On Facebook? You need to understand EdgeRank

Facebook EdgerankA recent post by Kelvin Newman on the e-consultancy blog entitled The ultimate guide to the Facebook Edgerank algorithm provides a detailed explanation of the way in which Facebook determines what users see in their Newsfeeds. We highly recommend you read the article. Understanding EdgeRank is critical to the effective planning and implementation of a successful FB strategy for your business. A brief bullet point summary is provided below:

  • An Edge is any interaction with Facebook that creates a piece of content e.g. a status update, a photo or video upload, comment, like etc.
  • EdgeRank is how Facebook determines which pieces of content we see first in our newsfeed
  • EdgeRank is based on 3 key criteria:
    • Affinity – how close we are to someone. The more you interact with an individual e.g. visit their page or comment, the more likely their Edges will appear in your newsfeed
    • Weight – some content items have more weight. Newman cites photos, videos and links as being more likely to appear in your newsfeed than straight text updates or likes
    • Recency – new content is more likely to appear than old content

This may all appear like commonsense but when you understand EdgeRank then a few implications become clear:

  • If you want to get your message viewed on more newsfeeds, you need to increase the affinity with your network. Newman cites an example whereby a brand might look to engage with more of its ‘likers’ before sending an important message out.
  • Consider also your use of media within status updates as photos, videos and links are more likely to appear higher in newsfeeds.
  • Timing is critical, look to post that important update when the competition for attention is lower (as well as when your network is likely to see it)
  • Re-evaluate how you measure success. Numbers of likers is not the “be all and end all”

Having been around web marketing for a number of years now, Facebook’s EdgeRank appears a lot like Google PageRank. I suspect we will be second guessing what each change and update means for both of these algorithms for some time to come.

As always your comments are welcome.

Alan, Jim and Vincent

Related Posts