The mysterious LinkedIn algorithms

Sometimes working out LinkedIn feels a bit like a cross between a meeting of Harry Potter and the IQ organisation  Mensa.  Nothing creates more confusion than trying to figure out how to get traction on LinkedIn.  So let’s unpack the hyperbole of the mysterious LinkedIn algorithms.



Constant changes, updates and new features can be eye watering. Some come with prior timely alerts and others instantly appear the next day.

There are 2 pathways to success (sic) – organic and non-organic.  The latter, non-organic is where the dodgy activities sit of paid followers and engagement pods , Paid Panels, Lempod, illegal chrome plug in content, gaming etc. 

And organic is about consistency, persistency and ethical application of content creativity and network true value.

And for both organic and non-organic,  there is a deluge of advice given on how to navigate the algorithm and raise content visibility and success.



It’s a veritable minefield of confusion and moving parts. But best practice, data and testing your own ROI in your field, industry, voice and audience is important.

Members tie themselves in knots about what is right and wrong. 

The minefield question of ‘should you put a link into your post’ has so many opinions. See the section below where I address this. 

And then the the use of hashtags gets people fired up   (read more about my hashtag research and lists here).

Look LinkedIn often will come out and state best practice, ie in the case of hashtags that 3 is the  optimal number and has significance.  Other times its just left to observations.

Reports containing definitive all encompassing  advice to not edit posts within 10 minutes, not to react before commenting, the exact best times and days to post based on tiny sample sizes etc can be confusing, incorrect and  send members into a bloody tailspin.


Firstly all  research /surveys must also advise the methodology, sample sizes, demographic breakdowns and relevant data sets to give validity to the findings. 

A survey in 2022 from Europe shared findings from analysing 10,000 LinkedIn posts and was spread throughout the platform.  There was no further information of methodology, member demographics, sectors, zones, topics, geography or other data subsets.   Some of the reported findings were general ones and well known. But others up for conjecture. 

Statistics  and data from the following sites and organisations are excellent resources of empirical evidence, qualitative and quantitative research :

A few links including the official LinkedIn’s press statistics page  includes

We Are Social / Hootsuite , / Social Media Examiner /  HubSpot, /Social Media Today/  Data Reportal, / Kepios /  Search Engine Journal and many more.

It’s important to note that  major online research and social media publications do not try and compile research and findings on ‘how to manipulate and decipher LinkedIn algorithms to report on (sic) secrets.  

Why??  Because it’s impossible to analyse and machine learning and AI is obsolete fairly quickly.  Trends are a different ball game but not absolute discoveries of AI mysteries.



In an article I wrote in 2018 on LinkedIn Jail here, I discussed how  LinkedIn distribute content.  It is still relevant. 

Here is a graph from LinkedIn’s Engineering department which they still use:



One statistical gap of confusion is how many of the 900 Mill members  post content and how many pieces if content are published daily.

It’s variously reported  that  around 2M posts per day are loaded and a range of between 2 – 8% members post their own content (average quoted generally is 4-5%).  But it is a guess.

Bonnie Barrilleaux  who is the Senior Staff Data Science in San Francisco  advised me personally that whilst they don’t share public figures of the number of content pieces published, there has been a 25% increase in content from June 2020 to June 2022.

Do refer to these useful official Help pages to analyse content data across all formats and with Creator Mode 

 View post analytics for your content  &  Post Analytics for Your Content


The discussion and old chestnut debate about whether you should or should not include external links in your Posts or Post a External article never stops raging on causing constant head scratching, Panadol and alcohol consumption.  

Look I get it that we all want our posts to do well and yes there are some very solid good practice rules to follow to ensure it’s not classified as SPAM and hence distribution throttled.  For example, stuffing 30 hashtags into a post risks a SPAM classification, as does 50 name tags

Does LinkedIn penalise posts with links within the body of a post? 

Should you ever post a external article? Should you put URL links into comments.  Will the algorithm destroy your reach and your post become invisible?  Doesn’t LinkedIn always want to maintain eyeballs on their platform and not divert away?

The questions are never ending.  And I say hogwash to the sentiment in general.  There are so many factors that determine a post distribution and engagement.   

I’ve seen posts with URLs and article links that do very well and others that bomb.  Its never a one size always fits.  I’ve posted some media article links that have had HUGE views and engagement, others died on the vine.

As LinkedIn’s editorial team content explodes internationally,  they also post links and external media articles regularly recognising the value of shared external content.

So rest petals and think of user experience, the validity of that URL and link may be valuable.  If a post bombs, it won’t be for a solo reason.  And that reason also may have jack shit to do with anything you did or didn’t do.

Please don’t consider engagement volume as the only success metric as lurkers abound on LinkedIn at a high rate.  

And don’t forget YOU can help spread the post in other ways rather than relying on the Harry Potter of the algorithm. 



Always take a critical analysis approach and don’t automatically follow everything presented without ensuring validity of research and transparency of methodologies.   Testing, re-testing and experimenting is key.

Everyone has opinions and opinions are just that. Be discerning and don’t follow something just because your mate or friend does.  And services which promote silver bullets and ‘hacking’  systems are to be avoided at all costs.

We are all navigating the realm of LinkedIn’s Harry Potter mixed with members from Mensa and trying to work out the mysterious LinkedIn algorithms.  

And a final word – given that LinkedIn is rented space and changes can totally change the game at any moment, don’t put all your content and visibility marketing eggs in the LinkedIn basket (even as good as it can be) 

For more information & LinkedIn resources:

LinkedIn Media portfolio here 

LinkedIn Services & Blogs here 

Download any of my free eBooks here (including the Top 600 LinkedIn Hashtags and guides to use)

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