Unless you're living under a rock, it's impossible to miss Artificial Intelligence (AI) and Machine Learning (ML) while talking about martech today. We've even seen a fresh set of tools launch this past year. Some hard-to-miss ones are:
- Teaching AI to write marketing content
- Increasing conversions with behavioral profiling
- Messaging with AI chatbots
While the use-cases are unlimited, we're touching upon our favorite in this article - Machine learning for SEO. Be my guest!
How Search Engine Optmization is changing because of AI?
Google is tightening up its algorithms around search using machine learning. Their learning algorithms are constantly measuring their users' behavior to surface the most relevant content.
On the other hand, marketing is more data-driven than ever before, and data collection alone is not enough. ML-driven tools are a must-have to make sense of data dumps. And if Google can, why can't we? Especially when we can get continuous, data-backed insights to improve traffic, keywords, rankings, content, and more.
The good news is that Google's constant updates and ML-driven SEO tools are already here. As SEO professionals, SEO specialists, search marketers, and content marketers, adoption is only a matter of time.
At Surfer, we're leveraging ML for your SEO strategy and content needs. Let's dive right in.
Surfer NLP: Optimize content for SEO with Deep Learning
Since 2019, search engines of Google introduced BERT, a type of NLP (natural language processing) to analyze your content marketing efforts. While the response to Google's NLP update was positive, it was still limiting for SEO marketers. And why wouldn't it be? Google set up a general-purpose API for NLP. The update didn't aim at helping marketers like you and me to generate quality content to the fullest. It was lacking context and providing many words and phrases that weren't that relevant. Search rankings went up, but not as high as they could.
So, we created a Surfer NLP engine. I am proud to say Surfer NLP has more raving fans than Google NLP in the SEO community.
In layman's terms, Surfer NLP helps you optimize existing content and write SEO-optimized articles from the beginning. Each top Google search result is measured and analyzed with ai powered techniques making SEO efforts more effective. That's unfair if search engines use machine learning technology while search engine optimization companies not.
Without SEO Machine Learning algorithms we had to rely on general-purpose solutions that do not drive maximum search engine results improvements. Don't be the person lagging behind and help your website climb any search ranking using ai technologies.
How to optimize content using Natural Language Processing?
This is super easy with Surfer thanks to Content Editor tool. It does all the calculations on backstage. Writer sees writing guidelines on the right hand side and can tick off entities by using them in content. The process is not only helping SEO's get optimized content but also writers - to get inspired and know what to write about. Examples of use come handy as well. If you want to know more about it, there is no better place than this video about Content Editor.
Content Planner: Ramp up your content strategy with AI-driven keyword research
We've all been there - doing the grunt work for months to find all the keywords we need to rank for, hunt the keywords we're missing out on, creating excels after excels filled with keywords, phrases, queries, and what-not.
If that wasn't enough, we now have to turn this keyword dump into topical clusters and relevant keyword groups. If you're still breathing after that, good luck charting out a solid content strategy and implementation plan. Also, don't forget to update the keywords, remove some, add more and make sure the list is always relevant.
Overwhelming, isn't it? It doesn't have to be. Take advantage of another field of Machine Learning - clustering.
Enter Content Planner. Powered by machine learning, Content Planner helps you create an always relevant content strategy and breaks it down into small clusters.
How to get unlimited content ideas packaged as clusters using machine learning algorithms?
To get started, add your root keyword. For instance, if your business is automating invoice management, your root keyword could be 'invoice management.'
Once done, Surfer will analyze and come back to you with clusters. Specific search intents make up the cluster.
Curious how Deep Learning solves user intent detection?
We used the same BERT that Google utilizes since the algorithm update. Getting machine learning to work for us wasn't an easy task but paid off. The neuron networks allowed us to teach it how to determine user intent based on search data like meta tags, URL, and search queries.
Here are the four main types:
- Informational - Users search for these keywords when they want to learn about specific topics. They are just trying to educate themselves.
- Customer investigation - Users are looking for specific information around a product or type of product. They could be looking at multiple products, including your competitors'.
- Local - Local services dominate this set of keywords. Their services page or home page are possibly showing up as the top-ranking search results.
- Shopping - You'll find an e-commerce brand ranking for this bucket of keywords. It can even be a category page.
User intent of the seed keyword is crucial to the Content Planner's output. If you expect ideas suitable for the blog, make sure to put seed keyword that you may to write about on your blog. This way Surfer will know about the angle of similar topics you want to get. Don't forget that you can easily use this feature to find new categories for your e-commerce business! Let's have a closer look at this.
Artificial intelligence output on different user intent
First keyword we are analyzing is the red dress. This search term is dominated by online stores, product categories to be precise. And it impact heavily on the output of Content Planner, just take a look.
These topics are great for expanding child categories in your store that will target precisely red dresses long tails. What else can be done to build topical relevancy and boost main category? Of course it is the blog. Creating a bunch of articles about red dresses can be beneficial thanks to internal links. But how to figure out the right topics for the blog? Thanks to using Machine Learning algorithms we can do it by providing the right seed keyword that has clear informational user intent.
Our next keyword is how to wear red dress. Smart way of finding trending topics for the blog, isn't it?
Content Editor: Build content outlines in less than 5 seconds with SEO artificial intelligence
Do you ever feel like you're doing the writer's job when preparing SEO briefs? Especially while creating detailed outlines, so your writer doesn't miss a thing? Yeah, us too. We realized that creating content outlines was a big part of every SEO specialist's job. And a lot of SEO professionals even created templates to suit the content writer's needs. This process was tedious and not real-time. Every time a new piece of content started ranking, SEO marketers had to go back to the drawing board.
Now with Content Editor, Surfer presents Brief. Unique AI-driven paragraphs are written automatically for you. Put an end to the disconnect between the SEO briefs and your writer's final content piece.
Content Editor's Brief uses complex machine learning algorithms in the backend that analyze and present common patterns in all the top-ranking search results. It will take competitors' content and summarize it, making sure you get the best TL;DR ever.
How to write 3000 words long article in 10 minutes?
The outline builder tool can be used as quick and dirty source of unique, optimized content. You can select paragraphs that you like and use them directly on your website, they are generated by AI so you don't have to worry about their uniqueness.
- Pick one H1 that you like the most.
- Browse through H2's and select these that make perfect subheadings to elaborate on.
- Once it's done you have a draft. Check H3-H6 to find smaller topics you can put between H2s.
- Go back to Guidelines tab and check the score. Improve it by adding terms to get at least 70 points.
The article is ready to publish!
Yet it's not the highest quality content, it ranks in Google and can beat even high authoruty sites.
Machine Learning SEO FAQ
Let me try to answer shortly some popular questions about the AI in SEO.
Can IA Content rank in Google?
Yes! It can generate thousands of impressions per month. Here are the stats of an article written entirely by AI.
Why SEO & Machine Learning are joining forces?
It's simple, time-consuming tasks that can be done with higher efficiency and more accurately, eg. keywords clustering.
Does Google use machine learning for search?
Yes, they do it to predict intent and best answers based on user experience.
Which search engine algorithm makes use of machine learning technology?
NLP is one of the Machine Learning realms.
What is Artificial Intelligence in SEO?
It's use of AI technology in SEO tasks like creating content outlines, keyword research or content optimization.
Will SEO be replaced by AI?
In fact it is a battle of two different engines, one from Google and the other, partially automated and kind of guerilla one from SEOs.
Will SEO be affected by growing artificial intelligence?
It is already, just look at the pace of content writers backed up with tools like Conversion.AI
Does Google search use neural nets?
Most likely yes, they have to figure out results for queries that haven't been searched before. This task can be done with help of neural nets.
What are the common types of machine learning used in SEO?
Natural language processing and clusterization are the most common types of machine learning utilized in SEO. It provides great SEO Insights for content.