- Natural language processing (NLP) is one factor you’ll need to account for as you do SEO on your website.
- If your content is optimized for NLP, you can expect it to rise to the top of the search rankings and stay there for some time.
- As AI and NLP keep evolving, we may also eventually see machines doing a lot of other SEO-related work, like inserting H1 and image alt tags into HTML code, building backlinks via guest posts, and doing email outreach to other AI-powered content editors.
- While it seems far-fetched right now, it’s exciting to see how SEO, NLP and AI will evolve together.
- Writer.com’s Co-founder and CEO, May Habib discusses in-depth about SEO content and shares top tools to help you through the content creation process.
Modern websites are at the mercy of algorithms, which dictate the content they show in the search results for specific keywords. These algorithms are getting smarter by the day, thanks to a technology called machine learning, also known as artificial intelligence (AI).
If you want your site to rank in search results, you need to know how these algorithms work. They change frequently, so if you continually re-work your SEO to account for these changes, you’ll be in a good position to dominate the rankings.
Natural language processing (NLP) is one factor you’ll need to account for as you do SEO on your website. If your content is optimized for NLP, you can expect it to rise to the top of the search rankings and stay there for some time.
The evolving role of NLP and AI in content creation & SEO
Before we trace how NLP and AI have increased in influence over content creation and SEO processes, we need to understand what NLP is and how it works. NLP has three main tasks: recognizing text, understanding text, and generating text.
- Recognition: Computers think only in terms of numbers, not text. This means that any NLP solution needs to convert text into numbers so computers can understand them.
- Understanding: Once the text has been converted into numbers, algorithms can then perform statistical analysis to discover the words or topics that appear together most frequently.
- Generation: The NLP machine can use its findings to ask questions or suggest topics around which a writer can create content. Some of the more advanced machines are already starting to put together content briefs.
With the help of NLP and artificial intelligence (AI), writers should soon be able to generate content in less time as they will only need to put together keywords and central ideas, then let the machine take care of the rest. However, while an AI is a lot smarter than the proverbial thousand monkeys banging away on a thousand typewriters, it will take some time before we’ll see AI- and NLP-generated content that’s actually readable.
As AI and NLP keep evolving, we may also eventually see machines doing a lot of other SEO-related work, like inserting H1 and image alt tags into HTML code, building backlinks via guest posts, and doing email outreach to other AI-powered content editors. While it seems far-fetched right now, it’s exciting to see how SEO, NLP, and AI will evolve together.
Major impact from Google BERT update
In late 2019, Google announced the launch of its Bidirectional Encoder Representations from Transformers (BERT) algorithm. BERT helps computers understand human language using a method that mimics human language processing.
According to Google, the BERT algorithm understands contexts and nuances of words in search strings and matches those searches with results closer to the user’s intent. Google uses BERT to generate the featured snippets for practically all relevant searches.
One example Google gave was the search query “2019 brazil traveler to usa need a visa”. The old algorithm would return search results for U.S. citizens who are planning to go to Brazil. BERT, on the other hand, churns out results for Brazilian citizens who are going to the U.S. The key difference between the two algorithms is that BERT recognizes the nuance that the word “to” adds to the search term, which the old algorithm failed to capture.
Instead of looking at individual keywords, BERT looks at the search string as a whole, which gives it a better sense of user intent than ever before. Users are becoming more specific with the questions they ask and are asking more new questions, and BERT breaks down these questions and generates search results that are more relevant to users.
This is great news for search engine users, but what does it mean for SEO practitioners? While it doesn’t exactly throw long-standing SEO principles out the window, you might have to adjust to accommodate the new algorithm’s intricacies and create more content containing long-tail (longer and more specific) keywords. Let’s move on to the next section to learn more about creating BERT-optimized content.
Developing SEO-friendly content for improved Google
When we perform SEO on our content, we need to consider Google’s intentions in introducing BERT and giving NLP a larger role in determining search rankings. Google uses previous search results for the same keywords to improve its results, but according to the company, 15% of all search queries are used for the first time. The implication here is that Google needs to decipher these new questions by reconstructing them in a way it understands.
With this in mind, your SEO should factor in the criteria below:
Core understanding of search intent
While keywords still play an important role in Google searches, BERT also pays close attention to user intent, which just means a user’s desired end goal for performing a search. We may classify user intent into four categories:
- Navigational: The user goes to Google to get to a specific website. Instead of using the address bar, they run a Google search then click on the website link that appears in the search results. It’s possible that these users know where they want to go but have forgotten the exact URL for the page.
- Informational: The user has a specific question or just wants to know more about a topic. The intention here is to become more knowledgeable or to get the correct answer for their question.
- Commercial: The user might not know what they want at the moment, so they’re just looking around for options. They may or may not make a purchase right away.
- Transactional: The user is ready and willing to make a purchase and is using Google to find the exact product they want.
Unlike old search algorithms, the new Google algorithm captures user intent better because it considers the whole context of the search terms, which may include prepositions such as “of”, “in”, “for”, and “to”, or interrogative words such as “when”, “where”, “what”, “why”, and “how”. Your SEO strategy should produce content that:
- Answers a user’s question or addresses a need right away
- Provides value to the reader
- Is comprehensive and focused
You might need to conduct more research about ranking sites for your keyword and check out what kind of content gets into the top results. It’s also a good idea to look at the related searches that Google suggests at the bottom of the results page. These will give you a better idea of user intent and help you draw an SEO strategy that addresses these needs.
Term frequency-inverse document frequency
You might not have heard of the term “Term Frequency-Inverse Document Frequency” (TF-IDF) before, but you’ll be hearing more about it now that Google is starting to use it to determine relevant search results. TF-IDF rises according to the frequency of a search term in a document but decreases by the number of documents that also have it. This means that very common words, such as articles and interrogative words, rank very low.
TF-IDF is calculated by multiplying the following metrics:
- Term frequency: This may either be a raw count of instances of a keyword, the raw count adjusted for document length, or the raw frequency of the most common word.
- Inverse document frequency: This may be calculated by taking the total number of documents, dividing it by the number of documents that have the keyword, then getting its algorithm. If the word is very common across different documents, the TF-IDF gets closer to 0. Otherwise, it moves closer to 1.
When we multiply the metrics above, we get the TF-IDF score of a keyword in a document. The higher the TF-IDF score, the more relevant the keyword is for that specific page. As an end-user, you may use TF-IDF to extract the most relevant keywords for a piece of content.
Google also uses TF-IDF scores in its NLP engine. Since the metric gauges the relevance of a keyword to the rest of the document, it’s more reliable than simple word counts and helps the search engine avoid showing irrelevant or spammy results.
Consumer opinions about brands are everywhere on the internet. If you can find a way to aggregate and analyze these sentiments for your brand, you’ll have some powerful data about overall feelings about your business at your fingertips.
This process is called sentiment analysis, and it uses AI to help you understand the overall emotional tone of the things your customers say about you. It involves three key activities:
- Knowing where your customers express their opinions about your brand, which might include social media, review sites such as Yelp or the Better Business Bureau, forums, feedback left on your site, and reviews on ecommerce sites such as Amazon.
- Utilizing AI and NLP to pull data from these sites in massive quantities, instead of gathering a random sample consisting of just a few comments from each platform. This gives you a clearer overall picture of customer sentiment.
- Analyzing data and assigning positive or negative values to customer sentiments, based on tone and choice of words.
Crafting an SEO strategy that places importance on customer sentiment addresses common complaints and pain points. We’ve found that dealing with issues head-on, instead of skirting them or denying them, increases a brand’s credibility and improves its image among consumers.
Salience and category
If you want to better understand how natural language processing works, you may start by getting familiar with the concept of salience.
In a nutshell, salience is concerned with measuring how much of a piece of content is concerned with a specific topic or entity. Entities are things, people, places, or concepts, which may be represented by nouns or names. Google measures salience as it tries to draw relationships between the different entities present in an article. Think of it as Google asking what the page is all about and whether it is a good source of information about a specific search term.
Let’s use a real-life example. Let’s imagine you do a Google search to learn more about how to create great Instagram content during the holidays. You click on an article that claims to be a guide to doing just that but soon discover that the article contains one short paragraph about this topic and ten paragraphs about new Instagram features.
While the article itself mentions both Instagram and the holidays, it isn’t very relevant to the intent of the search, which is to learn how to document the holidays on Instagram. These are the types of search results Google wanted to avoid when it was rolling out BERT. Instead of trying to game the system to get your content to the top of the search results, you need to consider salience as you produce your online content.
Five tools that can help you develop SEO-friendly content
Given all the changes that Google has made to its search algorithm, how will you ensure that your content remains SEO-friendly? We’ve gathered six of the most useful tools that will help you create content that ranks high and satisfies user intent.
Frase (frase.io) claims to help SEO specialists create content that is aligned with user intent easily. It streamlines the SEO and content creation processes by offering a comprehensive solution that combines keyword research, content research, content briefs, content creation, and optimization.
Frase Content, its content creation platform, suggests useful topics, statistics, and news based on the keywords you enter. If you’re working with a team, the Content Briefs feature tells your writers precisely what you need them to produce, reducing the need for revisions and freeing up their time for more projects.
Writer (writer.com) realizes that we all write for different reasons, and when you sign up, it asks you a few questions about what you intend to use it for. For example, you might be interested in improving your own work, creating a style guide, promoting inclusive language, or unifying your brand voice.
Writer’s text editor has a built-in grammar checker and gives you useful real-time suggestions focusing on tone, style, and inclusiveness. Writer also offers a reporting tool that lets you track your writers’ progress for a specific period, such as spelling, inclusivity, and writing style.
Surfer (surferseo.com) makes heavy use of data to help you create content that ranks. It analyzes over 500 ranking factors such as text length, responsive web design, keyword density, and referring domains and points out common factors from top pages to give you a better idea of what works for a specific keyword.
You can see Surfer’s analysis at work when you use its web-based text editor. You will see a dashboard that tracks what the app calls the “content score”. It also gives you useful keyword suggestions.
4. Alli AI
Alli AI (alliAI.com) offers you a quick, painless way to perform SEO on existing content. All you need to do is add a single code snippet to your site, review Alli’s code and recommendations, then approve the changes. Once you approve the changes, Alli implements them in minutes.
Alli does this by finding the easiest links to build. If you prefer to do things manually, the tool also shows you link building and outreach opportunities. If you’re struggling to keep up with all Google’s algorithm changes, Alli claims it can automatically adjust your site’s SEO strategy.
5. Can I Rank?
Can I Rank (canirank.com) compares your site content to other sites in its niche and gives you useful suggestions for growing your site and improving your search rankings. Its user interface is easy to understand and the suggestions are presented as tasks, including the estimated amount of time you will need to spend on them.
What we like about Can I Rank? is that everything is in plain English, from the menu to the suggestions it gives you. This makes it friendly to those who aren’t technical experts. It also presents data in graph form, which makes it easier to justify SEO-related decisions.
Google changes its search algorithms quite a bit, and getting your page to rank is a constant challenge. Because its latest update, BERT, is heavily influenced by AI and NLP, it makes sense to use SEO tools based on the same technologies.
These tools – such as Frase, Writer, SurferSEO, AlliAI, and Can I Rank? – help you create content that ranks. Some of them check for grammar and SEO usability in real-time, while others crawl through your site and your competitors’ sites and come up with content suggestions. Trying out these tools is the only way for you to know which one(s) work best for you. Stick with it, and you’ll stay ahead of the game and create content that performs well for years to come!
May Habib is Co-founder and CEO at Writer.com.
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