Understanding how Google Works for SEO

Mark writes in,

"I am really struggling with the efficacy of search for most businesses. More than ever, the odds are stacked against us.

1) Some search is leaking out through Siri + Alexa
2) Most Google search (51%) is now "kept" by Google
3) You're irrelevant unless you are in the top 1-3 slots. That is simply not accessible for most businesses.

For argument's sake, let's look at the hundreds of thousands of digital marketing freelancers out there. How many of them can rank in at least one term (or afford one) that can bring them meaningful business? While search, and your advice, is the heart of our profession I have a sinking feeling it becoming less relevant day by day."

The idea that search is a monolithic entity where either you rank or don't rank is only true for large enterprises challenging at the broadest levels. One of the wonderful things about machine learning and AI powering most search is that it's now more granular and more context-driven than ever before.

Searching for "coffee shop" on your desktop will give you different results than searching for the same phrase on your mobile device. Google in particular, but other search engines as well, understand that intent is different based on device. So, device type is one segmentation of several hundred applied to searches.

Another example of how Google automatically creates niches is based on the intent type. "Coffee shop" and "coffee shop near me" are very different intents, even though they're not semantically all that different. The latter is a location-based search.

Google has hundreds, if not thousands, of niches where any company can do well in search, even competing on broad terms, if the company and the searcher are both in the same niche. You don't have to rank in every niche, in every audience. You just have to rank well in the niches that matter to your business.

So in Mark's example, it's a fool's errand to rank for "digital marketing expert" or the like. But "digital marketing expert in San Diego real estate"? Or "digital marketing expert in SMB coffee shops"? That's the place where you want to focus your efforts - context-rich searches.

Mark is right in that Google keeps - and continues to grow - the overall share of search with new features like Passages. However, the absolute volume of search is also skyrocketing, so the volume of search a website earns is still increasing, as long as the SEO practitioner is keeping up with the times.

The Real SEO Problem Marketers Face

Therein lies the real challenge: keeping up with the times. Many marketers have incredibly outdated perspectives on SEO, ideas and concepts created years ago. Search engines have evolved incredibly just in the last two years - five year old SEO knowledge may as well be knowledge fished up with the Dead Sea scrolls. Moreover, using knowledge that's outdated is not only ineffective, it may be actually harmful to your website.

For example, two years ago, Google released a detailed paper on a new algorithm it deployed as part of search, called Deep Relevance Matching Models. This paper, which was later confirmed by Danny Sullivan as being applied to up to 30% of Google query results, is a huge game-changer for how we think about optimizing our content:

Deep Relvance Matching Models

What made this revelation a game-changer is how Google sees our sites. For years, search practitioners have been locked in the idea of keywords, keywords, keywords. Over the years, Google's AI capabilities have increased its scope of understanding from the word to the phrase to the paragraph to the document - and that's what DRMM understands and informs, queries and results at the document level. Your whole page as a coherent work matters, not just a single phrase.

The funny thing is, Google telegraphs a lot of this information very publicly. They make their research papers publicly available and free to read. They talk about their architecture and systems on blogs, YouTube channels, social media, and podcasts - and even provide helpful transcripts. They tell us the training data they use to build their models, the Search Quality Rating Guidelines. They lay out the buffet and invite us to dine at it with them.

And what do many marketers do? They stand at the massive, free buffet and eat only the croutons, because the buffet looks intimidating - and instead of rolling up our sleeves and teaching ourselves how AI and machine learning, we shy away and criticize Google instead, or bluff and pretend we know what we're talking about. Neither is a good strategy when you're competing with an AI.

Search is more relevant and more powerful than ever if you know what you're doing, if you know how the systems work and how to work with them, not against them.

So, that's the challenge facing many marketers. Take the time to skill up your knowledge of how Google works today, not the historical snapshot trapped in many people's minds, or hire an agency that knows what it's doing.

An easy way to screen SEO professionals and agencies is to ask them to explain two or three of Google's neural network-based models and how they impact search, like DRMM, BERT, and TF-Ranking. If, in a casual conversation, they express absolutely no idea what any of these things are, you're dealing with someone whose knowledge is out of date.

Ask them to explain how Google indexes content from a mechanical perspective. Google has outlined this process in detail - and given tactical advice for how to adapt your SEO practices. If the answer seems like a bunch of nonsense instead of details about Google's Chrome server farm, you've got someone with out of date knowledge.

Where to Learn More

Finally, keep in mind this one maxim: Google is optimizing for the human at the end of the search query. It's not optimizing for us, the marketer. We have to optimize to the same objective - and you don't need a billion dollars of technology at the end of it. You need to understand the human. Trust Insights has a new paper out today, in collaboration with our partner Talkwalker, on informing modern SEO with social media data. Give it a read; it'll show you how to take practical steps towards optimizing for humans and give you more depth on a lot of the AI talk in this post.


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