpenAI) November 30, 2022
From its humble beginnings, ChatGPT has continually pushed the boundaries of what we perceive as possible with generative AI for almost any task.
a year ago tonight we were probably just sitting around the office putting the finishing touches on chatgpt before the next morning’s launch.
what a year it’s been…
— Sam Altman (@sama) November 30, 2023
In this article, we take a journey through the past year, highlighting the significant milestones and updates that have shaped ChatGPT into the versatile and powerful tool it is today.
a year ago tonight we were placing bets on how many total users we’d get by sunday
20k, 80k, 250k… i jokingly said “8B”.
little did we know… https://t.co/8YtO8GbLPy— rapha gontijo lopes (@rapha_gl) November 30, 2023
ChatGPT: From Research Preview To Customizable GPTs
This story unfolds over the course of nearly a year, beginning on November 30, when OpenAI announced the launch of its research preview of ChatGPT.
As users began to offer feedback, improvements began to arrive.
Before the holiday, on December 15, 2022, ChatGPT received general performance enhancements and new features for managing conversation history.

As the calendar turned to January 9, 2023, ChatGPT saw improvements in factuality, and a notable feature was added to halt response generation mid-conversation, addressing user feedback and enhancing control.
Just a few weeks later, on January 30, the model was further upgraded for enhanced factuality and mathematical capabilities, broadening its scope of expertise.
February 2023 was a landmark month. On February 9, ChatGPT Plus was introduced, bringing new features and a faster ‘Turbo’ version to Plus users.
This was followed closely on February 13 with updates to the free plan’s performance and the international availability of ChatGPT Plus, featuring a faster version for Plus users.
March 14, 2023, marked a pivotal moment with the introduction of GPT-4 to ChatGPT Plus subscribers.


This new model featured advanced reasoning, complex instruction handling, and increased creativity.
Less than ten days later, on March 23, experimental AI plugins, including browsing and Code Interpreter capabilities, were made available to selected users.
On May 3, users gained the ability to turn off chat history and export data.
Plus users received early access to experimental web browsing and third-party plugins on May 12.
On May 24, the iOS app expanded to more countries with new features like shared links, Bing web browsing, and the option to turn off chat history on iOS.
June and July 2023 were filled with updates enhancing mobile app experiences and introducing new features.
The mobile app was updated with browsing features on June 22, and the browsing feature itself underwent temporary removal for improvements on July 3.
The Code Interpreter feature rolled out in beta to Plus users on July 6.
Plus customers enjoyed increased message limits for GPT-4 from July 19, and custom instructions became available in beta to Plus users the next day.
July 25 saw the Android version of the ChatGPT app launch in selected countries.
As summer progressed, August 3 brought several small updates enhancing the user experience.
Custom instructions were extended to free users in most regions by August 21.
The month concluded with the launch of ChatGPT Enterprise on August 28, offering advanced features and security for enterprise users.
Entering autumn, September 11 witnessed limited language support in the web interface.
Voice and image input capabilities in beta were introduced on September 25, further expanding ChatGPT’s interactive abilities.
An updated version of web browsing rolled out to Plus users on September 27.
The fourth quarter of 2023 began with integrating DALL·E 3 in beta on October 16, allowing for image generation from text prompts.
The browsing feature moved out of beta for Plus and Enterprise users on October 17.
Customizable versions of ChatGPT, called GPTs, were introduced for specific tasks on November 6 at OpenAI’s DevDay.


On November 21, the voice feature in ChatGPT was made available to all users, rounding off a year of significant advancements and broadening the horizons of AI interaction.
And here, we have ChatGPT today, with a sidebar full of GPTs.


Looking Ahead: What’s Next For ChatGPT
The past year has been a testament to continuous innovation, but it is merely the prologue to a future rich with potential.
The upcoming year promises incremental improvements and leaps in AI capabilities, user experience, and integrative technologies that could redefine our interaction with digital assistants.
With a community of users and developers growing stronger and more diverse, the evolution of ChatGPT is poised to surpass expectations and challenge the boundaries of today’s AI landscape.
As we step into this next chapter, the possibilities are as limitless as generative AI continues to advance.
Featured image: photosince/Shutterstock
SEO
Is AI Going To E-E-A-T Your Experience For Breakfast? The LinkedIn Example

Are LinkedIn’s collaborative articles part of SEO strategies nowadays?
More to the point, should they be?
The search landscape has changed dramatically in recent years, blurring the lines between search engines and where searches occur.
Following the explosive adoption of AI in content marketing and the most recent Google HCU, core, and spam updates, we’re looking at a very different picture now in search versus 12 months ago.
User-generated and community-led content seems to be met with renewed favourability by the algorithm (theoretically, mirroring what people reward, too).
LinkedIn’s freshly launched “collaborative articles” seem to be a perfect sign of our times: content that combines authority (thanks to LinkedIn’s authority), AI-generated content, and user-generated content.
What could go wrong?
In this article, we’ll cover:
- What are “collaborative articles” on LinkedIn?
- Why am I discussing them in the context of SEO?
- The main issues with collaborative articles.
- How is Google treating them?
- How they can impact your organic performance.
What Are LinkedIn Collaborative Articles?
First launched in March 2023, LinkedIn says about collaborative articles:
“These articles begin as AI-powered conversation starters, developed with our editorial team, but they aren’t complete without insights from our members. A select group of experts have been invited to contribute their own ideas, examples and experiences within the articles.“
Essentially, each of these articles starts as a collection of AI-generated answers to FAQs/prompts around any given topic. Under each of these sections, community members can add their own perspectives, insights, and advice.
What’s in it for contributors? To earn, ultimately, a “Top Voice” badge on their profile.
The articles are indexable and are all placed under the same folder (https://www.linkedin.com/advice/).
They look like this:

On the left-hand side, there are always FAQs relevant to the topic answered by AI.
On the right-hand side is where the contributions by community members get posted. Users can react to each contribution in the same way as to any LinkedIn post on their feed.
How Easy Is It To Contribute And Earn A Badge For Your Insights?
Pretty easy.
I first got invited to contribute on September 19, 2023 – though I had already found a way to contribute a few weeks before this.


My notifications included updates from connections who had contributed to an article.
By clicking on these, I was transferred to the article and was able to contribute to it, too (as well as additional articles, linked at the bottom).
I wanted to test how hard it was to earn a Top SEO Voice badge. Eight article contributions later (around three to four hours of my time), I had earned three.


How? Apparently, simply by earning likes for my contributions.
A Mix Of Brilliance, Fuzzy Editorial Rules, And Weird Uncle Bob
Collaborative articles sound great in principle – a win-win for both sides.
- LinkedIn struck a bullseye: creating and scaling content (theoretically) oozing with E-E-A-T, with minimal investment.
- Users benefit from building their personal brand (and their company’s) for a fragment of the effort and cost this usually takes. The smartest ones complement their on-site content strategy with this off-site golden ticket.
What isn’t clear from LinkedIn’s Help Center is what this editorial mix of AI and human input looks like.
Things like:
- How much involvement do the editors have before the topic is put to the community?
- Are they only determining and refining the prompts?
- Are they editing the AI-generated responses?
- More importantly, what involvement (if any) do they have after they unleash the original AI-generated piece into the world?
- And more.
I think of this content like weird Uncle Bob, always joining the family gatherings with his usual, unoriginal conversation starters. Only, this time, he’s come bearing gifts.
Do you engage? Or do you proceed to consume as many canapés as possible, pretending you haven’t seen him yet?
Why Am I Talking About LinkedIn Articles And SEO?
When I first posted about LinkedIn’s articles, it was the end of September. Semrush showed clear evidence of their impact and potential in Search. (Disclosure: I work for Semrush.)
Only six months after their launch, LinkedIn articles were on a visible, consistent upward trend.
- They were already driving 792.5K organic visits a month. (This was a 75% jump in August.)
- They ranked for 811,700 keywords.
- Their pages were ranking in the top 10 for 78,000 of them.
- For 123,700 of them, they appeared in a SERP feature, such as People Also Ask and Featured Snippets.
- Almost 72% of the keywords had informational intent, followed by commercial keywords (22%).
Here’s a screenshot with some of the top keywords for which these pages ranked at the top:


Now, take the page that held the Featured Snippet for competitive queries like “how to enter bios” (monthly search volume of 5,400 and keyword difficulty of 84, based on Semrush data).
It came in ahead of pages on Tom’s Hardware, Hewlett-Packard, or Reddit.


See anything weird? Even at the time of writing this post, this collaborative article had precisely zero (0) contributions.
This means a page with 100% AI-generated content (and unclear interference of human editors) was rewarded with the Featured Snippet against highly authoritative and relevant domains and pages.
A Sea Of Opportunity Or A Storm Ready To Break Out?
Let’s consider these articles in the context of Google’s guidelines for creating helpful, reliable, people-first content and its Search Quality Rater Guidelines.
Of particular importance here, I believe, is the most recently added “E” in “E-E-A-T,” which takes experience into account, alongside expertise, authoritativeness, and trustworthiness.
For so many of these articles to have been ranking so well must mean that they were meeting the guidelines and proving helpful and reliable for content consumers.
After all, they rely on “a select group of experts to contribute their own ideas, examples and experiences within the articles,” so they must be worthy of strong organic performances, right?
Possibly. (I’ve yet to see such an example, but I want to believe somewhere in the thousands of pages these do exist).
But, based on what I’ve seen, there are too many examples of poor-quality content to justify such big rewards in the search engine results pages (SERPs).
The common issues I’ve spotted:
1. Misinformation
I can’t tell how much vetting or editing there is going on behind the scenes, but the amount of misinformation in some collaborative articles is alarming. This goes for AI-generated content and community contributions alike.
I don’t really envy the task of fact-checking what LinkedIn describes as “thousands of collaborative articles on 2,500+ skills.” Still, if it’s quality and helpfulness we’re concerned with here, I’d start brewing my coffee a little stronger if I were LinkedIn.
At the moment, it feels a little too much like a free-for-all.
Here are some examples of topics like SEO or content marketing.


2. Thin Content
To a degree, some contributions seem to do nothing more than mirror the points made in the original AI-generated piece.
For example, are these contributions enough to warrant a high level of “experience” in these articles?


The irony to think that some of these contributions may have also been generated by AI…
3. Missing Information
While many examples don’t provide new or unique perspectives, some articles simply don’t provide…any perspectives at all.
This piece about analytical reasoning ranked in the top 10 for 128 keywords when I first looked into it last September (down to 80 in October).


It even held the Featured Snippet for competitive keywords like “inductive reasoning examples” for a while (5.4K monthly searches in the US), although it had no contributions on this subsection.
Most of its sections remain empty, so we’re talking about mainly AI-generated content.
Does this mean that Google really doesn’t care whether your content comes from humans or AI?
I’m not convinced.
How Have The Recent Google Updates Impacted This Content?
After August and October 2023 Google core updates (at the time of writing, the November 2023 Google core update is rolling out), the September 2023 helpful content update, and the October 2023 spam update, the performance of this section seems to be declining.
According to Semrush data:


- Organic traffic to these pages was down to 453,000 (a 43% drop from September, bringing their performance close to August levels).
- They ranked for 465,100 keywords (down by 43% MoM).
- Keywords in the Top 10 dropped by 33% (51,900 vs 78,000 in September).
- Keywords in the top 10 accounted for 161,800 visits (vs 287,200 in September, down by 44% MoM).
The LinkedIn domain doesn’t seem to have been impacted negatively overall.


Is this a sign that Google has already picked up the weaknesses in this content and has started balancing actual usefulness versus the overall domain authority that might have propelled it originally?
Will we see it declining further in the coming months? Or are there better things to come for this feature?
Should You Already Be On The Bandwagon If You’re In SEO?
I was on the side of caution before the Google algorithm updates of the past couple of months.
Now, I’d be even more hesitant to invest a substantial part of my resources towards baking this content into my strategy.
As with any other new, third-party feature (or platform – does anyone remember Threads?), it’s always a case of balancing being an early adopter with avoiding over-investment. At least while being unclear on the benefits.
Collaborative articles are a relatively fresh, experimental, external feature you have minimal control over as part of your SEO strategy.
Now, we also have signs from Google that this content may not be as “cool” as we initially thought.
This Is What I’d Do
That’s not to say it’s not worth trying some small-scale experiments.
Or, maybe, use it as part of promoting your own personal brand (but I’ve yet to see any data around the impact of the “Top Voice” badges on perceived value).
Treat this content as you would any other owned content.
- Follow Google’s guidelines.
- Add genuine value for your audience.
- Add your own unique perspective.
- Highlight gaps and misinformation.
Experience shows us that when tactics get abused, and the user experience suffers, Google eventually steps in (from guest blogging to parasite SEO, most recently).
It might make algorithmic tweaks when launching updates, launch a new system, or hand out manual actions – the point is that you don’t know how things will progress. Only LinkedIn and Google have control over that.
As things stand, I can easily see any of the below potential outcomes:
- This content becomes the AI equivalent of the content farms of the pre-Panda age, leading to Google clamping down on its search performance.
- LinkedIn’s editors stepping in more for quality control (provided LinkedIn deems the investment worthwhile).
- LinkedIn starts pushing its initiative much more to encourage participation and engagement. (This could be what makes the difference between a dead content farm and Reddit-like value.)
Anything could happen. I believe the next few months will give us a clearer picture.
What’s Next For AI And Its Role In SEO And Social Media?
When it comes to content creation, I think it’s safe to say that AI isn’t quite ready to E-E-A-T your experience for breakfast. Yet.
We can probably expect more of these kinds of movements from social media platforms and forums in the coming months, moving more toward mixing AI with human experience.
What do you think is next for LinkedIn’s collaborative articles? Let me know on LinkedIn!
More resources:
Featured Image: BestForBest/Shutterstock
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