The world evolves fast, and the digital landscape is right at the cutting edge of that evolution. Artificial intelligence has begun a foray into the search engine world and is changing the dynamics of the environment. In this article, we will take a look at how things have changed over recent years so that you can understand what you should be doing to develop your website in the current search landscape. 

The evolution of search engines

Let's start with a little bit of context and history so that we can see how marked the shift is in the way that Google and other search engines are beginning to operate.

When Google first started, it was enough to put keywords in the titles of your articles and pages and incorporate them into meta-tags and into your page. That enabled Google to label your website as about a certain topic. When people searched for things online, they used keywords, and if Google found those keywords within the various elements of your webpage, they presented it to the users as relevant. In addition, Google counted up the number of links that were pointing towards a website to get an idea of how reliable that website was.

As can be the way of the world, people manipulated search results by building artificial links and cramming as many keywords as possible into web pages.

Over the years Google has brought in various algorithm changes in order to try and provide the best, most reliable search results that they can. That has meant penalizing sites that have links from spammy networks, penalizing sites that are full of adverts, and downranking websites with thin content with little value. So how does Google now look at content and websites as a whole?

A learning search engine

Google is at the cutting edge of search engines. The digital giant accounts for around 90% of search traffic and it's where everyone wants to be. Google now does a much better job of understanding what a page is about. Where pronouns and the various aspects of language used to be ignored, Google now uses them to understand the context of the language on websites and in search queries.

Google assesses entities and looks at what makes up the web in order to comprehend topics. According to the B2B Inbound Marketing Agency JumpFactor The new natural language processing algorithm is able to tell the difference between apple the fruit, and apple computer with very little information. The new algorithm knows that if you are searching for “is my wife cheating?", it's appropriate to provide different search results depending on exactly what it is the user is asking.

In the example above the user could be asking casually what are the kinds of signs that would show that my wife is being unfaithful. The search query may equally mean show me a local private detective to find out definitively if my wife is straying. There could also be other meanings behind the search intent for that search query, so Google has a very complex job of understanding what information to present.

Google is using the massive amount of data at its disposal to hone the results to better match search intent. The amounts of information that Google has through Google analytics is phenomenal. Most websites now have Google analytics installed. There are components of the algorithm that look at website bounce rates, the number of pages visited the duration of visits and so forth. Google develops a picture of what good performing websites look like, and can then incorporate the elements that make up those websites as ranking factors. Google also has human raters that feed into the algorithm by providing general data on what is good and what is not. The algorithm has become a learning machine that can now pretty much understand language, just as you and I.

The future and what it means to your website

What you have to do with your website now is produce content that matches the search query intent is grammatically excellent and provides visitors with a path towards more solutions. It's not enough these days just to write decent content, you need to understand the language of your topic so that the page is clearly relevant.

For example, search optimization is made up of a number of different concepts. To understand what the topic really is requires that you understand all of the languages that make up the topic, and one way to do that is to assess what Google is currently ranking in the top 200 search results and look at co-occurring citations, language counts and the various meaning that is incorporated in the whole body of data.

When you have this information, you may find out that search engine optimization is about search engines and optimization. You, therefore, have two core aspects to the one term. There will be language around improving search results, and language around search engines. There will be the language that is common to the topic such as bounce rates, visitors, user experience, and there will be a language that is about one or the other subtopic.

For example, search engines have massive data service, work through browsers, and include MSN, Yahoo, Alta Vista, and Google. Optimization is about improving efficiency, analysis, and output graph line, and so on. You need to work out what the language is so that you can incorporate into your content and into your supporting pages.

Search engine optimization in the current digital landscape has become both harder and easier. If you are willing to do the data analysis then you can produce the content that stands out. Anyone was able to stuff keywords into a page and put together 500 words of copy.

It's harder to produce great quality copy that provides solutions and has the right language within it to fire the relevance and quality signals in the Google algorithm. It's a time when you need to be thinking about your website visitor experience and becoming a data analyst alongside being a quality copywriter.