Machine learning has affected — and continues to impact — virtually every industry, from medicine to business. Unsurprisingly, it’s changing search engine optimization (SEO) too. You might have already seen evidence of that in your work.
However, learning about what’s on the horizon is one of the best ways to adapt and prepare. Here are some compelling ways machine learning changes SEO. It’s a trend that will continue into 2023 and for the foreseeable future.
1. Offering More Details About How the Audience Feels
Succeeding in SEO means creating engaging content that reflects the audience’s needs. For several years, people have been interested in how social media posts might provide emotional clues about users.
For example, a Penn Medicine team found Twitter users post less-vivid images and those with a lower aesthetic value if feeling depressed or anxious. Elsewhere, researchers at Stony Brook University learned the language people use on Facebook subtly changes in the weeks leading up to an emergency room visit. Their posts became increasingly formal and included more depressed, worrisome or anxious tones as their eventual emergency room trips got closer.
Machine learning algorithms excel at finding patterns in massive amounts of data, which is why many SEO professionals and others use them for sentiment analysis. Taking that approach can reveal whether people reacted to a new blog post in the expected way, or found it boring or inapplicable.
Today’s internet users deal with numerous things competing for their attention at any given time. Fortunately, using machine learning to improve SEO can reveal how people felt after reading content. That data helps marketers adjust their future practices accordingly.
2. Improving the Voice-Search User Experience
Research indicates the computation required to get top-notch machine learning outcomes approximately doubles every 3.4 months and that’s been the case since 2012. As people experiment with using machine learning in new ways, those involved with improving the technology often need more data, realizing the information already used to train machine learning models is insufficient.
The rise of voice searches associated with Amazon Alexa, Google Assistant and similar programs highlights a new use for machine learning many people only thought about relevantly recently. Those assistants use machine learning algorithms to process people’s words, allowing the applications to give relevant answers. This trend also significantly changed SEO.
Changes to the SEO landscape due to voice search are still underway. Thus, researchers remain interested in making voice search accessible and convenient for as many people as possible. A team from the University of Virginia developed a method of converting existing neural networks to make them capable of understanding people speaking at slower paces.
The researchers also believe their work will make the underlying machine learning algorithms provide answers more efficiently. It could even reduce the associated data storage and carbon footprint of such AI applications. If this progress results in more people using voice search and enjoying their experiences, SEO professionals will find they must keep adjusting their practices accordingly.
3. Changing Search Result Rankings
A crucial part of SEO professionals’ work involves producing or managing content to give it the best chance of ranking well within search engine results. For now, that typically means following Google’s recommendations for making high-quality, helpful and authoritative content while staying abreast of news about the company’s algorithm changes.
However, doing what’s necessary to rank well could soon change. Cornell University researchers developed an algorithm that ranks search results based on fairness. They said it’ll reduce potential bias in search results while ensuring the options shown are relevant and valuable.
One of the researchers pointed out how many people who publish YouTube content such as recipes have very similar material, but some of it gets seen much more often than the rest. That’s due to how the algorithms rank what’s there.
This development — dubbed FairCo by the researchers — gives approximately equal exposure to search results with equivalent relevance. It also does not give preferential treatment to search results already ranking well.
Bear in mind that these search algorithms don’t apply in real life yet. However, laboratory experiments like this one show the possibility of major disruptions in the processes for making content rank well. This case is a good reminder of why a significant part of being a well-rounded SEO professional is remaining aware of new developments and pondering how they may eventually impact workflows.
4. Affecting SEO Practitioners’ Workflows
ChatGPT and similar large language models have taken the world by storm. They use a combination of machine learning and deep learning to answer inputs with impressive speed.
People in various industries quickly became curious about how it might help them with tasks ranging from web development to content creation. It’s still too early to predict to what extent these powerful chatbots could change how SEO professionals work.
But, a good thing to remember in these early days is the models have a downside that makes them confidently express false information. Machine learning experts call these instances “hallucinations.”
Consider a case where a Moz journalist asked ChatGPT several questions from the perspective of a business owner setting up profiles to make local SEO gains. The interactions revealed five instances where the chatbot was wrong.
The tricky part of the findings is that the chatbot got most of the information right, effectively making the errors hard or impossible to spot — particularly for someone with limited knowledge of the topic. Some of the answers advised the user to go against Google and Yelp’s policies, for example.
Treat these real-life attempts as cautionary tales, especially if you feel tempted to use ChatGPT to take a few shortcuts. Google prioritizes authoritative content in its rankings. However, factual blunders quickly reveal the content as less legitimate than it may first seem.
Will You Use Machine Learning for Better SEO This Year?
These four examples show how machine learning can majorly affect SEO rankings, audience engagement and more. Even if some of the applications explored here don’t break into the mainstream this year, they show what’s possible and help you become a well-prepared SEO and marketing professional.