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Posted By
Andrew
Marshall
andrew.marshall@cognitomedia.com

My LinkedIn post on Netflix’s results last week got over 121,000 impressions. That’s several times my highest impressions from a post to date, so I’m keen to understand why that happened, how to replicate it again, and more importantly how our clients can also maximise their posts. 

This particular post was written in five minutes: it was not detailed or original.  I simply said that a 32% fall in the Netflix stock price, on weaker subscriptions, made a mockery of the scale of investment research and active management on Wall Street covering a big stock like that.

What drove impressions in this case might be:

  • Speed - the post was within two hours of the earnings release

  • It had a simple, emotional point of view, which may have helped get seven shares 

  • It linked to a major publication’s story on the Netflix stock drop (WSJ)

  • It was about a big topic – the stock performance of a company everyone has heard of globally - not the niche topics I often love.

Unusual and striking was that the impressions on the second, third and fourth day were all higher than on the first.  This is all about how the LinkedIn algorithm works.  

Whenever you post, LinkedIn labels the post as “spam,” “low-quality,” or “clear” in near real time. If you make it through the spam filter, you enter what’s often called ‘the golden hour’. LinkedIn measures initial engagement with your content to determine if it’s worthy of moving on into other’s feeds. If you have a good ‘golden hour’ then your post is most likely to stay in circulation, and keep gaining momentum. 

As a post gathers audience, LinkedIn continuously predicts whether it likely to go viral. It monitors the network reach of the original poster, members interacting with the content, and signals like the velocity of likes, shares, and comments.  Its “virality predictors” aim to block spam/low-quality content going viral and cluttering the feed, while higher-quality content will appear more widely in people’s news feeds. It is worth noting that engagement isn’t all equal: a share or comment, for example, is worth more than the more passive like of a post in determining its quality. 

Figures showing the reach of my post on market data and the Netflix share drop

 

If the LinkedIn algorithm classifies the post as “clear”, it will cycle a post until engagement slows down.  The algorithm continually assesses whether the post is “clear”, so that a post could in theory be classed as 'clear', but then become 'spam'. Conversely, a “low quality” or “spam” piece could gather enough momentum that it gets reclassified to 'clear'. Some top content is then selected for manual review: in contrast to many other social platforms, human editors have the power to decide whether your content will be displayed even more widely on the platform, or if it will plateau as is.

Engagement on this post was good, but did not rise in line with impressions: the post got about 105 likes and 25+ comments.  I’ve had posts with many fewer impressions that have done better on comments.

What happens when a post goes (mini) viral is quite interesting.  As many will know, LinkedIn analytics (see below) can show you the top ten job titles, top ten companies, and top ten geographies.  Main takeaways on this: 

  • Quality of impressions (ie relevance to me) does not increase in line with volume.  In other words, I usually see job titles like CMO, head of communications in my analytics.  In this case, partly because the topic was a stock price not communications-related, the top ten job titles broadened to sales, finance and tech roles.

  • The top ten companies also broadened to very large companies, as opposed to seeing my main clients (and some PR competitors) as usual in the top ten.  Companies where I know more people will certainly have featured, but in this case below the top-ten level that LinkedIn discloses. In fact looking at the analytics over five days showed me how the top ten shifted.

  • The geographies also skew a bit differently, probably in part driven by the shares, with a lot of impressions from India kicking in, in addition to the US and UK.

  • The post got me picking up around 20 followers – of varying business use to me.

  • Views of my profile went up considerably, and it will be interesting to see if they remain elevated.

Most of the time, anyone using LinkedIn as a business tool should focus on high quality content that reaches the specific audience you care about.  But the occasional post that reaches a much wider audience and grows your profile can’t hurt either.

Andrew Marshall is Cognito's vice chairman based in New York. He has more than 5,000 connections on LinkedIn