In the realm of digital visibility, ascending the Google Search Engine Results Page (SERP) is akin to conquering Everest. It commences with a quest for relevance, where every keyword is a stepping stone, and every search a pathway leading to the coveted top Google search ranking.
As a company vying for a spot in the digital limelight, understanding Google searches, trends, and the definition of relevant keywords is fundamental. Just as a mountaineer trusts his compass, trust in the power of Google Trends to unveil what's trending, and Google Chrome to explore popular searches.
The climb accentuates as one delves deeper into the mechanics of the search engine. The goal is to rank higher, to see your content amidst the top trending searches, echoing across the local ranking sphere. The ascent is steep, but with every improved ranking, the summit of Google SERP beckons.
The terrain is ever-changing with fluctuating search trends. Yet, with the right blend of popular keywords, a keen eye on trending searches, and a relentless pursuit to improve, the peak is attainable.
Stand atop the digital summit, let your content resonate across the search engine, and watch as your company transcends from a mere name to a top definition on Google. The voyage through the SERPs is challenging, yet with every higher ranking achieved, the view from the top is worth the climb.
How does Google Arrange its SERP Based Upon Content and how can we Optimize this? Search Result Rankings
How does the Google AI work and how can we appease AI and encourage good results? Google AI
Google RankBrain is an artificial intelligence (AI) algorithm that Google uses to process search queries and deliver more accurate search results. It employs machine learning to understand and interpret complex, multi-word queries, and to continually improve its understanding over time. RankBrain is part of Google's broader search algorithm and helps to better understand the intent behind search queries, thus aiding in delivering more relevant search results.
RankBrain uses AI to sort the SERP (Search engine Reults Page) and to better understand what you are actually asking it. It may seem hard to believe but up until AI was integrated into the Google Search algorithm, the whole of Google Search was a set process that ran the same algorithm very time and had to be optimised manually by testing and changing (what we know today as trial and error) and gradually, in steps, they would improve the results pages and rankings as they went. This was obviously an all-day and all-night task carried out by analysts all over the world non-stop. And all of this to ensure that you do not switch search providers and damage their advertising revenue.
Well RankBrain, being run by Google, has what is without doubt, access to the largest data store of search queries anywhere in the world. Google has used this treasure trove of big data to train an AI (RankBrain) the art of association. What this means is that RankBrain was trained with a basic (although it is undoubtedly at least as good as ChatGPT 4.0 by now) understanding of the formation of language and was able to categorise quesries into distinct groups.
So what this means is that Google RankBrain can essentially discern what sort of query you are making. Google categorizes search queries to provide more accurate and relevant results. It may categorize queries based on factors such as the type of information sought (e.g., news, images, videos), the intent behind the query (e.g., informational, transactional), and the topic or industry. By understanding and categorizing queries, Google can tailor the search results to better meet the user's needs and expectations.
On top of this, Google is always perfecting the responses that RankBrain and other Google AI processes deliver by using measurements of customer satisfaction. Google AI gauges user satisfaction through various metrics like Click-Through Rate (CTR), Dwell Time, and Bounce Rate. For instance, if users often click on a particular result and spend a considerable amount of time on that page, it's a positive signal of satisfaction. Conversely, if users quickly return to the search results after clicking a link (a high bounce rate), it could indicate dissatisfaction. Over time, these user behaviors inform Google's algorithms on how to future optimize the relevance and quality of their search results.
Every SEO worker on the web is obsessed with rankings on SERPs across the Google pages and while they are doing this someone else is doing the same. Google, and they do it a million times faster with an army of AI.
Google is always checking which link you click in the list of search results and this is a very important part of the Google processing system. You tell Google how well it is doing and how it can do better - all the time! Before AI came along, Google was checking human behaviour with dwell time, link clicking and purchase histories and recording every result for analysis so that the results could be calculated and relaid back into the system for better search results in future.
Now of course, the AI data interpreters use the big data results to second-guess what links they should be providing at the top of the search results but historically they would often just try several different results until they gave a link to the page that people spent the most time reading. That is why Google sees dwell time (how long before you leave the page) as one of the most important properties of a page. That is why you need to get your message cross in the first few seconds, before they decide to leave!
All of the behaviours that Google use, such as Pogo-Sticking, Bounce amd Dwell time, indicate how the results they send are performing and analysing all of these factors together gives them an astonishingly accurate picture of how they are doing with each SERP for each query.