Introduction of EdgeRank
Every search engine has its own proprietary ranking algorithm and Facebook is not an exception. The ranking algorithm that Google ranks contents and websites is commonly known as Page Rank. And it is obvious that every search engine use different parameters to rank their contents and websites high on the search engine result page. But have you ever wondered that social networking sites like Facebook also use specific and proprietary ranking algorithm to rank person and business pages.
So let’s understand EdgeRank, the proprietary algorithm of Facebook step by step. The search algorithm of Facebook depends on certain factors and in this article we are going to describe all those pillars that are important in optimizing your person page or business page. The main three pillars are as follows:
EdgeRank is the proprietary algorithm of facebook and it uses this algorithm to rank a particular person page or business in its algorithm. These three main pillars are Affinity Score, Edge Weight and Time Decay.
Three Pillars of Edgerank
These three main pillars are Affinity Score, Edge Weight and Time Decay.
Affinity score is the numerical value assigned to users as per your activity the person in the Facebook social media space. Means every activity of the user into account by Facebook. Each like, each click, each comment and each sharing has its own value and each one of these contributes a lot in determining the total Affinity score. So more is the number of clicks, likes, comments, and sharing for your content higher you are likely get the higher rung of Facebook ranking.
The affinity score of page or profile also depends a lot on the divergence level of people. If there are two people having common friend and you are searching for a third one then Facebook will search for friends that you have common friends.
Each activity that a user does on Facebook page has different weight than the other. For example each click that you do get a weight-age and same is the case with comment and sharing. Facebook considers likes as less valuable than that of liking and a liking has less value than that of sharing.
In a similar way Facebook gives higher weight-age videos and photos than texts. So if you are tagging a video it will get higher edge value than tagging a text link or article.
Time Decay edge rank
Facebook gives more weight-age to contents and stuffs that are current and updated. Just like Google gives more weight-age to latest and updated content same is the case with Facebook. Any content or stuff that is gaining social traction and sharing is more likely ranked high. A content that is popular one time will gain different weight-age while when it loose social engagement and recognition its value fades way slowly.
The ranking algorithm of Facebook is not constant and stagnant but it remains changing and like Google, Facebook to keep on tweaking it often.
How to optimize a fan page
There is no single way by means of which you can optimize your profile page or fan-page. All you can do is make your page user friendly by offering relevant content onto it. You will have to keep users engaged to rank high on the Facebook algorithm. Though there is sure and short method to get your fan-page optimized for Facebook still there are certain activities that you can do to improve your ranking on Facebook search algorithm.
Some of these activities are as follows:
- Try to increase the number of likes to your page.
- Try to increase the number of friends to your page.
- Offer relevant and appropriate contents to user with your Facebook-page.
- Try to improve the rate of engagement to your Facebook.
Thus as a whole we can say that there is not a certain method and rule to optimize a Facebook page still you can do certain activities that can help you get higher rank on Facebook search. Hence we can say that if you are B2C company you want to optimize your facebook profile. For example if you are a pediatrician and looking to grow tour busines then you should search for seo for pediatricians and optimize your faecbook profile.