How is AI powering the Next-Generation of SEO?
Are you still using outdated SEO methods? Well, Google knows exactly which sites are using updated methods and rewarding them generously with Page 1 search ranking, Domain Authority and Trust. In 2018, Google celebrated its 20th birthday. It is quite amazing how a search engine we rely on so much is still incredibly young in the grand scheme of things. Right now, most of us couldn’t imagine life without Google and I’d be surprised if readers of this article don’t use the search engine every day. In 2019, statistics from StatCounter showed that Google have almost a 90% share of the search market.
The reason that Google has become a mainstay in our lives is because it has fundamentally changed the way we search the internet. The philosophy of search is still about information retrieval at its core but the queries we use, the channels we’ve adopted and the devices available have all been through many evolutions. Who wouldn’t thought 10 years ago that you could talk to your phone, have it search Google and then tell you the right answer?
Google have shaped the internet and for marketing teams, this means they have also drastically changed how they carry out one of the core functions of their role in search engine optimisation (SEO). Google are rewriting the SEO landscape all the time, changing the way companies rank and therefore, how marketing teams need to advertise.
The majority of changes we’ve seen have come from Google’s adoption of artificial intelligence (AI) which started in 2016. In that year, Google purchased the AI based company, DeepMind, as well as implementing their RankBrain technology which is founded on machine learning, an application of AI. In this article, we will look at how those AI and machine learning applications work and what they mean for marketers in 2019 as we move towards a new decade.
What is AI?
Before we look at the technology, let’s just remind ourselves what we mean by AI. Generally, AI is any intelligence shown by machines in contrast to natural intelligence that you would see in humans. AI systems will demonstrate some of the behaviours of human intelligence like problem solving, planning, designing and perception. To accomplish this, AI has different applications, one of which is called machine learning.
Machine learning takes existing data to create patterns and predict future actions and decisions. Given the huge amount of information processed by Google every day, there are naturally massive data stores and fantastic potential to generate powerful insights.
Important ways Google have used machine learning
Since the start of 2018, Google have really stepped up their game when it comes to experimenting with AI. Before we start talking about RankBrain and what that means for SEO, here are some of the key things you should know.
- Beyond pure search, Google properties like Maps, Images and YouTube mean that total market share is well over 90%. These properties are just as important for SEO.
- Google updated their algorithms over 3,000 times during 2018. This means marketers have to keep on top of their SEO strategy and stay ahead of the game
- Google now uses neural matching on over 30% of queries. This means they connect words to concepts during searches to provide more accurate results. We won’t go into huge detail in this article, but marketers need to be aware of neural matching.
- It is thought that about 62% of Google traffic is via mobile or tablet search. The way people interact with those devices is very different and needs to be part of SEO strategy. 76% of keyword generate a different search result on mobile vs desktop
- Mobile searches for “where to buy” have grown by 85% in the last two years
- 15% of Google searches are ones that have never been encountered before
The statistics go on but the takeaway here is that the way we search is forever changing and SEO must follow suit for businesses to remain competitive.
Google RankBrain
RankBrain was the foundation of Google’s move into AI during 2016. The function of the machine learning technology was to better understand the entities that people were searching for and to turn those into concepts. This meant that Google would be able to better understand the query and return results that were connected to the initial search.
The algorithms of RankBrain use data to recognise synonyms which instructs other parts of the algorithms to create the appropriate search engine results pages (SERPs). A lot of the evolution of Google in the last two years has been in making RankBrain more efficient. It now takes the content of every search, converts them into what are known as “word vectors” and performs mathematical calculations that have a very accurate guess as to what the user needs.
What does this all mean for SEO?
So, we can see that AI and machine learning have changed how Google operates. Whenever Google release a change to their algorithms, it will undoubtedly have a knock-on effect on SEO. Here are some of the ways that it is influencing what marketers do.
Voice Search
Comscore have said that 50% of all searches will be by voice in 2020. With everybody having access to Alexa, Siri, Google Home, Cortana and others, the trends have changed massively in the last five years. These forms of voice activated AI have changed the way people search. The way we speak is very different to the way we type. Voice searches will have more natural patterns than typed text and are usually more informal.
In terms of SEO, this means you need to adapt content to be more conversational. Traditionally, blog posts written for SEO would have a lot of repeated content to score points in the Google algorithms. As it edges more towards voice, natural full sentences of high quality content, answering audience questions have become pivotal.
Tools such as Yoast and Moz have come to the market to help marketers optimise their keyword formation. They help to formulate sentences, organise content and meet the basics of page structure for SEO. The technology within these tools also reminds users to add images and videos which are just as important for search as text.
Personalisation
We are living in a world where consumers demand personalised products. With so many channels and communications sent each day, the challenge for brands is in standing out from the competition. Whilst we often think about this in terms of the emails we send or in the ads we create, the same applies to SEO. What if two users who search for the same thing could get different results? Digital marketing teams now have massive amounts of data available from websites, blogs, social media and many other channels that their users interact with.
Using this data, brands can tailor what different visitors see on their websites. For example, if you sell sports equipment, customers who love skiing might see different content to those who are fans of football. The machine learning algorithms have the ability to dynamically create the right content for their users.
Many experts see Amazon as a leader in the world of personalisation. Their method takes user data to suggest products based on their history. With that technique, they can bring products that could otherwise be forgotten all the way up to the surface. Linking this back to SEO, the lesson here comes in associating content to different states of intent and capitalising on an opportunity to cross-sell. For example, if a user clicks a specific link on your website, that could be a trigger that they will be interested in a service that they wouldn’t have considered without being prompted.
Content Discovery
For consumers, discovering content is no longer just limited to a search results page as the Amazon example goes to prove. Marketers need to understand that their customers can engage with them anywhere, at any time. Predictive analytics, a segment of machine learning, ties all this together. Using patterns to understand the likely intent of your visitors can help SEO marketers deliver content to meet their demands.
For example, there may be triggers that show if your consumer is not ready to purchase yet so instead you offer them comparison products to try and retain engagement. On-page SEO might provide them with more information about the services.
Some ways that AI can compliment SEO for content discovery are:
- Using semantically specific pages that associate queries and intents
- Use AI to publish content at the right time to the right people.
- Create content based on the stages of your customer journey
Content Marketing
Marketing teams are making use of machine learning tools that can takes masses of online content and extract the core details required for their SEO strategy. A big part of SEO remains in being relevant and topical. For humans to research everything is tantamount to impossible with billions of websites currently online. New AI-based tools are able to take away the manual work and provide relevant content straight to teams in real-time.
A progression of this comes in what we know as natural language generation (NLG). This technology takes the researched content and builds its own headlines and even full content in natural human language. Whilst it is nowhere near perfect at this stage, a model algorithm known as GPT-2 which has been supported by Elon Musk is getting a lot closer. The Huffington Post as well as others are using this type of technology.
In SEO terms, have topical content that is automatically generated in human language is a dream for digital marketing teams. It gives them more time to strategize on other areas of marketing rather than be too concerned about their content.
Top quality content is even more important when it comes to off-page SEO which are the actions taken outside of your own site that impact page rankings. Traditionally, marketing teams would post links to their site in as many places as they could to generate traffic, but that art has virtually become dead. The aim now is to get natural links. These links come from other people who adds links to your site independently without your knowledge.
Machine learning algorithms can automate your social media content with topical posts that are likely to generate natural links from subscribers, followers and ideally influencers. You can quickly analyse emerging trends, understand your consumer voice and be quick to post on subjects that will see you as an expert in your field. AI can genuinely turbo-charge social media presence and off-site SEO.
Insights
AI can deliver business insights capable of supercharging your SEO strategy. This can include market trends, competitor benchmarking, SERP and pay-per-click management amongst others. AI will give teams data insight that they never would have been able to gather with the human eye alone, in a similar way to how we discussed content research earlier in this article.
Outside of Google, Pinterest is using AI and deep learning techniques to understand the context behind images on the website.
Data insights will help SEO marketers better understand elements of the customer journey they need to update, where they need more long-tailed content and where they have opportunities to deliver what the competition are missing.
The future of AI and SEO
While the tech giants like Google are adopting an AI-First approach, the technology is being designed to supplement human roles and remove the monotony of some tasks rather than make them obsolete.
Search engines will continue to evolve and incrementally change their algorithms. As the digital is still growing, consumer tastes are always evolving and search follows suit. The challenge for marketing teams comes in keeping up with the change. You cannot simply write a single blog post with some keywords today. All content must be well thought out within a full strategy that compliments the needs of the business and their customers.
As search engines like Google use more AI, marketers need to build their own AI tools to combat that. The automation available in modern tools means marketing teams have the ability to accelerate their SEO strategies and influence page rankings.