|SEO||– 43 min read|
How Artificial Intelligence Changes SEO: Asking Experts
In general, AI has fundamentally changed the approach to search engine optimization. In this article, we will discuss using it for our purposes and learn the opinion of experts on the topic of AI.
1.1 Why do you need machine learning
1.2 How artificial intelligence is used in search engine algorithms
2. Artificial Intelligence and SEO: expert opinion
2.1 How can Artificial Intelligence be used in SEO?
2.2 Do you use AI in your work? How?
2.3 What AI-powered SEO tools do you know?
2.4 How did the BERT algorithm affect search results?
2.5 What is your advice on optimizing your site considering AI in search engine algorithms?
Our today's contributors:
What is artificial intelligence
Artificial intelligence technologies are divided into categories regarding their ability to imitate human abilities. Using these characteristics, all artificial intelligence systems, both existing and hypothetical, are divided into 3 types:
Why do you need machine learning
How the machine works is a specific algorithm. Let's analyze the concept:
We encounter a problem → analyze it → identify the rules → translate these rules into program code that allows you to automate the solution of the problem in the given conditions.
However, in some instances, the classic approach to automation fails. There are many problems in which we can't identify and write down the rules: for example, image recognition, human speech, processing and checking the quality of texts, or identifying complex patterns in data.
We are faced with a fundamental limitation of the solution to the problem when we cannot identify explicit rules that the algorithm should follow. And we need a new approach to automation, different from the classical one. This is where artificial intelligence comes.
AI bypasses the error of the classical approach. This allows the system to identify patterns and learn implicit rules (usually by analyzing thousands of examples) to analyze data (images, sound files, texts, etc.) according to specific schemes (as was the case with the cat).
How artificial intelligence is used in search engine algorithms
Achievements of machine learning contribute to the development of artificial intelligence. The development of this area has been ongoing since 2003, but the first significant achievement was the Word2vec program.
Artificial Intelligence and SEO: expert opinion
How can Artificial Intelligence be used in SEO?
Another example is content writing. Writing first drafts is often the hardest part of article creation.
So if we could input data and links to a program, and then it spits the draft we can then make shine, that'd be a huge time saver.
Another interesting product is Google's "Discover". The product is developing into a good traffic supplier. AI optimizes the users news feeds on their smartphones by showing relevant news.
When you got the basics right, then you can have a look how and if topics like AI can add the remaining percentages to your website.
The use-cases of AI in SEO, unfortunately, have been very limited. So far AI has been more of a buzzword in our industry rather than real-world use cases for all businesses. However, this doesn't have to be the case, we can see more and more SEOs turning to ML and Python to better analyze, research, and understand big data.
AI can be a huge asset for SEOs and businesses, from finding keyword opportunities, automating competitive research , to better understanding your customers' journey, and creating relevant quality content that supports that journey.
The underlying result of trying to optimizise for AI is that, as webmasters, we're trying to increase the number of topics and phrases covered within our content, and create more logical site structures that flow between said topics. Whether or not this is done under the guise of AI optimization (which John Mueller has been on record saying it can't directly be optimized for) or through a wild spate of "LSI keyword optimization" (again, not a thing), the end result will only benefit users.
The difference between those rewarded in organic search vs. those who don't, comes down to those working with the theory vs. those trying to game it.
Other ways AI is being used that fascinates me is through keyword research and schema markup. For instance, every month we hear about new tools that can cluster topics better, build a more conclusive keyword list, and give SEOs better data in general to do their job.
- Cut down and cluster an avalanche of operational signals to look for anomalies;
- Forecast time series more accurately;
- Detect user intent and find subsequent opportunities via clustering;
- Auto-generate content at scale;
- Auto-label your keywords, URLs etc.
Do you use AI in your work? How?
We generally populate spreadsheets with the automated work and have a member of our team or client review and make any adjustments. For example, a common problem is mapping a large number of URLs between sites during a platform change. I explained how we use AI to do that.
We have someone manually review the mappings and make corrections. The AI still saves us more than 70% of the work.
So I gave up on the idea as it's more work to rewrite what the machine gave me, than to write it myself.
Buzzsumo is very suitable for finding topics that are currently performing well.
It helps us to find out which topics are hot in our industry.
We also use some grammar and content tools within the wider content optimization process, based on the theory that if the tool is working with data sets to make suggestions to improve content quality, it's good to have as a second phase to our own internal processes.
This still requires a form of human checking however, as AI isn't yet a substitute for logic.
Natural Language Processing (NLP) is the process by which search engines use AI attempt to understand what a person wants when they type a phrase into Google and hit enter. SEO tools with semantic analysis capability reveal topics that make up the latent intent behind a search term. Search engines themselves use a similar process to understand content crawlers have discovered on a web page so they can assign appropriate search terms that can then be ranked.
So by using SEO tools with NLP functionality, I can effectively reverse engineer the process by which search engines break up content into constituent topics so I can then assign to the search terms I want to target.
I also try to optimise our sites regularly with the most up-to-date schema markup to ensure search engines get the important information to helps us put our best foot forward in search.
Currently, I use ML for regression problems, forecasting and text classification. As a server log aficionado, I'm also experimenting with ML for anomaly detection.
It's only recently that I've integrated Machine learning in my daily workflow. Needless to say I'm only scratching the surface of it - there is so much to learn and for me that is super exciting! :)
What AI-powered SEO tools do you know?
It should be on every SEO tool by now. The core technology is both free and open.
And, while they're not SEO tools per-se, I'm fascinated by "Automated" ML solutions (Google AutoML, H20.ai, Uber's Ludwig, Spacy.IO etc.). It's great to see how these tools are democratising ML in the organisation, allowing anyone to build quality custom models with limited coding expertise. Sometimes, removing the hassle of tasks you'd otherwise need to perform manually (hear hear hyperparameter tuning!) can be a godsend!
Last but not least, I've recently fallen in love with Streamlit. I think it is a game changer for web applications, even outside of ML!
Leave a request, and our experts will advise you on the development of your project, share training materials, and offer test access to Serpstat!
How did the BERT algorithm affect search results?
Bottom line, BERT made it easier for weaker and smaller sites to beat the giants in their verticals. If their content is better and more relevant they have a good chance of ranking highly.
BERT has helped Google better understand the nuances and the context of conversational queries. Allowing the search engine to serve more relevant content, recognize entities, and make SERPs more interactive.
By being able ot better understand these words, as well as the surrounding context (other words on the page, other content on the domain), Google can work to serve better results in niche queries, and potentially also use Chrome data for SERP personalization to use context to better serve results for ambiguous queries.
If you wish to really understand how BERT works under the hood, get comfy and read this gem from Dawn Anderson. Dawn discusses the backstory and nuances of BERT's evolution, how the algorithm works to improve human language understanding for machines + what it means for SEOs. Time well spent!
What is your advice on optimizing your site considering AI in search engine algorithms?
So use AI for what it's worth but never forget that it'll probably never be able to beat human login, intuition, and common sense. So going forward, it's content; and it's links. And it's also the smart use of AI where possible, to get an early advantage over those that don't.
We always write our content with this goal in mind. We optimize our texts largely to answer questions such as "When will shoe XY be released" or "Where can I buy shoe XY". We always try to answer these questions in our content.
Trying to answer users' questions in our content has always been our goal in SEO and that seems what Google rewards in the long run.
Let's face it, we can't really optimize content for BERT or any other algorithm. As SEOs and content creators, we need to understand that the primary focus of AI in search engine algorithms, is to A) Better understand the context of each query and B) Serve the most relevant, quality piece of content. Make this your north star and you'll be golden.
That said, it's important to remember search engines can't read like you and I, as far as AI has come in the last 5 years it is not close to fully understanding language as we do. So by knowing the limitations of the AI search engines use and what measurable elements they use to assign relevance (topics, entities and keywords) for a given search you have all the information you need to create targeted content.
- Build strong technical foundations. Design lighting-fast websites. Stick to the crawlability rules to ensure content is discovered often and well.
- Oh, and did I mention to write for users? ;)
However, it is pointless to deny that the influence of technologies based on neural networks in the field of optimization is tremendous and grows every year, as new search engine algorithms and tools that experts can use are released.
Thanks to all the experts for sharing their opinion with our readers! ❤️
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