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Virtually everyone with an online presence knows the importance of having a solid content strategy. But let me ask you a question: How much time do you spend on the keyword research process? And here’s another one for you: How good is your keyword research plan?
We all know about Google’s algorithm updates. While we may not know exactly how they work, what we do know is that this search giant is heavily leaning towards offering useful information to its users. Why do I say this? Because it’s all about increasing semantic keyword analysis.
And for me there is no better way to save time and strengthen my keyword strategy than with the help of artificial intelligence (AI) tools. So, without further ado, let me present my case below.
Related: 5 Common Search Mistakes and How to Avoid Them
Understanding semantic keyword analysis
Let’s rewind the SEO clock to a few years ago. Back then, SEO tools were used to determine high search volume keywords. This was fine, but these keywords were then shamelessly “inserted” into the content multiple times, sometimes sounding illogical and even spammy.
This was based on the assumption that the longer the seed keyword appeared in a text, the more Google would pick up on its lexical meaning and rank the content on search engine results pages (SERPs).
Fast forward to the present day. With the many technological advancements underway, we are seeing an increase in the use of not only lexical keywords but also semantic keywords as Google targets search intent and useful content.
This is where semantic keyword analysis comes in. It’s an important strategy for improving content relevance and targeting because it goes beyond traditional keyword matching to better understand user context and intent. Simply put, this means that as Google’s algorithms evolve to understand the semantics behind a search query, we SEOs must adapt to these changes as well.
AI and natural language processing
So how do we adapt? How can we improve our semantic keyword research? How can we speed up the process while producing quality research results and content? Personally, I am a strong advocate of relying on AI to help us achieve efficiency.
And some artificial intelligence technologies, based on natural language processing (NLP), are the perfect application for semantic keyword analysis. Why? Because through NLP and machine learning, computers learn to understand and interpret human language.
The right AI tools can help interpret important linguistic nuances that identify semantic relationships between words. This means that NLP can improve our semantic analysis of keywords at a fraction of the cost and in less time than it normally takes to complete an in-depth research process.
Related: How to Leverage Artificial Intelligence to Boost Your SEO Efforts and Stay Ahead of the Competition
Benefits of semantic keyword analysis with artificial intelligence
Every SEO specialist, including myself, knows the value of in-depth keyword analysis. It’s the foundation for producing quality content, optimizing it, and outperforming the competition with finesse. That’s why AI-based semantic analysis is really at the heart of our efforts.
In particular, some key areas where some AI tools can help include:
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Improve the accuracy of content targeting
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Understand user search intent
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Improve content optimization efforts
In turn, once you implement these elements, you can start to see improvements in your SERP rankings and enjoy higher organic traffic. However, the double whammy comes from higher conversions and better user engagement with your content.
Implementation strategies
Are you already convinced of the power of NLP-based semantic keyword analysis? If so, now is a good time to share some key implementation strategies and practical tips for getting started effectively.
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Choose the right AI tool: First, you need to choose the right AI tool. This may seem obvious, but you should consider your business needs and budget. Look for tools that offer comprehensive keyword analysis that includes search volume, user intent, and content gaps.
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Identify your target keywords: Take your main keyword and enter it into the AI keyword tool. The results you should get are a list of related keywords. These should be accompanied by search volume, competition and a relevance score. It’s time to put on your thinking cap and analyze the list. You need to choose the most relevant, high-traffic keywords for your content while aiming for low to moderate competition.
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Analyze user intent: Your AI-powered tool should also provide you with insights into the user intentions behind search queries. This information can be used to guide your content structure and content creation process. When you meet user needs through content, you can enjoy better visibility and engagement online.
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Optimize your content: You’ve created a content structure and narrowed down the keywords to use in your article or content based on factual data from your AI tool. Now it’s time to optimize it. If you’re creating a blog post, your main keyword should appear in the post title, some headings and subheadings, as well as the meta title and/or meta description. Variations of your primary keywords and semantic keywords should also appear in your content. However, make sure you write with a natural flow of language. Important note: Avoid keyword stuffing as you would avoid any disease.
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Monitor, edit and refine: Your work isn’t done after you hit the “Publish” button. This is where the real work begins. You need to use your AI tool to monitor metrics like organic traffic, bounce rate, time on page, conversion rates, and others. With solid data at your fingertips, you can easily make the necessary adjustments and further refine your content for optimal performance.
And if you still think this sounds too good to be true, consider the case of my blog: InBound Blogging. In the span of just six months, our keyword growth increased from a low of 232 to a whopping high of 3,894 ranked keywords. All this with the help of artificial intelligence tools such as HARPA AI, NeuronWriter, AgilityWriter and others.
Related: Here’s the SEO Combination You Need to Beat Google’s Algorithm
Future trends
To conclude, I would like to leave you with some expectations that I have in terms of semantic keyword analysis using artificial intelligence.
First, voice search. I predict that SEO experts will increasingly implement conversational and long-tail keywords into content, capturing the rise in usage of smartphones and voice assistants.
Second, Latent Semantic Indexing (LSI) keywords will become the rising star of SEO because they help search engines like Google better index content and produce more accurate and relevant search results tailored to user queries .
All in all, AI tools have the power to shape our semantic keyword analysis approaches, speed up our processes, and save us valuable time and money, while producing excellent results for our readers and users.