Impact of Social Signals on Google Search
In 2010 Matt Cutts explained how Google uses Twitter and Facebook links as a ranking signal. He also mentioned that Google tries out to observe the reputation of public accounts on Facebook and Twitter. According to his last explanation in 2013, Google does not rate how many followers or likes someone has. Neither Facebook or Twitter are treated in a special way.
Causation and Correlation
The screenshot below is an excerpt of a test with six websites in six similarly sized cities in the USA. Also the websites were in the same niche. As you can see social signals from Facebook and Twitter had a significant impact on the Google ranking of the promoted websites. Obviously there is a relation between the Google ranking and social signals, but to understand this relation it is necessary to differentiate between causation and correlation.
A simple example for the difference between causation and correlation is the fact that crime rates are higher when lots of people are eating ice cream. Does that mean that ice cream consumption is the causation of crime? Of course not. More probably, it's the weather that affects people to eat more ice cream and if the weather is getting better crime rates are rising as well.
How powerful is a single tweet?
Due to correlation it's difficult to measure the cause and effect of social signals on the Google ranking of a website. Here is a fictive example what might happen if you tweet a link to your website.
1. Small Fanbase
To keep it simple, you are a new on Twitter and have ten followers. What will happen after your tweet? Likely nothing because you reached only a handful of people.
2. Large Fanbase
Perhaps one of your followers retweeted your tweet to his followers and luckily this person has a large follower base. Sadly it did not generate any new visitor to your site. Why? Maybe this person is just following everyone to get more followers and does not take care of quality and interaction. So having a large fanbase is not a guarantee for a better ranking.
3. Popular Hashtag
Let's say someone else retweets you to his single follower, but adds a popular hashtag to the tweet and you see lots of new visitors on your website. How is that possible? The reason for this increase might be the usage of a popular hashtag, which might be checked by millions of people.
4. Widgets and Content Aggregators
It's also possible that tweets with the popular hashtag are shown on several websites via a Twitter widget. On one of those websites someone sees the hashtagged tweet and visits your site. This person has not a Twitter account, but uses a content aggregator like scoop.it to share the tweet.
5. Public and Private Accounts
The scooped tweet with the hashtag is seen by two people. One of these people shares the scooped tweet with his ten friends on his public account on Facebook. At the same time the other person, who has a private profile on Facebook, shares the scooped tweet privately with his two thousand fans. A lot of his friends read the post and visit your site, but probably you can't identify the main source because it was a private post.
At the time of your tweet someone randomly has visited your profile on Twitter and quickly writes a blog article about your project for a website with lots of traffic. He also mentions your website with a backlink and pushes the story in their daily newsletter, which has ten thousand recipients.
At the end of the day you had thousands of new visitors and recognize a huge improvement on the ranking of your website on Google search. With disregards to correlation it's easy to say that a single tweet to ten followers was the causation for this success. Unfortunately it's not that simple because it was the correlation of different parameters that had an impact on the traffic and ranking.
Facebook, Twitter and especially Google+ have an influence on Google's websearch algorithm, but it's tricky to define the impact of social signals on SEO when it comes to causation. Operating in a complex and open system that also contains closed subsystems complicates the evaluation of causation and correlation. Therefore accurate data is needed and interpretations should be taken with care.
What are your impressions of the impact of social signals on search engine rankings?
- 2013 Correlation Study by MOZ
- Rank Correlation 2013 for Google USA by Searchmetrics
- Rank Correlation 2013 for Bing USA by Searchmetrics
- Google’s 200 Ranking Factors by Brian Dean
- Infographic: Google’s 200 Ranking Factors by Entrepreneur and Backlinko
Categories: Social Media - SEO || Author: Christian Prochel