What is the intent of a user when they enter a search term? Rather, what are the multiple layers of intent that Google sees in that query? What has Google determined to be important when showing results for a given keyword? Google has gotten far better at parsing search terms according to the multiple intents embedded within them.
But how are you supposed to determine how Google understands intent for a search term? How do you know what content Google thinks is relevant to users? How can you determine how Google understands intent?
Here's a simple method that's worked for me.
What a year in the world of SEO. Sure, I say that every year, but 2018 certainly had its share of game-changing developments. Predisposed to a high volume of SEO themes, be it mobile-first or Google's new "journey" outlook on search, 2018 has a flavor all unto itself.
Now then, there are just way too many stories for me to cover in one post to catch everything that we saw hit the floor in SEO during 2018. What's to come is my best crack at grabbing all of the major stories, the biggest changes, and the most interesting advancements that came out of the world of search in 2018.
Here we go!
As time has gone on, how we measure effective Google rankings has evolved. We're at one of those moments in time (again) where the ranking paradigm is changing/has changed. As you'll see, ranking above the fold is more important than ever. It's why we created a tool as part of our Beta Blitz SEO reporting initiative that tells you just that: Are you ranking above the fold or can no one see your site despite it ranking so well?
So then, why is ranking above the fold so important and how do you get there? The experts weigh in.
Keyword cannibalization is one of those SEO buzzwords that carries with it a certain myth and mythology. But behind the commonly held ethos of how keyword cannibalization is perceived lies a real problem that could impact your site and more importantly your bottom line. If you're wondering what keyword cannibalization is, what it's not, why it's a problem, and what you can do about it, then this post was written for you. If not, give it a read anyway, what do you have to lose?
Back in 2016, AMP, Google's open source project to make a speedier
, was all the rage. AMP was going to be the next big thing. Fast forward three or so years into the future and AMP, while still significant, is not the dominant force we thought it would be. AMP seems to have lost a bit of steam. Though still very much a part of the search marketing dialogue, AMP has faced some pretty significant obstacles that have downgraded its "SEO prestige."
Here's why I think AMP has hit a wall.
Google took its 20th anniversary as an opportunity to hang a pinata of search updates that have already begun to rain down on us. From "topic layers" in what is an all but transcendental Knowledge Panel, to Google pulling site content to create its own version of AMP Stories, the updates announced at Google's 20th birthday bash event are set to change the way users interact with search.
Here's what I think the common denominator between the changes is, what it means for search, and what you might want to do about it!
Dealing with feature heavy SERPs is a big problem for a lot of folks. I went around and asked some pretty smart people what they thought the best way is to handle ranking amidst Google's SERP features. The idea was to combine the different pieces of the puzzle into one resource.
To be blunt, this is not another roundup so that a bunch of people can walk away with links where nobody really says much of anything. These are the best thoughts these fantastic folks have on how to deal with a SERP where Google is a formidable competitor.
In the not too distant past, I wrote a piece highlighting how machine learning has impacted rank volatility (in that rank is considerably more volatile). At the time, we touched on what machine learning means for understanding how ranking works and how the process directly influences rank. Here, we'll get into the nitty-gritty of it all by analyzing the holy of holies of optimization information, ranking factor studies, particularly niche ranking studies by asking one very simple question
.... Do ranking factors studies still apply in a world where machine learning and intent reign supreme, and if so, to what extent?
Learn how machine learning changes the rules of the game for ranking on page one of the Google SERP. As Google becomes better at understanding intent, Google's machine learning properties have a greater impact on ranking itself and how we go about the optimization process. Get insight on how to identify the way Google sees user intent. At the same time, you'll better understand the role of niche ranking factor studies, and how to go beyond them with query specific analysis.
Organic is old news. If I would have said something like that five years ago, you might be looking at me all cross-eyed. However, in today's SEO world, one in which SERP features dominate, such a statement actually contains an air of viability. I mean, for crying out loud, Google has tested zero organic
result SERPs. Why? Why does it feel as if Google is increasingly giving more weight to its own SERP properties? Why would Google even test a SERP with no results?
I have a theory.
How will the tech giants handle privacy concerns? Who poses the biggest threat to Google’s empire? Which social media platforms are too saturated? Get an expert understanding of the ever-changing digital marketing landscape in this interview with Blue Thread Marketing co-founder Mordecai Holtz.
After extensive testing, Google's 'More results' button officially does away with mobile pagination. With the new mobile format users can quickly load the equivalent of another page of search results with just one click and without
wait, but what are the consequences? Who benefits from this considerable change to the mobile SERP? Who loses out? What are the implications?