Table of Content
1. Usage Data of Pages and Sites
It is no secret that Google has been collecting data on how people use and interact with its search engine. It tracks before, during and even after you make the search query. By understanding people’s interactions and engagements with the search results, Google will be able to return search results that are more relevant and useful.
For example, if a higher ranked website has only 500 visits per day, with less engagement from the visitors, while a slightly lower ranked site has more visitors and higher engagement from visitors, then Google might just start ranking the second website higher because Google wants to send searchers to the page with greater visitor loyalty and engagement.
According to the Ranking-Factors 2014 published by Searchmetrics, click through rate showed a 0.67 correlation. Thus, it’s not surprise that Google is going to utilize more usage and engagement data to rank websites in the near future.
2. Brands as Entities and Associated keywords
Google has rolled out knowledge graph for a while now. More and more brands are becoming entries in Google’s knowledge graph. Check out the following video if you are not familiar with the knowledge graph.
Having a knowledge graph for your brand provides a distinctive advantage over your competitors because of the large real estate on the search result page. In the near future, Google is also going to integrate more and more of knowledge graph information into the Android Google Now app. As you can see, Google is slowly moving away from keyword based search, instead it is going to rely on knowledge graph that it has built over the years in order to provide more relevant and engagement information for searchers.
The best way to get your information onto the knowledge graph is to implement structure data and schema markup. Below is an example on how to get your event information onto the knowledge graph.
The brand dropdown menu on the wikihow.com suggests an implicit bias toward accumulating brand associations and showing it off to searchers. There is also a correlation between brand dropdowns and higher ranking.
Another example below shows that if you type in “seattle real estate market”, Google automatically shows Zillow (brand) as a result. These keywords have been so tightly associated with the brand that Google can predict what people are actually looking for.
Not convinced? Check out another example here. If you search for toys, Google will automatically show not only Toyrus as a suggestion, but also the link to the website. This means Google thinks if you are looking for toys, you can find it on toyrus.com. It also means visitors will skip the result page, and go directly to the brand website. Interesting, Google is willing to sacrifice its Ad revenue in order to collect more data from users and provide a better user experience to searchers.
So what’s the best way to rank in 2016, 2018, or 2020? It’s find a way to be the best or first in the category of your product/service.
3. User experience as ranking signal
Ever since Panda, Google has been trying to surface not just quality content, but “high quality websites” as well. This means Google is increasingly giving more credit to websites that provide better user experience. Just in the past year, Google has declared both HTTPS (security) and Mobile-friendly as ranking signals.
According to eMarketer, mobile searches will surpass desktop searches in 2016. In addition to making your website responsive or mobile friendly, you need to go further, deliver a true mobile experience. This means you need to have a mobile mindset when designing websites and product offerings.
With a truly “mobile first” mindset, marketers will be able to easily capture mobile consumers. For example, things like creating simpler, more focused product pages, keeping only features that are useful to mobile users, and creating mobile only deals and promotions are important on mobile as well.
4. Google Will Use Deep Machine Learning to Rank Websites
There is an article over on Medium called “Google Search Will Be Your Next Brain,” by Steve Levy. The article is a bit lengthy and complicate. But it basically says that they will try to get machines to generate outcomes/results on their own instead of us feeding algorithm or inputs into computers for them to consider. Deep machine learning will be able to predict and forecast and basically think on its own.
Many tech companies have already used some aspects of machine learning in their products. For example, Facebook’s facial recognition uses machine learning to figure out things like who is in the picture and where the picture is taken place..etc. Both Amazon and Netflix have been using machine learning for their recommendation engines.
But what does this mean for SEOs. This implies that SEO in the future is going to mean much less distinct universal ranking inputs, or ranking factors. Maybe even Google Engineers won’t know what certain websites rank higher over other websites.