A Data-Driven Approach To Maximizing Your Content Reach on LinkedIn

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A Data-Driven Approach To Maximizing Your Content Reach on LinkedIn

LinkedIn is, according to Wikipedia, a ‘business and employment-oriented social networking service’.

Hmmm… now that doesn’t sound very warm and friendly, does it?

In actual fact, LinkedIn is more like a ‘human’ platform for meaningful engagement.

No longer do users simply turn to LinkedIn when they want to search for a new job or share a professional accomplishment.

Nowadays, many people are using LinkedIn to document their daily experiences, personal musings and favorite content. The smart ones are also optimizing their posts to gain maximum exposure and profile growth.

In this post, I’ll be sharing how you can adopt a similar approach to using LinkedIn. I’ll be doing this by:

  • Noting what influential LinkedIn users are doing from a qualitative perspective.
  • Breaking down data to offer a better idea of the type of posts that perform best.

Let’s get started!

The rules behind my data

Before we jump into the data, let me first offer a quick disclaimer:

I’m not a data scientist and the results of this study are by no means statistically significant. However, with data from 400 posts, we can certainly make helpful inferences.

Here’s how I conducted this study…

First, I identified four individuals who I follow or am connected with on LinkedIn. These influential users appear to be doing extremely well on LinkedIn and they have high follower counts.

I collected data on the past 100 LinkedIn posts from each of these users, noting of the number of likes and whether each individual post contained a link, photo, video, or was sharing another users’ content.

Next, I looked at the average number of likes for each individual, and converted each post into a percentage based on the average number of likes for that individual (this is seen in the ‘Likes/Average’ column in the screenshot below).

I did this in a bid to normalize the data across the four users.

It left me with the ability to distinguish both high and low performing posts. If a post in the spreadsheet has a percentage over 100%, it’s over-performing. If it’s less than 100%, under-performing.

For instance, you can see below that one of the posts listed received 172 likes, yet is still considered low-performing – whereas a post with 101 likes is considered high performing.

This is because a user with 172 likes averages a lot more likes per post than the user who received 101 likes.

Now it’s time to filter the data by post features, and find out if the inclusion of features – or the lack thereof – has any affect on performance!

So do links affect performance?

I’ve heard people say time and time again that links hurt the overall performance of posts. The reason behind this theory is that the LinkedIn algorithm favors posts without links in an attempt to prevent users from leaving the platform by becoming diverted.

This makes sense, and it definitely has encouraged people to include links in the comments instead of in the actual post copy. However, let’s see if it’s actually true.

I sorted through the data to find posts with a link in them, then looked at the average. I did the same for the posts without a link.

The difference in performance between posts with a link and those without was significant, coming in at 63.58%.

What’s even more interesting to note is that posts with a link can perform nearly 40% worse than the average, coming in at 62.81%.

I’m not trying to make sweeping generalizations as there are a lot of variables to consider. Furthermore, I’m basing the performance of posts on likes alone, not comments, impressions, etc.

Nonetheless, this is solid evidence that links can hurt the performance of your LinkedIn posts – so consider placing links in comments, or not including them at all.

What about images/video?

After filtering through my data for posts with and without images, there didn’t appear to be any noticeable difference in how they performed, only about 13%. If anything, it seemed like posts with images (I didn’t include ‘rich snippets’) performed a fraction better than the average post.

As for video, based on the data below, it didn’t appear to be a major factor. In fact, posts with either an image or a video seem to be performing in much the same way, hovering around 108-109%.

How about content sharing?

Another feature that I decided to look into was shares. How well does your post perform when you share someone else’s?

Many people believe that shared posts perform poorly. This is disappointing because generally it’s assumed that a share is a good indication of how much you enjoyed a post, as compared to likes/comments.

Here’s the complete table of data:

What does all this mean?

First off, there is no such thing as ‘hacking’ the system to optimize content on LinkedIn. That’s not the point.

What we should all aim to do is create content that aligns with our follower’s interests in a way that is best formatted for the LinkedIn algorithm.

Based on what we’ve seen here, from both a qualitative and quantitative perspective, there are certainly ways to optimize posts for maximum engagement.

Here are some of the main takeaways:

  • Avoid links. If you want to share a link, simply place a call to action at the bottom of your post and encourage people to click the link in the comments.
  • If you’re interested in video or images, try including them. Based on the data here, posts with either an image or a video actually performed a little better than the average post.
  • Incorporate people whenever possible, but make sure it benefits them in some way. This means commenting to provide assistance, responding to questions, tagging people in your posts, etc.
  • Get creative and share your story. I’ll admit, this sounds a bit cheesy.The point is that those who are exposing themselves, opening up to their connections, sharing stories and continuing the conversation in a bid to help people are the ones who truly are dominating on LinkedIn. Human beings love authenticity in social interaction. It makes us feel safe, as if we can trust the person we’re engaging with

The platform has become a mix of business and personal. This means that you need a people-focused approach to publishing there, no matter what industry you’re in.

I’d love to hear your thoughts on my data studies below – let me know how it aligns with your ideas in the comments.

Guest Author: Henry Foster is a digital marketer from the Greater Boston area. He writes about social media, content marketing, and online growth strategy at IgniteMyCompany.com.

The post A Data-Driven Approach To Maximizing Your Content Reach on LinkedIn appeared first on Jeffbullas's Blog.


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