How To Use CopyAI's Free Keyword Generator To Begin Keyword Research

Artificial intelligence (AI) has brought immense advances across industries, and digital marketing is no exception. One part that is crucial in digital marketing, is content marketing. When talking about content marketing, we’re talking about content creation. And when it comes to content creation, it is about keyword research.

Creating content alone is a hard task. Before diving into content creation, you need to figure out what content to create. And for that, you’ll need keyword research. Why? Yes, to discover the right keywords that are good for your content, that can capture the essence of your message, and preferably have a good monthly search volume so your content doesn’t end up being seen by only 10 users.

In the past, marketers spent a lot of time analyzing data, examining search queries, studying Google SERPs, and other data to find keywords. It took more time than you can imagine.

But now, with AI, those days are behind us.

Have you ever wondered how to quickly find the right keywords for your content without spending hours digging through data? Have you ever thought of using AI for your keyword research?

Let’s talk about AI keyword generators.

AI keyword generators are simplifying how content creators and SEO professionals research and optimize content and keywords to reach more aligned audiences.

In this post, we'll explore what AI keyword generators are, why they provide immense value, and how to leverage them for enhanced content results.

Let’s break it down.

What Are AI Keyword Generators?

At its core, an AI keyword generator takes the guesswork out of finding keywords. That’s because AI keyword generators use sophisticated machine learning algorithms to analyze massive datasets from sources like Google Search and Amazon Search.

Using semantic analysis, they identify statistical patterns and relationships between words and phrases to generate tailored, relevant keyword suggestions.

Think of it this way—if keyword search used to feel like fishing in the dark, AI turns on the lights and points to where the fish are hiding.

And here’s what AI keyword generators can do for you:

Instantly generating hundreds of long-tail keyword variations related to a seed keyword.
Providing keyword ideas optimized for high search volume and low competition.
Analyzing user search intent signals to recommend phrases aligned to what audiences are seeking.
Continuously improving suggestions based on fresh data on search trends and content performance.

In essence, they automate the tedious process of manual keyword research. Writers now have access through free keyword and research tools to unlimited, up-to-date suggestions to get ideas and optimize their content for search visibility and traffic.

Sounds great for writers, right? Let’s dive deeper into why AI-powered keyword tools are essential for finding new keywords—or even honing in on specific keywords.

Why Are AI Keyword Tools Important?

AI has ushered in a new era where efficiency meets precision for programmatic SEO. The importance of these keyword research tools cannot be overstated, as they streamline traditional content marketing strategy by offering a million high-value shortcuts.

Here are some reasons why AI Keyword Tools are important in today’s content creation process.

Save Significant Time

Manual keyword research was not only labor-intensive and inefficient, but also likely to contain inaccuracies.

Content creators spent countless hours brainstorming potential keywords, assessing their relevance, and analyzing their competitiveness without any guarantees of success.

But with AI keyword tools, those difficult days are gone.

AI keyword tools have dramatically altered this process by providing quick, tailored, data-driven recommendations for best keywords. These tools leverage advanced algorithms to sift through massive data sets, offering precise keyword suggestions within seconds. This efficiency allows content creators to concentrate on crafting quality content rather than getting bogged down in the initial research phase.

For content creators, this also means less time crunching numbers and more time creating amazing content.

Find Long-Tail Keyword Suggestions

One of the challenges in SEO has been identifying relevant long-tail keywords.

These specific, often longer phrases are important for targeting niche demographics (some even say these are the phrases users type when they’re closer to making a decision!) but are difficult for humans to predict and compile due to the amount of possibilities and nuances involved.

AI keyword tools shine in this aspect by employing sophisticated linguistic models to unearth these valuable long-tail keywords. By doing so, they enable content to reach more targeted audiences, often with higher conversion potentials.

Optimize for Search Intent

Not all searches are the same. When using Google Search (or Bing, Safari, etc.), some people might be looking for information, some might be comparing products, and others might be ready to buy. This is known as search intent.

And for that, catering to search intent is key to creating content that not only ranks well in search engine results but also satisfies user queries.

AI tools analyze search behaviors and patterns to deduce the underlying intent behind searches. This capability ensures that all the keywords being suggested are not just relevant but are in alignment with what the target audience is actively seeking, enhancing content visibility and engagement in search results.

For example:

If someone searches for "buy coffee machine online," the intent is transactional—they're looking to make a purchase.
If they search "how to make espresso," the intent is informational—they want to learn something.

Having this insight helps tailor your content to meet users’ expectations.

Provide Comprehensive Analysis

The depth and breadth of analysis provided by AI keyword tools are unparalleled. They analyze billions of data points and offer insights and recommendations that would be humanly impossible to achieve.

This comprehensive AI analysis encompasses not just keyword suggestions but also insights into competition, search volume trends, and recommended content frameworks.

Such exhaustive search data can empower writers to create content that is both relevant and competitively positioned.

How Did We Generate Keywords Before AI?

The advent of AI in keyword research marked a significant departure from traditional methods that were cumbersome, often speculative, and limited in scope.

The days before AI, finding the right keywords was hard work. Writers had to sift through endless spreadsheets of search terms, manually check Google Keyword Planner for inspiration, and use various SEO tools to assess keyword difficulty. Forget all that—AI now does in seconds what used to take hours.

To make it clearer, here’s what writers typically did before AI keyword tools came along.

Brainstorming and Guesswork

Previously, keyword generation was largely a creative exercise, relying heavily on the content creator's ability to brainstorm potential keywords. This approach was not only time-consuming but also full of inaccuracies, as humans are naturally limited in their ability to predict the massive amount of ways a topic might be searched.

Plus, it actually took us writers hours—sometimes even days—to collect keywords and analyze them one by one to find the precise keywords. Can you imagine how hard those days were?

Analyzing Related Pages

Another common method involved analyzing popular keywords being used on related pages or competitors' content. While this could offer some insights, it often resulted in a mimicry strategy that did not necessarily tap into new or emerging search trends. Overall, it limited content differentiation and innovation.

Leveraging Basic SEO Tools

Early SEO tools provided basic functionalities, such as keyword volume and competition levels. However, they lacked the sophistication to offer in-depth context or semantic analysis, requiring users to manually extrapolate and interpret data. This process was not only time-intensive but also less precise, potentially leading to suboptimal keyword choices.

And that was the day before AI.

Today, AI keyword tools have fundamentally transformed this practice, offering a level of insight, efficiency, and precision that was previously unattainable. Content creators can now design their strategies on solid and accurate data-driven foundations, ensuring their content is both relevant and competitive thanks to these AI keyword generation tools.

Now, are you ready to level up your keyword research game? Keep reading as we will dig deeper on how free tools like AI keyword tools can generate relevant keywords for your content marketing strategy.

How Do AI Tools Generate Relevant Keywords?

As often mentioned in this article, AI keyword tools use machine learning algorithms to generate relevant suggestions. These algorithms undergo multiple stages:

Stage 1: Analyze Enormous Datasets

AI algorithms can process billions of pieces of data. They retrieve data not only from search engine databases but also from millions of web pages, social media posts, online marketplaces, and more.

And that’s a lot of information to work with!

But here’s where it gets even smarter and more interesting. Benchmarked against this vast sea of information, AI algorithms extract semantic relationships and context. AI's data ingestion capability helps it understand both explicit and connotative meanings of keyword phrases to make sense of keywords with context.

This means it understands not only the direct meanings of keywords but also the subtle, implied ones.

As an example, the word "bank" illustrates the challenge AI faces in understanding semantics. "Bank" can refer to a financial institution, the side of a river, or even an action (to tilt, as in an airplane's maneuver).

AI algorithms use super-smart techniques to figure out which one makes sense in a given situation. Pretty impressive, right?

Stage 2: Identify Statistical Patterns

When it comes to understanding language, AI can get pretty clever.

Machine learning models in AI dive deep into the web's textual universe to identify word associations, context, and patterns based on the probability of co-occurrence and semantic proximity.

These patterns help them narrow down the practical implications of a particular keyword in a given context. Over time, they are able to convert raw data into organized keyword suggestions that align with the user's search intent.

From the example above, by examining the words that frequently co-occur with the search term "bank," the AI begins to recognize patterns. For example:

In financial contexts, "bank" is often found near words like "account," "loan," "deposit," or "mortgage."
For river-related contexts, it appears with "river," "water," "fishing," or "stream."
In aviation contexts, "bank" might be surrounded by "turn," "angle," "airplane," or "pilot."

TLDR: AI algorithms learn the different meanings of a word by noticing which words it often appears with, then use this knowledge to understand what the word means in different situations. This is a concept that helps AI fine-tune keyword suggestions and make smarter decisions.

Stage 3: Suggest Semantically Related Terms

Following the pattern recognition process, the machine learning models generate a list of keywords semantically connected to the input keywords.

But what does that really mean?

Well, these recommended extended or long-tail keywords are not just synonyms of similar keywords but phrases that users commonly use while searching for similar content. This helps in understanding user behavior and better tailoring your content to meet their expectations.

For example, if you're a digital marketer using an AI tool to generate keywords for a series of articles on financial planning, you might input "bank savings" as your seed keyword.

The AI tool, applying its semantic understanding, suggests related search terms such as "high-interest savings account," "bank deposit certificate," and "online banking savings." It knows you’re talking about finances so it dismisses river-related or aviation-related interpretations due to the contextual signals given by "savings."

By understanding these user-focused terms, you’ll have a better ability to write content that aligns with what your audience is actively searching for.

Stage 4: Continuously Improve with New Data

Like any machine learning system, AI keyword generators learn and improve over time. As more and more data is ingested, AI models reinforce their "knowledge" bases and refine predictions, becoming even more effective at suggesting contextually relevant, popular, and intent-focused words or phrases. This learning curve enhances their capability of identifying newer patterns and relationships, consequently increasing the efficacy of your keyword strategy.

In the world of search engine optimization, AI proves instrumental in generating a dynamic list of keywords that not only match user intent but also stay ahead of changing search trends and behaviors.

How to Use Copy.ai as an AI Keyword Generator

Now, whenever you need to generate keywords, instead of manually inputting a single topic at a time, you can input multiple topics or titles into a defined workflow. This will allow the keyword tool to automatically generate keywords for each of the entered topics in one go, thus achieving a 'bulk' operation.

Remember, the main advantage of a workflow like this is the efficiency it provides. You get to process multiple inputs at once, saving time and effort compared to traditional methods. Instead, you’ll have a comprehensive list of relevant keywords ready to go in no time.

Want to give it a try? Try using Copy.ai workflows as your keyword generator, it is simple and easy!

With Copy.ai Workflows, you can leverage AI to generate a list of related keywords based on a general topic or potential title of a blog article or post.

Here's how you could use Copy.ai Workflows as a keyword generator tool:

Step 1: Define Your Workflow

You start by defining the structure of your workflow in Copy.ai. This structure will include the specific task it needs to accomplish, based on the inputs it will receive.

In this case, your workflow should be structured to take a general topic or hypothetical title of a blog post and generate 5 associated keywords.

For instance, you can define a workflow in Copy.ai to automate the process of generating associated keywords with the instructions:

"Given the topic or title of a blog post, generate 5-10 associated keywords."

Step 2: Run the Workflow

Initiate your workflow. Copy.ai will proceed to generate a list of 5-10 related keywords for your topic.

If you input primary keyword "savings accounts" as your seed into the AI keyword generator, following our above example, the suggested keywords output looks like this:

best savings accounts 2023
high interest savings accounts comparison
top online savings account rates
no-fee savings account offers
how to choose a savings account

Step 3: Bulk Operations and Keyword Analysis

Repeat the process for multiple topics or titles, generating a large list of keywords. Once you have your list, you can run a keyword analysis using your preferred SEO tool (more on these below).

This will give you an understanding of search volumes, keyword metrics, Cost Per Click (CPC), etc, and how competitive these keywords are, as well as their potential relevance to your target audience.

This analysis will help you discover which keywords are worth targeting for on-page SEO, PPC campaigns, or organic search performance. Pay special attention to search queries and user intent to keep relevance high.

Step 4: Assign Keywords to Topics or Titles

After the analysis, you can begin assigning the generated keywords to the relevant topics or titles you're planning to write about. Remember to keep user intent, relevance, and competitiveness in mind when deciding which keywords to use for each topic.

Tips:

Prioritize long-tail keywords if your focus is organic search.
Use high-CPC terms effectively for Google Ads campaigns to increase ROI.
Ensure every piece of content aligns with user intent.

This workflow allows you to generate and assign relevant keywords to your topics at scale, which can greatly streamline your SEO-focused content creation process.

Also important to note, however, is that Copy.ai Workflows don't directly integrate with SEO tools or databases. The keywords generated are contextually related to the seed phrase or sentences based on language models trained on a diverse set of internet text. The process here involves manual analysis of the generated keywords using traditional SEO tools.

Additional Keyword Tools to Consider

While Copy.ai delivers excellent keyword functionality out of the box, combining it with a few additional tools can take your strategy to the next level. Here are some complementary AI keyword tools to consider for your tech stack:

SEMrush Keyword Magic Tool

SEMrush offers robust keyword data and groupings to inform planning. It identifies related keywords, search queries, and helpful groupings to sharpen your PPC or organic search strategies. Need more ideas for your Google or Bing campaigns? This tool's got you covered.

Ahrefs

From keyword difficulty to finding new backlinks, Ahrefs helps both beginners and experts carve their niche in competitive markets.

Use Ahrefs to delve deep into keyword and competitor analysis, helping you craft effective strategies to carve your own niche, no matter whether you're a beginner or a pro.

Analyze search engine rankings with in-depth metrics to refine on-page strategies and scale your goals faster.

Übersuggest

Neil Patel's free Übersuggest tool harnesses AI to churn out endless long-tail keyword variations for seed keywords. This makes it simple to find hyper-specific phrases.

It is perfect for businesses looking to target autocomplete phrases that drive organic traffic. Bonus? It acts as a free tools to use for basic keyword searches!

Moz Keyword Explorer

Moz boasts high-quality metrics like search volume and competitiveness scores. Use it to identify low-hanging fruit keywords to target first.

Blend these with Copy.ai for a truly expansive keyword generation workflow that leaves no stone unturned. From finding specific keywords to improving cost-per-click and driving stronger SERP visibility, you’ll have everything needed to dominate SEO.

For professionals serious about elevating their search game, these tools—paired with Copy.ai—make for a seamless, efficiency-focused tech stack. Give them a try today and watch your results grow!

Simplify Content Strategy with a Keyword Research Tool

Keyword targeting is imperative for content creators seeking to amplify organic visibility, traffic, and enhance value for prospects. Yet for years, these digital marketing efforts were hamstrung by slow, limited manual processes that can be painful and often misses the mark.

The advent of AI keyword generators has completely transformed the keyword research process—unlocking unlimited semantic recommendations in seconds with minimal human effort.

By combining best-in-class AI keyword software like Copy.ai Workflows with supporting tools, marketers now have an automated system for tailored suggestions. This removes all the previous struggles of manual keyword brainstorming.

The result is more organic traffic, more conversions, and more delight for audiences through precisely optimized content. AI eliminates the grunt work so creators can focus entirely on producing standout content that captures share of voice.

Looking for more ways to improve your content strategy? Check out our latest articles:

How To Use Copy.ai's Free Keyword Generator To Begin Keyword Research

Justin Zack