Google has on many occasions downplayed the importance of social interactions as far as their ranking signals are concerned. But there are still many reasons to believe that soon or later Google may increasingly take social signals into account. One of the strongest indications has to be their recent patent US 2016/02466789 A1, which goes by the title “Searching Content of Prominent Users in Social Media”. A patent doesn’t of course mean the technology will definitely be implemented, but it does provide the necessary clues we need to know what would be considered if the implementation is ever done. So even if Gary Illyes and other folks at Google say they don’t use social signals for ranking, don’t think they totally don’t or aren’t considering doing that.
With the new patent that Google has been granted, we clearly see the possibilities as far as taking into account social as a ranking signal is concerned. The patent covers the methods, systems and apparatus that Google may use to do so. If they eventually decide to use the technology behind it all, it means searchers will be more likely to see results based on what their prominent social connections often recommend. If such prominent social users recommend certain resources, they may start to determine rankings. But it depends on which resources they reference in social sites and whether searchers are attracted to them or not. If a searcher ignores any recommended resources, Google may devalue such resources and therefore they may not impact on rankings.
At this point it may not be easy to fully understand how social signals will work. But when a search is being done, the prominent social users connected to the person doing the search are those whose followers meet a certain threshold. From the Google patent content, user social graphs will be used. Each social graph may include direct connections or even higher degree connections. So this may not just be limited to single social networks but also multiple social networks. The focus will also not be limited to traditional social sites but also pretty much anything social including chat, email, blog posts, reviews and so on.
Frequency of social interactions will also count in determining the degree of separation in the social graph, and how it will be used to augment search results. Google will not only look at what a searcher’s social graph members are sharing or engaging with, but also any content they may have created themselves. For instance, a searcher’s social connections may have created written or video reviews of restaurants or other services and products. If such social users and their reviews are taken into account when returning results for search queries, a searcher is likely to find the search results more useful.
Considering that there are many other ranking signals used, we cannot always expect conclusive answers from anyone in Google regarding what exactly happens with each ranking factor. That’s why they could tell you social signals don’t count, when they actually mean it isn’t a direct ranking signal yet. Remember RankBrain is the third most important ranking factor after links and content. Since RankBrain functions based on artificial intelligence (AI) and machine learning capabilities, it’s easy to see why at some point not even Google engineers will be able to say the exact contributions of different ranking signals. At least as far as query interpretations and similar aspects of Google search rankings are concerned. The engineers will still know more than we do, but they will certainly not know everything because RankBrain teaches itself without using detailed programming inputs from humans.
Since Google has been granted a patent that allows us to get an idea of what they might be doing, it helps to refine our SEO strategies without dismissing the idea of social signal impacting on rankings. We have to create great content that friends of our prospective clients can engage with as well. It is easy to see why establishing a strong social media presence is necessary.
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