Do social networks affect SEO? We conducted an experiment to find out
Can social media help with SEO?
Glossary of SEO terms
SERP: search engine results page
Search ranking: the position of a URL in a SERP for a specific keyword
Search visibility - A metric used to calculate the visibility of a website or page in a SERP. If the number is 100%, for example, it means that the URL is ranked first for a keyword. Search visibility is especially important when tracking a site's aggregate ranking for a keyword basket.
Domain or page authority: the strength of a website or page on a specific topic in the eyes of search engines. For example, the Hootsuite blog is perceived by search engines as an authority on social media marketing. This means that we have a better chance of ranking keywords related to social media than a cooking blog like Smitten Kitchen.
Do social networks help SEO?
The question of whether social media has an impact on SEO has been debated for a long time. Four years later, that stance changed after Twitter temporarily blocked Google's access to its social network. In 2014, former Google web spam chief Matt Cutts released a video explaining how Google cannot rely on signals that may not exist tomorrow.
That's when the conversation stopped. Since 2014, Google has publicly denied that social media has a direct effect on rankings.
But now it's 2018 past four years. A notable change is that social media has started to appear on search engines on a much larger scale.
Facebook URLs are among the top 100 on Google.com (USA)
Do you see the exponential growth of Facebook and Twitter pages reaching Google results? Well, we did and we thought it was time to analyze the relationship between SEO and social media with a series of tests.
Say hello to the "Elephant Project", an experiment in honor of the "elephant in the room". The elephant, in this case, is the long-standing question, but never answered: can social media help improve the ranking of searches?
How we structure our experiment
Representatives from Hootsuite's inbound marketing, data analytics and social marketing teams came together to develop a reliable and controlled testing approach.
We organize our content (blog articles, for the purposes of this experiment) into three groups:
The control group: 30 articles that did not receive organic posts or paid promotions on social media (or anywhere else)
Group A (organic only): 30 articles published organically on Twitter
Group B (paid promotion): 30 articles published organically on Twitter, then conducted for two days with a budget of US $ 100 each
To simplify the number of data points, we chose to run this first test on Twitter and developed a posting schedule to keep up to date.
But before starting the test, we needed to level the playing field. This allowed us to establish a baseline for their search rankings.
After this stage, we promoted two posts per day from Group A and Group B over a period of two weeks and measured the results the following week. From start to finish, the entire experiment took approximately a month to run.
Methodology
To ensure coverage of all of our databases, we record the following data points:
What keywords we were tracking
What URLs (blog articles) were we crawling
The monthly search volume for each keyword.
The Google search ranking of each item before the test starts
The Google search ranking for each item 48 hours after the test starts
Google search ranking for each item one week after starting the test
The number of links that point to each item before the test starts (backlinks are the number one ranking engine in the survey)
