Ever wondered what makes content go viral on LinkedIn? If you’re a marketer or a business development professional, then this post about the LinkedIn algorithm is for you.
We’ll dive deep into how it functions, and how you can leverage it to reach more audiences.
Table of Contents
What is the LinkedIn algorithm?
To understand the algorithm, we’ll need to first understand the purpose of LinkedIn.
LinkedIn was created to connect the world’s professionals in order to make them more productive and successful.
The LinkedIn Feed is at the heart of this worldwide professional community, allowing its users to discover and participate in the conversations taking place among their connections, within their groups, and sparked by the Influencers and companies they follow.
LinkedIn users share their thoughts, career news, queries, positions, and suggestions in a variety of formats, including video, photo, brief text, and long-form pieces. Each of these initiates a conversation.
When a member visits LinkedIn, a machine learning algorithm initiates and searches for the most relevant conversations for the member. The algorithm sorts tens of thousands of posts in a fraction of a second and places the most relevant at the top of the user’s feed.
That’s essentially what many Marketers call: The LinkedIn Algorithm.
What are the benefits of understanding the LinkedIn algorithm?
Understanding how LinkedIn selects content to show to its user is crucial in marketing and business development.
This would help you reach more users at a fraction of the cost (or no cost).
Josh Fechter, a growth hacker, understood how the algorithm worked and generated 2M views in only 6 months. And all that was generated Organically.
That’s easily the equivalent of $100k USD of ad cost that he got for free.
The “Broetry” writing method took advantage of the algorithm. It has since been banned and this method no longer works.
I do not recommend chasing the algorithm updates, but having a basic understanding will at least give you a slight edge over others.
Comprehending what LinkedIn wants for its users will help you deliver content that’s suitable for the LinkedIn environment. You’ll be able to design a better marketing strategy on LinkedIn
How does the LinkedIn algorithm work?
Thousands of signals flow into the LinkedIn algorithm, allowing them to learn a member’s preferences and customize the feed for a specific user.
These signals are classified into three types:
- The user’s identity: Their connections, the company they work for, job skills, and overall identity will be important signals
- Content relevance: Is the content receiving high engagement and views? What is the content about? How fresh is the content? Is it in a relevant language to the user? Were there any mentions in the content that are relevant to the user (companies, people, topic tagging)?
- A user’s past behavior: What type of content has the user engaged with in the past. Whose content have they engaged on before? What have they saved? Which profiles are they following? What type of content does this user spend the most time on.
These signals will assist LinkedIn members in finding the most relevant interactions that will help them become more productive and successful.
How to beat the LinkedIn algorithm
These latest core updates to the LinkedIn algorithm have shifted the type of content that you should create. Here are some of the most important ones you’ll need to know.
Use the latest LinkedIn products/tools
Whenever LinkedIn launches a new product, they’ll definitely try to provide those products with more exposure. For example, when LinkedIn polls was first launched, the algorithm seem to push more impressions to it.
Not all products will work out as we can see with LinkedIn stories. But it is worth a test since LinkedIn would definitely boost its newer products for its users to review.
Keep in touch with their product updates and be the first to use them, even though the format might be uncomfortable. You might gain an out-sized ROI before everyone starts using it.
Optimize your content for Likes (reactions), Shares, and comments
There are 3 factors that affect the feed ranking system.
- Probability of the user taking action
- Expected downstream impact (Clicks, reactions, and shares)
- Expected upstream impact (Comments etc)
Downstream impact refers to the virality of posts. Whenever someone interacts with a post, it gets shared with their network/connections.
Upstream impact refers to how much “value” the content creator gets. A comment for example is an upstream impact because it encourages a creator to post more content.
The most effective way to “game” this is to incentivize or give a strong reason for a user to take action. Here are some examples from within LinkedIn and from Twitter. Giveaways also work.
Optimize your content for dwell time
LinkedIn has acknowledged that ranking by reactions, shares, and comments as it’s following shortcomings.
- Click and viral activities are uncommon, especially among passive feed consumers. While these members may continue to view the feed and find value in the updates they see, they may be hesitant to do click and viral actions.
- Click and viral actions are generally binary indications of engagement—you either do or do not do the activity. When it comes to sharing actions, the text associated with a remark or re-share (if available) can provide a deeper signal, however, it can be more difficult to comprehend.
- Clicks are distracting signals of engagement. For example, a member may click on an article but immediately close it out after determining it isn’t relevant, and then return to the feed within a few seconds. These are referred to as “click bounces”. This noise affects the scoring and feed experience of a member.
To compensate for some of the flaws with click scoring, LinkedIn started using dwell time to see whether it could help improve feed ranking.
At a high level, each feed update generates two forms of dwell time. The first is dwell time “on the feed,” which begins measuring when a member scrolls through their feed and at least half of a feed update is displayed.
Then there’s “after the click” dwell time, which is the amount of time spent on content after clicking on an update in the feed.
What does this mean?
Create intriguing content that gets people to stay on your post for as long as possible. Use videos, documents, and images that spark curiosity. Use good copywriting that hooks users into reading/viewing the entire content.
Essentially, create irresistible, in the feed content.
It’ll be interesting to test a “Find Wally” image to see how it performs.
We’re half kidding.
Leverage LinkedIn’s content approval process
Maintaining the quality of LinkedIn users’ content experiences requires keeping the LinkedIn feed relevant by recognizing unprofessional and spammy content.
This will help LinkedIn to provide timely and relevant content.
At the beginning, Linkedin will predict whether a share will go viral. In addition to the computed content quality scores, LinkedIn monitors the original poster’s network reach, members interacting with the content, and periodic signals like the velocity of likes, shares, and comments for this forecast.
These algorithms highlight any content that requires manual review. The process is both man and machine.
The process also takes into consideration member-reported feedback on the posts.
These member flags are monitored in real-time, and content that receives a lot of flags is examined.
What does this mean for you?
Don’t create spammy content and ensure that you get engagements fast. Early engagements do help.
Find a community of similar creators who will authentically engage with you. Do not use PODs although it will help short-term. PODs are very obvious to humans after a while.
Final Thoughts on LinkedIn’s Algorithm
Understanding the algorithm is great but don’t chase it. It will always be changing and pegging your entire B2B Marketing strategy on the algorithm isn’t smart.
Instead, focus on truly delivering valuable content in the feed and all the above strategies should naturally fall in place.
