There are fundamentally two ways to reach an audience — organic and paid. On Facebook, organic reach is the number, or the proportion of people a marketer can reach for free by posting to the company’s Page. And paid reach is what the marketer pays for.
When marketers post messages on their Fan Page, only a fraction of those messages reach their fans, and that fraction is getting smaller. According to various studies, Facebook’s organic reach has plunged — to as low as 2% in 2016 and it continues to decline.
The reasons for the decline were outlined by Brian Boland, Facebook’s VP of Advertising Technology, in June 2014. He said that more and more content was being created and shared every day, and that for the average person, there were 1,500 stories that could appear in her news feed each time she logged onto Facebook. So rather than show all possible content, Facebook’s news feed shows each person the content that is most relevant.
What is most relevant, of course, is a matter of opinion, and that opinion is built into the logic of Facebook’s machine learning algorithm that decides what gets filtered. Naturally marketers are keen to get a sense of the logic that controls the algorithm so that they can craft content that has greater likelihood of reaching their fans.
Your news feed on Facebook is essentially a summary of a selection of the actions by your friends on Facebook. It also includes a selection of the actions on the pages that you follow/like. (Liking a page makes you a fan of that page).
The range of actions on Facebook includes updating status, commenting on a status update, tagging a photo, joining a fan page, or replying to an event. When you take an action, it triggers what Facebook calls an “Edge”. Depending on how it ranks, relevant content on the action, could appear on your friends’ or fans’ news feed.
The ranking algorithm scores the content for each individual, and only the ones that rank on top for that individual are shown on his or her news feed.
To get a sense of what ranks high, Socialbakers, a social media analytics company, conducted a study, reported by Business Insider, covering 4,445 Brand pages and more than 670,000 posts between October 2014 and February 2015. Findings of the study (see Exhibit 13.14) revealed that video was the “most effective way to reach users in the newsfeed, driving more than twice as much reach as photo posts”.
Only an average of 4 out of every 100 (3.7%) page fans got to see a photo post, compared with, videos that garnered 8.7% on average. Links and text-only (defined by Socialbakers as “status”) posts follow with organic reach averaging 5.3% and 5.8% respectively, though their ranking varied over the course of the study.
Considering that the use and popularity of videos has grown with the penetration of high-speed internet, it is not surprising that they have supplanted photos, which used to garner high organic reach some years back. Having said that, the rapidity of the growth suggests that Facebook may consciously be driving the use of video.
In 2010, Facebook spelt out three factors — affinity, content weight and decay — used by their algorithm to rank content, and a simplified version of the algorithm was presented as:
Where ue is user affinity, we is content weight and de is the decay.
This algorithm, which was called EdgeRank, is no longer in use since 2011. According to company sources, though the new algorithm is based on machine learning, and though it takes a large number of elements into account, the original three factors remain important. It remains useful, therefore, to understand their role in the context of the EdgeRank algorithm.
Affinity is a measure of the strength of the connection between the user and the content creator. For instance if you write frequently on a friend’s wall or regularly interact in other ways, and you have a large number of mutual friends, your affinity score is likely to be high.
Each interaction has a different weight. Commenting, for instance, carries greater weight than liking, which outweighs clicking.
Taking your social graph into consideration, the affinity score, in an iterative manner, depends also on your friends’ actions, and on their friends’ actions. The weights differ depending on the strength, frequency and recency of the interactions with the friends.
And to reflect recency, the interaction weight is adjusted by multiplying with the reciprocal of the time (, where is the time) since the interaction occurred.
Importantly, affinity score is one-way, it recognizes that the extent of your interaction with a friend is not the same as the extent that he interacts with you.
Weight: Each category of edges has a different default weight. Somewhat similar to the standard for computing affinity, commenting carries greater weight than liking, which outweighs clicking. Moreover, as can be seen from Exhibit 13.14, videos have higher weight than links which weigh more than photos.
Decay: Stories are weighed by multiplying with the reciprocal of the time (, where is the time) since the action occurred. Decay is also dependent on the length of time since the user logged into Facebook and the frequency of logging in. For instance, if you are very active on Facebook, the decay would be faster, so that you do not keep seeing “old news”.
Though it is no longer applied, the EdgeRank algorithm gives some insight to the key factors that contribute to securing high organic reach. The machine learning algorithm, however, takes many more elements into consideration to estimate factor scores and rank the content.
One improvement is the inclusion of global interactions in addition to personal interactions. This means that if some content gains heavy traction globally, it would raise the ranking of the content even for users whose personal interactions with the content might not be strong.
Relationship settings also play a bigger role. Though algorithms are capable of accurately deducing affinity, Facebook gives weightage too to the relationship labels, i.e. “close friend” versus “acquaintance”, set by their users.
The weight for category of content is adjusted at the individual level as well now. So for instance, if your past behaviour suggests a greater propensity to comment on photos, you will have higher content weight for photos.
The “hide post” and “mark as spam” features introduce additional variables that contribute to content ranking. For these variables, a decay parameter is introduced so that choices made in the recent past have a bigger impact.
Interactions with Facebook ads contribute yet another stream of variables that feed into the machine learning algorithm, and contribute to the ranking of content.
Relying on a vast number of variables, Facebook’s machine learning algorithm works in a manner that ordinary people find hard to comprehend and, therefore, difficult to contest. It protects Facebook from the scrutiny of their numerous stakeholders with their diverse agendas.
Bearing in mind that the algorithm is doing what it is intended to do, to secure high reach you need to create content that engenders greater affinity with your fan base; content that your fans find interesting and useful. They are more likely to read and respond if the posts are brief. To spark interactions you need to have call-to-action triggers, hashtags and website links (at present, Facebook does not support hyperlinks). And to increase the content weight, you should use more video and audio, instead of photos.
That said, considering the decline in organic reach, to target more eyeballs, you will increasingly need to rely on Facebook’s paid options. There are two routes to consider — page boosting and Facebook advertising.
Marketer can “boost” their post by clicking on the “Boost Post” button on the bottom right of their post. Boosting allows them to expand the audience beyond the post’s organic reach. Boosted posts appear in news feeds, and are not shown in the right column. Marketer have the option to choose their audience, and set a budget based on how many people they want to reach on Facebook and Instagram, and how long they would like their boost to run.
Boosted ads come with 3 targeting options:
Though it is easy to use, boosting a post is not the recommended approach if you are seeking to optimize your returns on advertising spend. This is because, in the context of digital marketing, your targeting options are severely limited. Facebook is engineered to finely target advertising, yet in the absence of campaign objectives and targeting options, it optimizes boost posts purely for greater engagement – i.e., more likes, shares, comments and so on. For those marketers who are seeking other objectives such as conversion or sending people to their website, they are constrained by the lack of control on placement of posts (i.e. mobile vs. desktop) as also the lack of targeting options.
In comparison, the advertising options open to marketers, when they click the “Create an Advert” button are far richer. Besides allowing them to more finely target their audience, the algorithms that channel their advertisements, do so in a manner that optimizes spend based on the campaign objectives they selected.
As they create their campaign, first and foremost, the advertiser needs to have a clear objective. For this purpose, Facebook’s ad console offers a broad range of “campaign objective” options for them to choose from, as shown in Exhibit 13.15.
Facebook devotes considerable time and effort to optimizing their advertisers’ campaigns, as can be gauged from the performance metrics. This is beneficial not only for the advertisers who benefit from superior returns, but importantly also for users, who are sheltered from poorly targeted content that is of little relevance to them.
Advert provides a few formats for boosting posts that are grouped under the “Engagement” objective. The look and feel of the post remains the same irrespective of whether it is boosted from the ad console or from the Page. The key difference is that from the ad console, advertisers have more targeting and placement options, as well as additional features such as call-to-action buttons. Also, unlike ads boosted from the page, these ads are labelled as “Sponsored”.
Besides the array of targeting options outlined in the section on targeting, Facebook Adverts allow advertisers to create their content in the ad console without displaying it on their Facebook page. These news feed ads that do not actually get published to the news feed of the advertiser’s page, are called dark or ghost posts.
Dark posts allow advertisers to run different ads as sponsored posts, targeting distinct consumer groups. They may split test headlines and create personalized messages for different demographic and geographic targets, simultaneously running multiple ads, one for each of the target group.
Facebook Adverts call-to-action button is useful for promoting actions such as ‘buy’, ‘sign up’, ‘download’ and ‘contact us’ to name a few. These buttons greatly improve click through rates.
For placing their ads, advertisers can choose from these three choices — news feed, mobile, and right column. News feed and mobile ads are more versatile, coming with additional options such as call-to-action button. Moreover, because of its location and size of image, the right column ad is less likely to attract the user attention, and it underperforms considerably on click-through rates. It does however, cost much less than the other options.
One of the benefits arising from the partnership between Facebook and Shutterstock is the free access to the millions of stock pictures from Shutterstock’s database. This saves considerable time and money for advertisers.
Facebook supports a wide range of ad formats, including the ones listed below, to suit the diverse needs and objectives of advertisers.
Bidding: Facebook supports an automated bidding and optimization system called Optimized CPM (oCPM). The system analyses the data and optimizes the advertiser’s campaign delivery to only hit users who are more likely to complete the desired action.
A/B Testing: Facebook also supports automated A/B testing (aka split testing). Testing multiple ad variations is very effective way for advertisers to refine their content and improve a campaign’s performance.
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