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Your Audience Rules – How Facebook’s News Feed Algorithm Really Works

I recently attended an education session on Facebook’s News Feed algorithm, conducted by a social media lecturer of relatively high standing in the field. The session sounded great – insight into how Facebook’s News Feed algorithm actually works, the ‘hows’ and ‘whys’ of what appears in your News Feed and what brands can learn and implement in order to boost their organic reach. All great, all interesting. Except, the information presented was largely wrong.

This person, who speaks and presents to a great many people on social media best practices, outlined strategies that were either out-dated, ill-informed or just plain incorrect, yet stated them as total fact. And as other attendees narrowed their eyes and nodded along, I felt like standing up and saying ‘no, that’s not right’. But then that would assume I was right, and given the secrecy around the specifics of Facebook’s News Feed algorithm and how it works, maybe I was actually wrong. Maybe what was being presented here was the right info.

In order to get to the bottom of it, and clarify for all those looking to maximize the performance of their Facebook content, I did some research into what's known about Facebook’s News Feed algorithm and how it selects the content to be shown to each user. And while we can’t know every specific factor that plays a part in how content is distributed on the platform, there are quite a few well established principles that clearly indicate the path to best performance.

Seeking Attention

First off, a bit of history.

When Facebook launched News Feed back in 2006 it was a straight-up, chronological feed of all the activity of your connections.

Your Audience Rules – How Facebook’s News Feed Algorithm Really Works | Social Media TodayRemember that? The basic looking blue links, the green comments. The ‘Like’ button was introduced a year later, giving Facebook its first insight into what users were actually interested in. As Facebook became more popular, and more people started using the service, the News Feed, logically, got more cluttered, so Facebook started using Likes – along with other measures including shares, comments and clicks - as an indicative measure to show users the content likely to be of most interest to them. This worked for a while, but there were a couple of problems with this basic approach.

The first issue was that people clicked ‘Like’ for different reasons – funny cat pictures were getting heaps of Likes, and thus, flooding people’s News Feeds, while more serious content which people weren’t clicking ‘Like’ on, was being buried. Publishing click-bait style headlines became a key tactic as they garnered lots of Likes and clicks, pushing them higher in the News Feed - eventually Facebook was at risk of losing their audience because Feeds were just being crowded with junk and there was no way, under that system, for Facebook to filter and uncover better, more relevant information for users. In 2013, Facebook acknowledged it had a problem on this front and sought to correct it with a new algorithm that would uncover ‘high quality content’, the first iteration of the News Feed algorithm.

The second issue was that Facebook was becoming really popular. People were adding more friends and Liking more Pages, meaning there was more and more competition for attention in the News Feed. But people only have so much time in the day to check their Facebook updates – according to Facebook, the average Facebook user might have 1500 posts eligible to appear in their News Feed on any given day, but if people have more connections and Likes, that number could be more like 15,000. It’s simply not possible for users to read every single relevant post, based on their connection graph, each day – Facebook’s challenge with the algorithm was to create a system that uncovered the best, most relevant content to provide users with the best possible experience in order to keep their audience coming back.

“If you could rate everything that happened on Earth today that was published anywhere by any of your friends, any of your family, any news source, and then pick the 10 that were the most meaningful to know today, that would be a really cool service for us to build. That is really what we aspire to have News Feed become.” - Chris Cox, Facebook’s chief product officer (to Time Magazine in July 2015)

These were the two major challenges facing Facebook in developing the News Feed algorithm. And despite the protestations of brands who were forced to sit idly by as their organic reach slowly declined (and who are rightly annoyed at Facebook for promoting Likes as a means of reaching audience, then reducing their relevance), the numbers show that Facebook’s machine learning curation process for News Feed is actually working. In their most recent earnings report, The Social Network reported that engagement was now up to 46 minutes per day, on average, across Facebook, Instagram, and Messenger, with Monthly Active User numbers continuing to increase.

Your Audience Rules – How Facebook’s News Feed Algorithm Really Works | Social Media Today

Inside the Machine

So how does Facebook’s algorithm work? While the company is understandably tight-lipped about the specifics of the News Feed calculations - largely because it’s continually evolving - the basics have been communicated by Facebook several times over the years.

Back in 2013, when Facebook introduced the first version of the News Feed algorithm, they noted four key points of focus for people creating content on the platform:

  • Make your posts timely and relevant
  • Build credibility and trust with your audience
  • Ask yourself, “Would people share this with their friends or recommend it to others?”
  • Think about, “Would my audience want to see this in their News Feeds?”

Those core principles remain the fundamentals of the News Feed – in a 2014 interview with TechCrunch, Facebook News Feed Director of Product Management Will Cathcart outlined a similar listing for the ‘most powerful determinants of whether a post is shown in the feed’:

  • How popular (Liked, commented on, shared, clicked) are the post creator’s past posts with everyone
  • How popular is this post with everyone who has already seen it
  • How popular have the post creator’s past posts been with the viewer
  • Does the type of post (status update, photo, video, link) match what types have been popular with the viewer in the past
  • How recently was the post published

This advice lead to creation of this equation, which is a basic overview of how News Feed prioritizes content:

(Image via TechCrunch)

Of course, as noted, there are many more factors than these at play, but at its most basic, this is the logic behind how Facebook shows content to each user. But the system is always being refined.

Those refinements are borne of necessity – more people using Facebook means more content and more variables to take into account to ensure the best possible user experience for each individual. To get an insight into just how complex that equation is, take a look at the documentation behind Facebook’s ‘Unicorn’ social graph indexing system. While Unicorn was built to power Facebook’s Graph Search engine, the way that system works highlights just how many factors can come into play when trying to uncover the most relevant content for each user – particularly when you consider that a typical Facebook user’s relationship graph looks like this:

Your Audience Rules – How Facebook’s News Feed Algorithm Really Works | Social Media TodayIn the Unicorn documentation, Facebook refers to the many 'nodes', signifying people and things, and 'edges', representing a relationship between two nodes.

“Although there are many billions of nodes in the social graph, it is quite sparse: a typical node will have less than one thousand edges connecting it to other nodes. The average user has approximately 130 friends. The most popular pages and applications have tens of millions of edges, but these pages represent a tiny fraction of the total number of entities in the graph.”

Even without a full grasp of the technical complexities of such inter-connections, you can still imagine how complex Facebook’s algorithm needs to be to serve up the most relevant content, and how many potential variants have to be taken into account.

This is why it’s almost impossible to explain the full extent of how the algorithm works, and why Facebook largely avoids doing so. It also enables them to make changes without worrying about what they’ve said previously – if Facebook were to say ‘this is how the system works’ then make a change that altered that, brands that had structured their Facebook strategy around that rule would be disadvantaged (which is pretty much what happened with 'Likes' previously). As such, the core principles noted above remain the driving force and the key elements marketers should logically be focused on. The further complexities and refinements are working to support these fundamentals.

Constant Evolution

In line with this, Facebook is always seeking to refine and update the News Feed algorithm to better serve their users and deliver an evermore relevant on-platform experience. Time Magazine recently reported on how Facebook uses two primary devices to help refine and improve the News Feed algorithm – a team of around 20 engineers and data scientists who assess and evaluate the results of tests and updates to determine the best evolution of the system, and a group of some 700 reviewers, called Facebook’s ‘Feed Quality Panel’, who deliver real, human feedback on their News Feed results, which then help the data team make more informed decisions.  

"...[members of the Feed Quality Panel] write paragraph-long explanations for why they like or dislike certain posts, which are often reviewed in the News Feed engineers’ weekly meetings. Facebook also regularly conducts one-off online surveys about News Feed satisfaction and brings in average users off the street to demo new features in its usability labs.”

Through this process, combining feedback from real people and improved machine learning, Facebook is always moving the News Feed algorithm forward and uncovering new system best practices – this is why we see so many changes and updates to the algorithm rules. Newer factors like ‘time spent reading’ are brought in as Facebook learns from user behavior – content that people click 'Like' on before reading, for example, is not given as high a rating as content that’s Liked after reading, because if you’ve taken the time to read something and then Liked it, that’s a more considered judgement of quality than a knee-jerk response to a headline. Such refinements are logical and thoroughly tested, and Facebook has gone to efforts to underline that the way the system is weighted is entirely dictated by each individual users' actions and preferences. The way Facebook’s algorithm defines ‘high-quality’ in this sense is entirely user driven – if you like cat memes but hate posts from The New York Times, you’ll be shown more of the former.

“...there’s a line that we can’t cross, which is deciding that a specific piece of information - be it news, political, religious, etc. - is something we should be promoting. It’s just a very, very slippery slope that I think we have to be very careful not go down.” - Adam Mosseri, Project Management Director for News Feed

Due to this, it’s up to each individual brand and business to create content that appeals to their specific audience, and caters to that audience's needs.

It’s worth noting too, in considering Facebook reach and how the system uncovers and highlights content to users, that the actions users take after exposure to your content are far more important than them seeing it in the first place.

This was pointed out by Facebook marketing expert Jon Loomer, who noted that even if your Page reach has declined, that’s not really relevant – what is relevant is whether your website clicks have also declined as a result.

“Let’s assume for a moment that reach actually did drop. If all engagement remained healthy — including website clicks and conversions — what does that drop in reach mean? It would mean that Facebook was showing your content to people most likely to engage favorably — which is what we as marketers and users would want.”

It may just be that, as a consequence of Facebook improving their algorithm, that your Page reach will inevitably drop, because your content is being shown to a more targeted and focused audience based on their behaviors. Which isn’t necessarily a bad thing.

In all, the main thing to focus on in order to maximize Facebook reach is quality content, as defined by audience response. The more engagement, the more interaction, the more utility you can provide for your audience, the more likely they’ll want to see more information from you, which they’ll indicate through their Facebook actions, be those direct (Likes, shares, comments) or indirect (time spent viewing). In that sense, the core fundamentals of Facebook content remain the same as they did the day the News Feed algorithm was introduced back in 2013:

  • Make your posts timely and relevant
  • Build credibility and trust with your audience
  • Ask yourself, “Would people share this with their friends or recommend it to others?”
  • Think about, “Would my audience want to see this in their News Feeds?”

Main image via PromesaArtStudio/Shutterstock

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