How the Facebook Algorithm Works in 2021 and How to Make it Work for You
By Paige Cooper
Source: Hootsuite
Good morning to everyone except for Brian, who just asked the company-wide Slack channel “wow why do our organic Facebook numbers so bad?” Well, Brian, the short answer is the Facebook algorithm. Read on, and we’ll explain.
First, let’s look at some benchmarks.
As of the end of 2020, organic reach is still on the decline. The average reach for an organic Facebook post is down to 5.2%. (For the record, at the end of 2019 it was 5.5%, and the year before that it was 7.7%).
Meanwhile, the average engagement rate in 2020 for an organic Facebook post was 0.25%. That number drops to 0.08% for those of you with more than 100k followers.
These numbers should make everyone feel a little bit better (everyone except for Brian, who should feel sorry for being rude). The algorithm can be pretty tough on branded organic Facebook content.
But every Facebook marketing strategy needs both organic and paid content, which means it’s time to buckle up and figure out what this complex, mysterious galaxy brain wants us social media managers to do.
Fortunately, Facebook just dropped a bunch of new information on the algorithm, so we’re going to fill you in on the latest details.
What is the Facebook algorithm?
The Facebook algorithm decides which posts people see every time they check their Facebook feed, and in what order those posts show up. For its part, Facebook would like to remind us that there is no single algorithm, but rather “multiple layers of machine learning models and rankings,” built to predict which posts will be “most valuable and meaningful to an individual over the long term.”
In other words, instead of presenting every available Facebook post in chronological order, the Facebook algorithm evaluates every post, scores it, and then arranges it in descending order of interest for each individual user. This process happens every time a user—and there are 2.7 billion of them—refreshes their newsfeed.
While we don’t know all the details of how the Facebook algorithm decides what to show people (and what not to show people) we do know that—like all social media recommendation algorithms—one of its goals is to keep people scrolling, so that they see more ads.
What does this mean for brands? When it comes to earning more organic reach, the Facebook algorithm will reward you for posting content that people engage with.
A brief history of the Facebook algorithm
The Facebook algorithm isn’t static; engineers are constantly tinkering with it.
To make its predictions, the algorithm uses thousands of data points, a.k.a. ranking signals. Over the years, ranking signals have been added, removed, and had their importance adjusted, depending on what Facebook thinks users want to see.
Here are some of the more notable changes.
2003-2009
First things first: we all know that Facebook was born in 2004 when Mark Zuckerberg got dumped for being conceited (or at least, that’s what I learned from finally getting around to watching The Social Network).
Non-fictional accounts of Facebook’s history, however, confirm that:
- The Facebook newsfeed debuted in 2006.
- The Like button showed up in 2007.
- In 2009, Facebook premiered a sorting order where the posts with the most Likes got bumped to the top of the feed.
2015
Fast forward a few years to 2015, when Facebook became concerned enough about user experience to start downranking Pages that posted a high volume of overly promotional content. (i.e., organic posts with content identical to ads.)
Also in 2015, Facebook gave users the ability to nudge the algorithm directly: the “See First” feature let users indicate that they’d like a Page’s posts to be prioritized in their feed.
2016
In 2016, Facebook added a “time spent” ranking signal. In other words, it started measuring a post’s value based on the amount of time users spent with it, even if they didn’t like or share it.
Live video was also prioritized, as it was earning 3x more watch time than regular video.
2017
This was the year that Facebook started prioritizing emotional reactions, by weighing reactions (i.e., hearts or the angry face) more than classic Likes.
Another ranking signal was also added for video: completion rate. In other words, videos that keep people watching to the end are shown to more people.
2018
In January 2018, Zuckerberg announced that the Facebook algorithm would now prioritize “posts that spark conversations and meaningful interactions.” (This was apparently in response to widespread criticism about Facebook’s negative effects on, you know, the fabric of society as a whole.) The changes were meant to increase the quality of the time people spend on Facebook, and take responsibility for how the platform affects its users’ mental health and overall well-being.
Brands had valid concerns about this shift. Posts from friends, family and Facebook groups were given new weight, over and above organic content from organizations and businesses. To get traction, brands would now need to earn a lot more high-value engagement (eg., comments, reactions, comment replies—and if a post was shared over Messenger to a friend, that counted too).
2019
Updates in 2019 included prioritizing “high-quality, original video” that keeps viewers watching longer than 1 minute, and especially video that holds attention longer than 3 minutes.
Facebook also started bumping up posts and content from “close friends”: i.e., those that people engage with the most, whether that’s by tagging each other in photos or DMing in Messenger.
Meanwhile, Facebook was receiving a lot of criticism on two fronts. First, the algorithm’s role in the spread of dangerous misinformation. According to critics, the 2018 algorithm change increased outrage and divisiveness, political polarization, and promoted misinformation and borderline content. And secondly, critics did not like the techniques or quantity of personal data that Facebook was collecting in order to feed said algorithm.
2020
Facebook announced that it was helping users understand the algorithm, and take control of their own data to give the algorithm better feedback. However, people have been increasingly concerned about their privacy, and for many, “more relevant ads” does not seem like a worthwhile trade-off.