Talking Facebook, EdgeRank, and Graph Search with the University of Wisconsin–Madison

I ventured up to the University of Wisconsin–Madison on an unexpectedly frigid day to discuss a variety of topics including Facebook, EdgeRank, and Graph Search. Thank you to the brave souls who journeyed through the subzero temperatures—on a Friday nonetheless.

Chad Wittman Talking About EdgeRank

I was happy to lend my perspective and suggestions to a thriving and intelligent group, wide ranging in expertise and focus. Many Page Admins had experienced a decrease in Reach sometime around late September—most Admins want to know why, and what they can do to reduce that effect. I will attempt to recap my discussion through the narrative of this blog post.

What Is EdgeRank?

When discussing Facebook’s news feed, the EdgeRank algorithm needs to be addressed. For Facebook Pages, content is ultimately governed by the EdgeRank algorithm when determining the success of a Post. The higher the value of EdgeRank for an object in the news feed, the more likely people will see it. Understanding this algorithm is imperative.

A look at the algorithm:
er_algorithm_graphic

What Changed In September: Negative Feedback

Facebook increased the weight of Negative Feedback. Now Posts and Pages that receive high levels of Negative Feedback are contributing to lower Reach levels. For some Pages the change has been devastating, while for others the change has been relatively modest.

Below is a ScreenShare that focuses on Negative Feedback:

It should be noted that every time we study Reach, we almost always find that it has decreased. This is the nature of a finite resource with an ever-expanding catalogue of content to be displayed. The news feed only has X amount of real estate, with more content, more people, and more stuff all the time, so it’s easy to see why Reach is slowly decreasing. Think of it like a developed plot of land with settlers, businesses, livestock, children, and stagecoaches—it will get crowded quick.

What Can Page Admins Do About Negative Feedback?

First and foremost, understand that this is a normal aspect of Facebook marketing. The trick is to continue to drive engagement by connecting fans with interesting content. Fans are quick to report Posts as Negative Feedback. With Facebook’s new emphasis on this type of feedback, it’s imperative to avoid being reported.

Negative Feedback on Faecbook

Avoid being reported by keeping your content within your fans’ expectations. If they signed up to receive deals, be sure to keep them in the loop about deals, as opposed to cat memes.

Understanding your audience is vital. Certain fans will be online at different times of day, and will consume different content formats at different times of day.

I often use the example of an audience that does a lot of commuting. This audience may be more inclined to engage with Photos during their commute, while consuming detailed information shared via Links after hours, while at home. We actually see this with our EdgeRank Checker fans, they tend to consume Photos in the morning and Links in the evening.

What is Graph Search?

Facebook is making an attempt at revolutionizing search. While I don’t think Graph Search is quite there yet, the underlying concept could be interesting.
what-is-gs

I tend to use the example of a user searching for “pizza”. On Google, a search of “pizza” pulls up three paid links (which a vast majority of users have evolved to avoid) with three organic results below. The three organic results tend to favor major retail brands, due to extremely high PageRank when compared to local pizza places. Google attempts to decrease this affect by displaying Google Places results in the 4th-10th search result listings. These objects use more local input signals, such as reviews, to help provide exposure for local pizza places.

Google Search - Pizza

When asking the room, the most popular pizza place was Ian’s Pizza hands down. Facebook has an opportunity to vastly improve this accuracy. In Google, Ian’s Pizza was placed in the fourth overall spot, while with Facebook’s Graph Search it landed at number five. This is just the beginning. Facebook is still only officially listening to a handful of input signals. I fully expect these search results to become increasingly more relevant to users as time goes on.

Facebook Graph Search Pizza Results

Two things need to happen to make this worth Page Admins’ time:
1)   Facebook users need to actually use Graph Search
2)   Search results have to be more compelling and relevant than Google’s

If these two conditions are met, there is a chance that Facebook could begin to take down the behemoth that is Google. This is a big “if”, but an “if” nonetheless. My recommendation to marketers is to make sure you’re prepared for the chance that it does take off.

You can learn all about how to optimize your brand for Graph Search here.

I hope that this recap helps anyone who was unable to attend, or was interested in learning about EdgeRank and Graph Search from the discussion. Thanks again to the University of Wisconsin for having me out!

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