Social Signals – Impact on Google Ranking Algorithms

Unless you’ve been completely absent from any forms of promotion or SEO the last few years then you’ll definitely recognize ‘Social SEO’ or ‘Social Signals’ and all the buzzwords associated with them, but does social live up to the hype in terms of content ranking?

I’ve seen so many marketers and SEO companies pitching why social is the way forward, why it’s right for every type of business and how you’ll be more visible in the search engines than ever before. The problem with these claims via blogs and word of mouth is the lack of data to support any of it, here are some examples:

  • After using social SEO, this website got several hundred more visitors in several months (that could be due to anything)
  • Ranking factors of social  (Insert images containing many charts and tons of numbers which are not supported by any study)
  • Why social signals are the best for ranking (usually just opinions)

Marketers doing what they do best of course, however very few people are putting any time or effort into conducting research into any effects of social signals and are forming opinions from what they have read on forums and blogs.

Social Signal Case Study

I performed some testing a few months ago with the three big social platforms, these being Google+ Facebook and Twitter. These very generalised, non controlled tests suggested that Retweets on Twitter had the biggest impact on search positions for search ranking increases. Maybe the Twitter accounts had a lot of authority, or maybe because Retweets exponentially scale in value, anyway there are too many variables, but Twitter had the biggest impact in the tests by far so Retweets will be used for a controlled study.

Controlled Study (to a degree)

Whilst I would love to create a concrete case study, there are simply far too many variables to explicitly state ‘this happen because of x’ but I can state ‘this most likely happened because of x’. What I’m trying trying to say here if you imitated this test, you would mostly likely not get the exact same results due to the massive amount of variables present. Anyway here are the important parts of the test:

  • Target a keyword, 600k results, 630k in quotes
  • New domain with keywordword in name
  • 5 pages of 450 words articles, unique content
  • All the normal onpage seo stuff, keyword in title, headings etc

A new fresh site; no links, we can assume no search engine knows the site exists which is essential for the case study.

Now comes the fun part, the site will get its URI Retweeted approximately 8000 times within 24 hours.


Start – Website indexed in Google within 3 hours and ranked 293 for chosen keyword.

36 hours –  (Retweets finished 12 hours ago) site is up to 56th for chosen keyword.

3 Days – The the website disappears from Googles index (perhaps a flag trigger) 2 days later the website resurfaces at rank 13!

3 Weeks – The ranking position danced for around 3 weeks before dropping into the triple digital SERP range.

6 Weeks – The approximate 100 SERP is sticking, so I decide to build a few links over 2 weeks to see if this changes anything.

10 Weeks – The SERP slowly rises and has been around the 20 mark ever since. It’s only here than the site receives spiders from Bing & Yahoo, I guess they both honor the nofollow in Twitter?


Overall we can conclude that Retweets get your site indexed in Google, interesting considering everything is nofollow ;). Secondly from observing the results, we can state that Retweets likely have a significant impact on search results temporarily with little benefit as a prolonging effect. Both Yahoo & Bing spiders only found the site once links outside of Twitter were built, it’s unlikely they are using social data in their algorithms yet as I’ve seen the same outcome from Facebook shares. If you have any questions about the case study please feel free to ask.

Ash Grennan

I can cook 1 minute rice in 58 seconds, I enjoy coding and sharing things.