I’m not obsessed with the LinkedIn algorithm, but I am 100% focused on better understanding what happens to LinkedIn content after it is published. If I chose to race my car at the weekend, I’d want to race within the track rules and win/lose fairly, based on my ability alone. Publishing on LinkedIn without adequately knowing how the algorithm works, is like sitting in a Volkswagen Beetle on a starting grid flanked by Porsches. The objective of this article is to put you in a Porsche, maybe even a Tesla. Start your engines.
My interest in the algorithm began in 2014 when I got to know a South African Data Scientist (Gericke Potgieter) who had conducted research on 561 ‘Top Posts’ featured in 48 ‘Pulse’ channels. Articles (or long form content) were all the rage back then and everyone was chasing eyeballs. Sound familiar? I’ll come back to Gericke later. I think he made some shrewd observations, particularly when it comes to posts (short form content) even though he was researching articles at the time.
LinkedIn doesn’t talk about the algorithm much, so it was notable when they announced via the traditionally boring LinkedIn Engineering Blog on Oct. 16 2018, (‘Spreading the Love in the LinkedIn Feed with Creator-Side Optimization’) that they had adjusted their algorithm in order to generate more engagement on the average user’s posts and counteracting “Irrelevant hyper-viral posts (which) were gaming the feed and crowding out posts from closer connections”. This change came after LinkedIn realized that users were not posting as many updates (posts) because the previous version of the algorithm relied mostly on content from top creators. In other words, users were writing less because they couldn’t apparently get in front of their audience and hated that the 1% were getting most of the eyeballs. A LinkedIn spokesperson said at the time “Members like seeing more content from people they know”. Me and countless other exasperated LinkedIn citizens: No shit, Sherlock.
One of the LinkedIn Data Scientists, Bonnie Barrilleaux, who co-authored that ‘Spreading the Love’ piece also shared a presentation that was embedded in the Engineering Blog article (‘Strata Data 2018: Perverse incentives in metrics’). Which was pretty interesting by itself but I thought the questions asked of Bonnie during the short Q&A after her presentation were probing and her answers revealing. At the time of writing, Bonnie’s presentation has only gotten 644 views on YouTube, I encourage you to watch it, when you find the time. Q&A starts at 29:37.
In March of this year a friend of mine, Adrian Dayton wrote a fascinating article entitled ‘Why LinkedIn Thinks Your Posts are “Low Quality”’ where he drew 5 conclusions based on the research his agency, Clearview Social had undertaken by processing over 5 million social media share links. The subheadings of his research are: 1.You overshare 2. You never add comments or insights 3. You don’t share enough 4. You don’t tag companies or people 5. You sometimes post “just for the hell of it”.
Pete Davies, Senior Director of Product Management caused ripples in June when he recommended a maximum of 3 hashtags in LinkedIn posts. He also provided basic guidance on the feed “What’s in your LinkedIn feed: People You Know, Talking About Things You Care About”, and in general terms explained how the algorithm prioritized some content over others.
Most recently, in July Richard van der Blom, a friend and fellow LinkedIn trainer in the Netherlands published the findings of his algorithm research based on analysis of more than 3,000 LinkedIn posts. His post highlighting the results of his study received over 1,500 comments and more than 185,000 views, and was so well received because it confirmed what many LinkedIn content creators/strategists had already observed/suspected. Richard’s study also provided useful data on the state of LinkedIn video and some easily overlooked potential factors (SSI & All Star) governing how LinkedIn ultimately decides what to do with content.
Almost 20% of the posts I’ve written in the last 12 months have been about the algorithm. Anything to do with the algorithm are conversation starters on LinkedIn. Without conversation, there is no engagement, no enlightenment, no questions. Because we can never fully understand the LinkedIn algorithm that decides who wins and loses the content game, there will always be questions.
It’s thanks to Gericke, Bonnie, Adrian, Pete and Richard that the following frequently asked questions about the LinkedIn algorithm can now be answered with a modicum of confidence. If you want to go fast, go alone. If you want to go further, go together (wise and old African proverb).
(1) In a nutshell, how does the algorithm work?
It assigns a ‘quality’ score to your content before anyone sees it by judging the text, anything attached to the post and tries to predict how well it will be received by your intended audience (new connections, connections, followers, mutual hashtag followers, group members). It then pushes your post to a small sample of your audience (mainly connections, followers, fellow group members) and waits to see if they engage. Depending on how that first ‘test’ goes, it’ll then decide whether to push it to more people and continue testing, or to stop showing it in the feed.
(2) Is there a diagram explaining what the algorithm does?
Yep. Here it is. Doesn’t really explain, kinda just gives an overview of the decision path content takes on LinkedIn.
(3) How do I know if my post is ‘low quality’?
You don’t. In essence, if the LinkedIn algorithm decides that your post stinks, it will not appear in the feed and hardly anyone will see it. The algorithm apparently does attempt to make a judgement call, pre-engagement signals, by looking at “attributes of the post, the member who posted it, its content, its text, any photos on it, the relationship between the poster and potential viewer. All of these to decide the expected quality of the post” (Bonnie). She also said “Historically I think the model was focusing more on the past engagement of a post as a signal of whether it’s good, rather than its inherent attributes”. So, though we don’t have a quality metric per se (what attributes?), we are informed that the algorithm takes a big picture view on author/post/audience before anyone sees it.
(4) Does the algorithm remember how your last post performed?
I wish. You will always be a one-hit wonder in the algorithm’s mind. The fact that you created a post which got over a hundred thousand views and beaucoup engagement, won’t give you an advantage when you pen your next post. Even though Bonnie says “If you regularly post thoughtful content that sparks interesting conversations, the feed will learn strong affinities between you and the people you talk to, so it’ll be even more likely to show your posts to those people in the future.” This has not been my experience. I’ve not seen an audience ramp or expansion after consistent content success. Followers aren’t followers at all, they’re people who followed you, past tense. I think that’s a shame but it is in keeping with the temporary nature of LinkedIn posts. Most of my posts seem to have a shelf life of 12-24hrs, they’re a chore to find and posts older than 6 months lose audience stats. A member of my LinkedIn Action User Group Heroes community on Facebook recently asked if anyone knew how she could find a LinkedIn post she wrote 8 years ago. Good luck with that.
(5) If my post is struggling to get engagement, will it be helped?
Perhaps. Pete Davies referred to a rather fluffy concept baked into the algorithm “We also consider who would benefit from hearing from you, and may rank a connection’s post higher if their post needs more engagement. We call this ‘creator side optimization”. In theory, the algorithm may provide a boost by putting your low engagement post in more feeds/higher up the feed, but there’s no way of knowing when/if that happens, or more importantly, why.
(6) Do I need a large network for my content to go far?
No. Though I’ve got over 16,000 followers, only a handful of people are needed to start the engagement ball rolling and to signal to the algorithm that my content may be worthy of wider distribution. Connections and followers who regularly react, comment and share your content i.e ‘fans’ are vital to content strategy success. So are the persistent engagers of your 1st, 2nd and 3rd degree connections. Your content is like a steel ball in a pinball machine, your fans operate the flippers at the start of the game and every person who subsequently engages is like a pop bumper making your post bounce again (via likes, mentions, comments re-shares) to someone else, via notifications.
(7) Are likes, re-shares and comments equal?
No. The algorithm apparently loves comments. Which makes sense, right? LinkedIn is all about the data. If you stopped giving data to LinkedIn, it would die. But LinkedIn also wants and needs users to be on the platform, to keep coming back to it and to hang around for as long as possible. Comments provide more data than likes and re-shares, they also generate engagement. This is why many successful authors end their post with a question. They understand the importance of generating a discussion. It’s crucial for reach. They also understand that it’s smart to respond or to react to every comment. Your work doesn’t end with clicking ‘publish’, it’s only just begun. Richard confirms this “Be consistent. Give a comment to each comment you receive and we noticed up to 250% increase in views and engagement from others”.
(8) Does the type of reaction matter?
I don’t think so. Whether your post receives a like, clap, heart, bulb or hmm, the algorithm only cares that someone interacted. I’d be surprised if the algorithm interpreted the 5 reactions differently, or gave different rank/weights to any of them.
(9) Will posting too many times a day/week be punished by the algorithm?
Yes. Adrian wrote “Posting more than 20 times per month isn’t going to help you, and posting way too much will hurt your distribution. Unless you are a proper celebrity or have a high-level of engagement with each and every post, don’t annoy people with too many posts”. Richard’s research backs this up “We noticed that when you share more than one post a day, this has a negative impact on the views of all the posts shared that day. Basically because the algorithm wants to show the content of more members, instead of the content from a minority of “heavy-users””. He also found that if someone shares a second post on the same day, the second post needs 3x more engagement to get the same views as the first and if you share 3 posts in one day, the third will be ignored by the algorithm. He therefore advises to wait at least 3 hours before posting twice in a day, says the algorithm will then treat both posts equally.
(10) Will adding a link in the post body affect its distribution/performance?
The word on the street is that adding an external link to the main body of your post still harms distribution. That’s certainly been my experience to date and from what I know, this fits with LinkedIn’s war on urls. Anything that takes the user away from LinkedIn is forbidden/discouraged. This is why you can’t add clickable urls to your profile page. I’ve seen/heard nothing conclusive recently to suggest that this has changed. If LinkedIn has reversed policy on this, I’d expect it to be big news and to hear from fellow authors confirming this is what is actually happening in the wild. Pete’s response to a comment on his June 25th article ‘What’s in your LinkedIn feed: People You Know, Talking About Things You Care About’ is interesting, he wrote “Assuming the links are to content that’s relevant, links in posts are great!”. Let’s parse, he says links are “great” if relevant. He doesn’t answer specifically whether the algorithm “downvotes” posts with links in them, which was the question. We also have no idea how LinkedIn decides relevancy of links. So it’s a non-answer. A popular method to prevent any penalization of links is to publish without it and to add the link post publication and/or to add the link in the first comment and let readers know in the post that’s where to find it. Kludgy but it works. Doesn’t work if that comment is buried after a ton of comments, but by then you’ve added the link back in the post and you’re off and running, right? Richard’s research also supports the perception that links can damage post distribution, he says that text+external link reduces distribution by between -25% and -50% and a post with just the external link (i.e no text) fares worse, between -50% and -80% distribution. Don’t know about you but if I see a post that is sharing a link with no intro/commentary, I usually ignore and don’t click on the post. Adrian’s research found that we won’t click on a post if it looks like a ‘lazy’ share “Posts with comments get an average 56% more clicks than those that simply share a link to an article”.
(11) Which content performs better (text, picture, document, video, live video)?
I’ve settled into a routine of mostly posting text plus a picture or text plus a document. I get decent views/engagement and was buoyed to see that LinkedIn recently added a Documents tab in the activity section. Richard’s research supports my approach, he categorizes a post consisting of text and an image as the norm, equating to “100% reach”, text plus document gets between +50% and +80% reach, native video (including Vimeo) between +20% and +70% and text-only, between +20% and +50%. The one fly in the ointment is the potential decline of native video. Not a very large sample but he partnered with 10 frequent video posters, analyzed more than 200 videos and found that average video views/engagement had steadily fallen from Q2 2018-Q2 2019. Hard to tell if this is related to the algorithm or was simply capturing audience sentiment. Time may tell if there is mounting indifference to native video but in the meantime, LinkedIn is currently experimenting with LinkedIn Live. Oh boy. Notice that there’s no ‘Video’ button currently in your Activity section…..
(12) Are LinkedIn articles dead?
For the time being, yes. Most users seem to have abandoned articles, my guess is both authors and the audience prefer posts (short, 1,300 character ‘updates’ as LinkedIn used to call them), because they’re easier to write and easier to consume, especially if you’re mobile. The one major difference between articles and posts is that articles are indexed by search engines and posts currently aren’t. So when you’re writing a post, you’re creating content that never leaves LinkedIn’s walled garden, it won’t get any distribution by google, bing etc. Some of my most successful articles only became successful (widely read) because google shared them to the world at large. Richard’s research confirms the demise of articles and squarely pins the blame on the algorithm “LinkedIn has stopped the article from being spread amongst your network in big numbers!”. He writes that “LinkedIn articles were boosted by the algorithm in 2014 and 2015. Whenever you published an article LinkedIn would send a “Notification” to your entire network” and it’s true that those audience building notifications dried up (sometime in early 2016, I think).
(13) Are re-shares worth doing?
Apparently not. My experience tells me that posts which are re-shared tend to have low views/engagement. Other people I know who spend a lot of time on the platform share this opinion. Richard mentions it in his research “(re-shares) pop up in your timeline now and then, but receive little to zero engagement”. I think one reason re-shares are less appreciated is that they’re a weird love child of the original poster and sharer, with neither side’s built-in audience engaging. I agree with Richard when he gives this advice “Want to “Share” a valuable post of one of your connections? For the algorithm it is much better to copy the entire post and then give the author credits by tagging him/her”. A friend and fellow LinkedIn observer, Mark Williams thinks that the reason re-shared content typically goes nowhere is because we, the audience decides its fate. “I think it’s a myth that LinkedIn discourage shares, the algorithm loves them, the problem is us, the viewers! We just don’t seem to want to engage with them and that is what throttles the visibility.” Whether the algorithm loves re-shares or not, it is undoubtedly looking for signals from the reader when deciding whether or not to show it to others.
(14) Should hashtags be part of my content strategy?
Absolutely. Hashtags are almost certainly one of the ‘attributes’ that Bonnie referred to when pre-judging and pre-guessing the quality (potential popularity) of posts. If you write about a robot dog and include #DARPA (126 followers) #robots (185,712) and #future (24,787,297) you’ll in theory be part of a very large crowd, or barking up the right trees, at least. Does it make sense to add hashtags that apparently have millions of followers? Sure. Will millions of those followers see and engage on your post? No. There could be a strong argument to be made for sticking with hashtags that are known to stir up a lot of engagement. But, there’s no easy way to discover which hashtags are favored by active users, or which hashtags typically drive engagement. In fact, just finding the most followed hashtags is incredibly time consuming and difficult (until I made my own list) which is probably what LinkedIn prefers. Since hashtags are all about discovery, LinkedIn may want you to discover/create your own, rather than slavishly follow a super/official list. We know that 3 hashtags per post is the max. Pete confirmed this “Use hashtags (we recommend no more than three) to help other members find the conversations that match their own interests.” I use my own for professional branding (#andydoeslinkedin) and I’ll choose two others that are 100% relevant to my content. Pay close attention to the hashtags your network is using and jump on that bandwagon. Pete says “If a connection uses a hashtag you also happen to follow, it gets an extra boost”. Using ‘network hashtags’ could potentially help your post get a higher ranking in someone’s feed depending on the hashtags they follow.
(15) I’ve heard that getting engagement early is important, why?
It’s crucial. I call it the Golden Hour. I’ve found that if no one reacts or comments to my posts within 60 minutes of posting, it will perform badly and get low engagement. If, on the other hand my post rapidly gets multiple likes and comments shortly after being published, I know that it will get good levels of engagement. Gericke identified ‘velocity’ when he studied LinkedIn articles in 2014. “A post gains velocity if there is a healthy ratio between the views, likes and shares. I haven’t been able to identify precisely what this ratio is (yet), and I know that other factors may play a role (like the bounce rate). However, I do know that the algorithm measures in terms of ratio rather than actual quantity. This means that an article with only 30 views stands as good a chance of being featured in Pulse as one with 300 views, as long as the audience interacted with it. So having an engaged audience, regardless of size, matters a great deal if you want to build that audience”. Richard confirms this “Based on the algorithm LinkedIn will always show your post to several of your connections, regardless of the time of posting. However, we noticed an important correlation between posts that do extremely well (more than 10.000 views) in the timeline: They all received +20 engagements (likes and comments combined) in the first hour”. Nurturing your post, especially in the first 60 minutes by reacting and responding to everyone who has taken the time to engage is essential if you want to reach the maximum possible audience. The algorithm will reward your responsiveness and besides, it’s just good social manners.
(16) Should I use a pod to boost my content?
I would advise against it. I ran 2 pods last year to experiment and being obliged to engage quickly/fully on content which may not be relevant/good was a tall order. Some of my fellow pod testers suspected that the LinkedIn algorithm could sniff for pod content and penalize. I think it fair to say that we had mixed results. I heard during that time that LinkedIn were investigating pods and so I asked if pods were breaking any rules. LinkedIn responded quickly “After careful review we have found that the use of pods does violate 8.2.q of the LinkedIn User Agreement. Please see 8.2. (Don’ts) You agree that you will not: q. Interfere with the operation of, or place an unreasonable load on, the Services (e.g., spam, denial of service attack, viruses, gaming algorithms)”. LinkedIn has banned the use of pods because it considers them to be gaming the algorithm. The counterargument I often hear from pod users is how will LinkedIn know, if I’m part of a pod? Go ahead and game, see what happens.
(17) Do humans decide which content succeeds/fails?
Ultimately, yes. The algorithm diagram in (2) tells us this. Understand that while the algorithm is doing all of the heavy lifting initially and quickly deciding winners and losers in the content game, LinkedIn would never leave it up to a string of computer code to decide champions. Every hyper viral post you’ve ever seen on LinkedIn has had the full backing of, and perhaps even the helping hand of LinkedIn Editors. A small and powerful committee (50+ people) ultimately decides reach. I am resigned to the fact, and have been for a while, that my content will likely never reach hundreds of thousands of LinkedIn users, not because it’s not good enough – but because LinkedIn Editors will decide that it’s not good enough. Their game, their rules. So the next time you see a hyper popular post, know that it’s popular but it’s also preferred. Gericke wrote about ‘fame’ in 2014 “My research shows that the Pulse algorithm seems to compare the ratio of the base metrics of posts in a given channel to qualify a post as a Top Post. This means that an article with relatively few views can in fact be a Top Post if its ratio between views, likes, shares and perhaps even comments are higher than those of other featured posts. In other words, once a post has been selected for a channel, if it performs well on that channel, it can get boosted by having prime positioning on LinkedIn’s top shelf.” The concept of fame and channels doesn’t seem all that dissimilar to posts that we are notified are ‘trending’ for certain hashtags. It’s also the method used to highlight and give posts top billing in our notification feed because those posts have been ‘featured by LinkedIn Editors’.
(18) What’s the secret to writing a popular post on LinkedIn?
Pete says “Authenticity is key: all the tips above work out better when members talk about things they truly care about, in a way that’s natural for them. Genuine conversation around real experiences spark better and deeper conversation. Better conversation, in turn, leads to stronger community and connection”. Sure but what’s the SECRET to going viral on LinkedIn? If you look at the type of content that is preferred by LinkedIn Editors, you’ll detect some common traits: feel-good, work relevant, career related, helpful/valuable/sensible professional advice. Interspersed with heart-tugging, deeply personal or entertaining, social sharing content, which many people will recognize if you’ve spent any time on facebook.
(19) What’s ‘Broetry’?
A LinkedIn user called Josh Fechter figured out that users liked posts which began with a hard to resist hook, were easy to read with short sentences, lots of white space. He said the hook should highlight either a problem, significant change, announcement or credibility. When asked about it, he said he was “spoon feeding people exactly what they want”. It’s a posting style that did terribly well for him. He also said that it got him banned from LinkedIn. He thinks that because of his success in hacking the algorithm, LinkedIn changed it. I can’t find him on LinkedIn (though he does have a co page), so presumably still banned. The hook method definitely works, getting engagement from a 1,300 character post is possible but you need to know your audience and you need to add value, get comments and be responsive. It’s not just about the structure.
(20) Should I tag/mention others to seed engagement on my posts?
Only if you are confident that the folks you tag will respond. I tend to agree with the theory that your content will suffer if people you tag don’t respond, or if they remove their tag. Why do I think this? We already know that the LinkedIn algorithm is sensitive to positive and negative signals, I don’t think it’s a stretch to think that the tagging response, including non-response, is being evaluated. Pete advises users to use a maximum of 5 “Use @mentions to pull other people you know into a conversation when you think they’ll have something valuable to add. Be thoughtful: only mention people that you think are likely to respond, max five is a good rule of thumb”.
(21) What’s bad for content?
Certainly over-sharing i.e posting too frequently is going to ding your reach. The algorithm diagram (2) specifically lists ‘hides’ and ‘flags’ as part of the evaluation process. I think it’s therefore reasonable to presume that other negative content related signals like delete, mute, unfollow, turn off, de-tag and report are also measured and taken into account.
(22) How important is writing for ‘my tribe’?
Paramount. As Bonnie has said, even before testing your post with a live audience it already has a good sense of “the relationship between the poster and the potential viewer”. In other words, we, the user have already provided a ton of relevant data which primes/feeds the algorithm. It already knows for example, which people, groups, hashtags, skills, employers, universities etc. we have in common. It’s smart enough to show our new content to our newest connections. But if you are only connecting and not engaging, the algorithm will know that too. Bonnie: “The feed has a sense of affinity between members. If you and I are connected but every time I post and you don’t respond, the feed will remember not to show you my posts anymore. If someone is connecting to a bunch of people but never talking to them, it won’t really get them anywhere because the feed will learn that these people are not actually interested in each other”.
(23) Do all of my followers get notified when I post?
No. Only a small percentage of followers will have your post in their feed. I’ve no idea what that percentage is or how LinkedIn determines which followers to show your post to. Perhaps the algorithm behaves similarly in relation to new connections and shows your new content to a small group of new followers? That would be logical. LinkedIn have been experimenting for a year with a ’subscribe’ feature which currently allows 117 LinkedIn users to invite others to ‘subscribe’ to their article ‘series’. Bonnie said this about the pilot in a comment on my post “Hi Phil, thanks for the feedback. I like your idea of limiting authors to one piece of content per week that is guaranteed to get distributed to 100% of people who self-elect that they want to see it. It actually sounds a lot like the new pilot program we just launched this week: ‘LinkedIn Series’, which are articles published on a pre-specified cadence and delivered via notifications to all subscribers (guaranteed!). Some people want to discover content serendipitously in their feed, but for folks who want guaranteed delivery, I totally agree: #LetTheAudienceDecide”. It’s anyone’s guess whether all users will get this feature eventually but the ability to actually allow followers to follow, would be a game changer.
(24) Should I use my company page as part of my posting strategy?
Sure. Treat your co page as another channel for your content and mix it up, alternate between publishing posts from your personal account and to your co page but don’t post the same stuff in both channels. The co page has decent analytical tools to help you keep track of followers and has SEO power, search engines index your co page, so you could attract more eyeballs from web traffic. The algorithm takes note every time a user follows your co page but if you want to maintain that relationship, you need to work it, as Richard confirms “The average reach of a company page is about 4 – 6% of the followers. But if you start following a co page, their posts will appear more frequently in your timeline for the first week. If you don’t engage, you will not see any of their updates in your timeline again. If you do engage on one of them, the algorithm will keep favoring them for a longer period”. It’s similar to new followers, the algorithm favors them initially but it’s up to both parties to demonstrate that there is affinity.
(25) What other factors are important to LinkedIn content strategy?
Interestingly Richard’s research showed that LinkedIn took a much wider view when deciding content distribution and reach. For example, he found that there was a correlation between your SSI (Social Selling Index) and reach “A higher SSI results in a higher reach, regardless the size of your network. It looks like LinkedIn is rewarding people with a higher SSI with more visibility”. He also suggests that having a fully completed LinkedIn page may be beneficial “An All-Star profile rating seems to have a positive impact on the views. It looks like LinkedIn is returning All-Star profiles a favor in the algorithm (members with “Intermediate” rating score about 30% less on views/ engagement)”.
To sum up, comments are king, they will provide you with more views than likes and shares. You need to to react/respond to every comment, if you want to maximize reach. Any kind of engagement within the 1st 60 mins is crucial for the success of your post. Try to engage with new followers and new co page followers to keep them in the loop for longer. Use a maximum of 3 hashtags, keep a list of the hashtags your fans are using/commenting on. Only ever tag a maximum of 5 users and only tag people you are certain will respond. Comment on posts that you want to see more of. Have conversations in those post threads. If you only have time to give a quick reaction, come back later to leave a comment. Focus on the quality and not the quantity of your posts. Measure engagement, not views.
Hope you found this useful. Please share it with your family, friends, colleagues and clients. Thank you!
I Know What Triggers The LinkedIn Pulse Algorithm (Nov 2014)
Spreading the Love in the LinkedIn Feed with Creator-Side Optimization (LinkedIn Engineering Blog (Oct 2018)
Strata Data 2018: Perverse incentives in metrics (YouTube) (Oct 2018)
Why LinkedIn Thinks Your Posts are “Low Quality” (March 2019)
What’s in your LinkedIn feed: People You Know, Talking About Things You Care About (June 2019)
Richard van der Blom
Research Algorithm (July 2019)
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