How machine learning levels the SERP playing field

We don’t ordinarily think of Google when we think about competition in the digital marketing world, since it seems to reliably dominate most areas in which it does business. A recent segment discussing corporate monopolies on John Oliver’s “Last Week Tonight“ hilariously referenced Bing as the dominant search engine with a graphic that stated, “Bing. The best place to Google something.”
For the most part, however, the digital marketing sphere has been a fairly competitive landscape, though there were exceptions to this maxim. Established brands frequently dominated top SERP positions because of long-standing trust, fresh domains had to wait their turn in line, and black-hat SEO allowed webmasters to game the system and deliver high rankings for thin content. A decade ago, SEO agencies and webmasters could apply simple heuristics and buzzworthy keywords to rank content regardless of its utility to user intent or actual quality.
The Hummingbird update and subsequent rollout of RankBrain changed all of these notions

Search Engine Land Source

What I learned from the Danny Sullivan/Gary Illyes keynote at SMX Advanced

On June 13, 2017, in Seattle, Search Engine Land’s Danny Sullivan sat down with Google’s Gary Illyes to talk about all things Google. You can read live blog coverage from the session here. In this post, I’ve organized the content of this session into topical groups and added my own analysis.
Note: The questions and answers appearing herein are not direct quotes. I am paraphrasing Sullivan’s questions and Illyes’ answers, as well as providing my interpretation of what was said (and including additional context where appropriate). I’ve also omitted some content from the session.
The featured snippet discussion
Danny Sullivan asked: Are we going to keep getting more featured snippets?
Illyes has no idea about that, but he notes that featured snippets are very important to Google. They want the quality to be really high, and one consideration people don’t normally think about is that, in some cases (e.g., voice search results), the answers may be read out loud.
This example is one of my

Search Engine Land Source

How Google uses machine learning in its search algorithms

One of the biggest buzzwords around Google and the overall technology market is machine learning. Google uses it with RankBrain for search and in other ways. We asked Gary Illyes from Google in part two of our interview how Google uses machine learning with search.
Illyes said that Google uses it mostly for “coming up with new signals and signal aggregations.” So they may look at two or more different existing non-machine-learning signals and see if adding machine learning to the aggregation of them can help improve search rankings and quality.
He also said, “RankBrain, where … which re-ranks based on based on historical signals,” is another way they use machine learning, and later explained how RankBrain works and that Penguin doesn’t really use machine learning.
Here is the audio file:

Here is the full transcript:
Danny Sullivan: These days it seems like it’s really cool for people to just say machine learning is being used in everything.
Gary Illyes: And then people

Search Engine Land Source

Google uses RankBrain for every search, impacts rankings of “lots” of them

Google is now using its RankBrain machine learning system to process every query that the search engine handles, and the system is changing the rankings of lots of queries.
The news emerged this week as part of Steven Levy’s Backchannel story about machine learning efforts at Google. From the story, in regards to RankBrain:
Google is characteristically fuzzy on exactly how it improves search (something to do with the long tail? Better interpretation of ambiguous requests?) but Dean says that RankBrain is “involved in every query,” and affects the actual rankings “probably not in every query but in a lot of queries.”
What’s more, it’s hugely effective. Of the hundreds of “signals” Google search uses when it calculates its rankings (a signal might be the user’s geographical location, or whether the headline on a page matches the text in the query), RankBrain is now rated as the third most useful.
We’ve already heard before that RankBrain is considered the most useful search

Search Engine Land Source