AI keyword research: Unlock Traffic Gold Mines With This Novel Method

Remember when popping some exact-match keywords could skyrocket your page to the top of Google?

That strategy is now as dead as disco.

Google has grown up and become more complex. A single page can rank for thousands of keywords. Now, the question is, how do you find all these keywords that can be targeted with a single page?

There are two ways to approach this part of your Search Engine Optimization (SEO) strategy.

1. The old way: Manually comb through individual SERPS (Search Engine Results Pages) for each keyword, identify the search intent (whether the user wants information, purchase, or compare options), and group related keywords. But that’s about as efficient as running a marathon in flip-flops.
2. The new way: Leverage AI for SEO keyword research. These AI keyword research tools can find low-competition keywords, analyze SERPS, and group similar ones, all while you sip your morning margarita. (Don’t judge. I’m on a juice cleanse.)

Manual keyword research is like bringing a horse and buggy to a Formula One race. It still works, but your competitors might not choose the buggy.

Problems with the traditional keyword research process

The keyword research process often involves the repetitive task of inputting the seed keyword to find related long-tail keywords that are easy to rank. Doing this the old way is tedious, time-consuming, and prone to mistakes. You have to search for keywords related to your topic manually, identify the search intent (whether the user is looking for information, trying to purchase something, or comparing options), and then group them based on Google SERP similarity.

Many content strategists base their content plan on the keyword difficulty score displayed by their keyword tool. The risk with this approach is that, in most cases, these keyword tools only consider links to predict the ranking potential. While links are important, Google’s ranking algorithm has become way more complex. It now considers a myriad of factors — like topical authority, personalization, content depth, user satisfaction, and page-load speed, to name a few. Also, each keyword tool displays a different difficulty score and organic traffic for the same term. Here’s an example where the term “brand promise” returns varying results. And that’s a reasonable difference; in many cases, the difference is significantly larger.

Another problem you’ll face when using popular keyword generators like Google Keyword Planner, Ahrefs’ Keywords Explorer Tool, SEMrush’s Keywords Magic Tool, and Ubersuggest is that they give you a big list of unrelated keywords. You might end up creating separate pages for related keyphrases, creating an unnecessary workload and diluting your content’s potency.

What is AI Keyword Research?

AI keyword research is a process that uses artificial intelligence algorithms and machine learning to discover, analyze, and group relevant keywords. It’s more efficient than manual keyword research because machines can process massive amounts of data and develop thematic keyword clusters at a scale a human couldn’t achieve.

Why you should be using AI for keyword research

The algorithmic nature of keyword research makes it a prime candidate for AI automation. Tasks like keyword collection, pattern recognition, search intent identification, keyword difficulty scoring, and thematic clustering are all tasks ripe for an AI SEO tool. By outsourcing these steps to an AI-powered keyword research tool, you can save time, improve accuracy, and semi-automate your SEO keyword research. I have personally experienced faster search engine rankings using the new method.

Keyword research using AI

Here’s what my AI SEO keyword research looks like:

1. I do topic research based on the business category.
2. After analyzing various topics, I pick my primary topic based on my business strategy and the available resources. A subject that warrants a separate post.
3. I use a keyword suggestion tool to find relevant keywords.
4. I cluster related keywords based on the number of shared URLs in search engine results. You’ll need an AI keyword tool for this step.
5. The main keyword, usually the one with the most search volume and business value, becomes my content hub.
6. The content hub then branches into various connected articles, each focusing on different long-tail keywords. These articles answer my customers’ questions and add topical authority (topic coverage demonstrating my expertise for Google) to my website.

An AI keyword research tool can do all these steps except the business strategy part because AI doesn’t understand your business as you do. I never attempt to automate this part because it needs a human to understand nuanced factors such as brand strategy, customer behavior, and market conditions. Once you do the final step and choose the relevant topics and keywords, you can focus on content creation.

My favorite AI keyword research tools

LarSEO

LarSEO is a relatively new keyword tool, but it’s one of those software that just clicks when you start using it. Here are some of the reasons I love it for keyword research.

The workflow

It’s my favorite AI keyword research tool because of the well-thought-out workflow and the intuitive user interface. It combines AI keyword generation, SERP analysis, and Google SERP-based keyword clustering into one tool. With just this one tool, you can go from your seed topic to a full-blown content strategy. Most other tools I tried involved jumping back and forth between different software, which means more time, money, and energy.

Topic explorer

The topic explorer is a great way to come up with different topic ideas in your niche. Here are some ways to generate topic ideas:

• Competitor URL
• From a domain
• From a seed keyword
• Import your own set of keywords to sort them into topics

Let’s look at an example of how the Topic Explorer: Let’s say you want new topic ideas for your niche “Cybersecurity.” You can simply input your main keyword in the topic explorer, and you’ll get topics like phishing, password management, firewalls, malware protection, etc. You can then choose your main topic based on the business relevance and available resources.

Once you decide to focus, for instance, on ‘malware protection,’ you can use LarSEO’s keyword explorer to generate more keyword ideas.

Keyword explorer:

The keyword generator gives you control like no other tool – it generates thousands of related keywords based on your chosen condition and source. Here are some of the sources LarSEO uses to get you keyword suggestions:

• Google PAA
• Google autocomplete
• Reddit
• Quora
• Any specific site you want to scrape

You can choose different modes to add conditions when scraping from these sources.

• Use NLP to yield more results
• Add an “In Topic” condition to scrape only keywords related to your main topic
• Use Entity filters to sift out non-relevant terms

Keyword clustering

The keyword research tool offers two types of clustering.

Semantic clustering: Semantic clustering groups the list of keywords based on common themes. For example, keywords like ‘account security,’ ‘fraud prevention,’ and ‘secure transactions’ might cluster together as they focus on the security aspect of a product or service. The tool uses AI to understand the context, thereby increasing the feasibility of automated keyword clustering.

SERP clustering: SERP–based clustering checks the number of shared URLs in Google for each keyword and groups them based on this similarity in URLs. You can choose to group all the keywords with either 3 or 4 shared URLs. So, all the keywords that elicit the same Google results are grouped in clusters.

LarSEO has many additional features on top of keyword research, like keyword extraction, content gap analysis, link analysis, and so on. I’ll cover these in my upcoming LarSEO review post.

Keyword Cupid

I think Keyword Cupid was the first keyword clustering tool launched in the market. Before Keyword Cupid, people were manually clustering their keywords, which, as you can imagine, was a royal thorn in the behind.

Keyword Cupid can automatically check Google SERP similarity and create a content silo structure. So, it was an instant fan favorite among SEOs and content strategists. It clusters keywords based on Google’s algorithm rather than randomly grouping them, which makes it incredibly accurate. I like that it can handle thousands of keywords simultaneously, a capacity many AI tools lack— most tools are limited to 3-5K keywords. The only con is that Keyword Cupid doesn’t have an AI keyword generator; you’ll need a separate keyword research tool like Google Keyword Planner to find the keywords.

Once you run the clustering, Keyword Cupid groups keywords into topics and sub-topics. You can view the results in the software or download the Excel and CSV files.

It doesn’t have all the other features LarSEO offers, but it’s still a solid choice if you only need the clustering feature.

Note: These are not the only two keyword clustering tools, but these are the ones I like the best because of their accuracy and the way they streamline the entire content strategy process. Using these AI tools in tandem with some AI content optimization tools and AI copywriting tools can elevate your content strategy.

The future of AI keyword research

As the demand for AI adoption increases and AI developers continue to refine their algorithms, it seems likely that keyword research tools will only grow more sophisticated and effective. We’ll see better keyword ideas, improved keyword grouping, enhanced AI keyword analysis, and more precise prediction of search intent. These SEO tools will help small businesses compete with the big boys.

By letting an AI tool handle much of your keyword research process, you can shift your focus from tedious manual tasks to creating emotionally relatable content that targets those keywords.

The bit where you need manual review is the business value assessment — AI can amplify your efficiency in this area, but it can’t make business decisions for you.