Machine and deep learning have certainly been a common news topic over the past few years, with the implementation of artificial intelligence working its way into various industries all over the world.
The technology itself is groundbreaking and works to better a company and allow it to run in a way like never before. But, while AI can change almost every industry, what about digital marketing and SEO companies?
It is likely the majority have little insight into how AI can alter and change technical SEO, or how it is already doing so.
So, it’s important to question, what does the future of technical SEO look like, as far as AI and machine learning is concerned in 2020?
Why Is Technical SEO Changing?
While the industry is changing due to increased AI development, Google is another culprit encouraging this shift in technical SEO. The search engine is getting better at understanding and reading webpages to help find relevant information for the searcher.
This algorithm from Google is called, ‘RankBrain’ with its first initial release in 2015. The property is machine learning that is dedicated to working alongside the search engine while learning the way in which it works to acknowledge how it can be made smarter to better satisfy the user’s intent.
For technical SEO, the use of AI takes away the need of having to markup data for it to be seen within the SERPs. Now that Google is much smarter, it can reward those placing content into the search engine, with rich snippets, for example, and rank them higher in the SERPs, without having to make its SEO features obvious.
What Does Google Rank Brain Do?
In terms of working alongside the Google search engine, RankBrain makes a guess from a phrase or word a user has entered into their query and will draw up content based on, or similar to, the chosen language.
It filters the results accordingly to how high they should rank against the user’s question. This adapts the way in which search queries and keywords are used.
Both features are handled and distributed into sections commonly known as vectors. Each vector will represent words, or phrases, that can be paired together in terms of linguistic similarities while still relating to the user’s search query.
From here, RankBrain tries to offer the user the best possible search results, based on learning what it thinks the user means and wants from the language and keywords used.
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It is important to make content’s intent obvious, so the machine can always find the correct results, making the user experience satisfactory. If the machine gets the user’s intent wrong, however, it will record was has been offered so far, and make adaptations until successful, turning the process into a lesson for itself.
In the future, RankBrain will ultimately get smarter, working to cut down the time it takes for a user to complete a search query. This will be done by ensuring that search results are enough to satisfy the user and they do not need to wade through pages of information to find the answer they want.
Rank Brain will also change the way in which Google controls the amount of data implemented into its database every day to become more efficient.
Keyword Focused Content
Keywords are used so that Google knows what the content is about when crawling the webpages. Google uses this information to help users find relevant results to their search queries.
Not only do keywords need to be placed within the text but also in the image tags, meta descriptions and titles.
It is important that keyword placement looks natural otherwise Google will pick this up as being against their webmaster rules. Further, by having keywords placed multiple times throughout a piece of content, it could appear spammy. This alone could turn a user away and make them find a new source of information.
But, with the aid of machine learning, Google can scan the SERPs for sites that are relevant to the keyword within the user’s query. Those pages where the keyword is implemented not only strategically, but naturally, are more likely to be offered to the user first over spammy sites that overuse keywords.
The Updates Of Google Ranking
SERPs are fluctuating constantly due to the increased competition, content creation and algorithms. Because of this, a website needs to be updated regularly, to ensure that Google continues to trust your site as being the most relevant result for your particular keywords. There is no room for stagnant content when looking to stay at the top of SERPs.
From improving visual aesthetic to being continuous with trends and content, each change or addition to the website and the content within it will show Google that the site is active. This means that it will be crawled more often than the sites which haven’t been updated in months or even years.
Quality Of Content
Alongside the much-loved links, content is one of the main focal points of SEO. Search engines scan over content to find those that are the most trustworthy and give each domain an authority level to show how trusting they can be to those making the queries.
Realistically, the higher-quality links a site has used within or has pointed towards it, the higher it is going to rank, and the better the return on investment received.
Right now, the way in which search engines such as Google work to evaluate the quality of content is working, but it could be made better. In the future, it should be seen that the process will be updated to include the use of machine learning, making more efforts to automate the way in which content is ranked in Google search.
The search engine individualisation processes currently in place are nothing far from impressive, with users everyday driving their own minds crazy for seeing an advert on something they just looked at on Google pop up on a new webpage. These efforts are there to draw in the user, act as a persuasion method and hopefully, cause them to make a purchase after reacting to this ad they keep seeing.
With the inclusion of machine learning, the search engines will likely be capable of making the user experience even more personalised, making much deeper predictions, rather than simply knowing where we are, or what we’ve previously searched for.
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It is likely that Google will be able to offer users a search query before they even know they need it, turning the search engine experience into that run by machine learning completely.
Not only is individualisation embedded within the search engine pop-ups or ads that seem to follow us around, but it can also benefit when implemented into content too.
Individualisation has quickly become an integral part of SEO processes, with consumers demanding it as a standard feature. Those who do not implement individualisation into their site will see a drastic drop in rankings.
Through AI influence, website deals, trending products and site pop-ups can be personalised, leading to companies layering concrete over existing connections and bring in new customers.
Industry Adaptability To Algorithm Changes
Google is becoming rather well-known for its regular, major algorithm changes being released as little as every few months. These changes are made to better the way in which Google can analyse data and the amount of which it can do so, to ensure it is always better than that of a human team.
These changes, while months apart as of now, are likely only going to become more regular, and an industry that works solely on search engines, such as technical SEO, needs to ensure they can comply with these continual changes and stay up to date, so work is never delayed.
The advancement is working towards real-time analytics in which the machine will always learn, and change as fast as every day. This can make it difficult. Without the help of machine learning within SEO, the industry may not be able to keep up.
Will Technical SEO Uphold Against Machine Learning?
SEO is rapidly changing, and through the advancements of machine and deep learning, it is certain to change even further with the collaboration.
It’s all about delivering the best user experience, and getting the most out of content, links and traffic volumes to rank as highly as possible within the search engines. Because of this, the industry will have to comply with the demand of the machine learning process that is likely going to arise in 2020, to better themselves, and ensure every search engine user is completely satisfied at the end of their journey.
With these changes happening so regularly, it should not be hard for the SEO industry to adapt to these technological changes. If anything, they will work to better the results produced for the clients.
But over time, there is a chance technical SEO will not be as important as it currently is, with it requiring a less substantial amount of human interaction by being able to run entirely with machine learning technology.
Google Search Console already has the potential to grow in a way that will allow it to send out its issues, but fix them independently too, after learning the various patterns taken to be fixed by a human. From this point, not much is left for that of a human technical SEO expert to take on except hope that the machine learning aids the industry, turning Google search into the best-experienced engine available, increasing its daily users even further.
Machine Learning is changing the world by transforming all segments including healthcare services units, Education, Transport, Food, Entertainment and different businesses like assembly line and many more.
Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”. And, Machine Learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves.
AI marketing is a method of leveraging technology to improve the customer journey. It can also be used to boost the return on investment (ROI) of marketing campaigns. This is accomplished by using big data analytics, machine learning, and other processes to gain insight into your target audience.