AI-driven keyword research has become indispensable for bloggers looking to grow their audience and boost their online presence. By leveraging advanced ML algorithms, AI tools provide data-driven insights into user search behavior, revealing high-potential keywords to target. This process helps you create compelling, relevant, and searchable content that attracts organic traffic and improves your blog’s search engine ranking. In this article, we’ll introduce you to the benefits of AI keyword research, the best tools to use in 2023, and actionable tips for harnessing their potential to grow your blog exponentially.
What is AI Keyword Research?
AI keyword research is the process of using machine learning algorithms and advanced data analytics to identify high-potential keywords that can help improve a website’s search engine ranking and drive traffic to the site. It involves analyzing user search behavior and identifying relevant, popular, and low-competition keywords to target in content creation.
Importance of Keyword Research
- AI keyword research is an effective marketing tool
- Incorporating the right keywords helps optimize the blogs for SEO which in turn can potentially increase the monthly views of older and updated blogs by an average of 106%
- It is linked to an increase in clickthrough rates
- It generates around 67% more leads
- AI keyword research provides insights into current keyword rankings, helping formulate effective strategies
- SEO is preferred over paid advertisements due to cost-effectiveness, and keyword research helps boost organic search.
Benefits of AI Keyword Analysis
- Helps understand the search demand
- Makes the users aware of competitors’ rankings
- AI keyword research provides ideas for topics for content creation
- Helps explore the potential and preferred keywords at different product or industrial development stages
- Assists in understanding appropriate keywords for the article, as all the generated results are not completely useful
- Enables predictive analytics for keyword research.
Several AI keyword research tools are available in the market. Here is a list of the most popular ones that have helped brands drive successful businesses online:
It helps optimize websites through a huge keyword database along with competitive SEO analysis. The users must provide the domain or website to gain insights on the top-performing keywords in current articles. Alternatively, users are free to put in keywords in exchange for long-tail keywords and associated crucial metrics. It is also user-friendly, easing usability. The application of filters further eases its operation.The broad, phrase and exact match are some interesting options for playing with keywords and curating the articles.
Features and capabilities of SEMRush
- SEO Writing Assistant
- Keyword gaps
- Backlink analysis
- Website SEO audit
- Keyword magic tool
It provides the best keyword research and analysis tools for any category type. The platform is suitable for finding keywords with low difficulty. It also allows users to search by domain, location, and language applicability.
Features and capabilities of KWFinder
- Possibility to refine the keyword suggestion list
- User-friendly interface
- Reliable statistical data on each keyword
- Detailed SERP overview coupled with a suggestion list
It is the most popular and commonly used search engine optimization tool. Ahrefs is an all-rounder due to its functions of keyword tracking, site audits and backlink analysis. The reliability and accuracy make it stand out among other available options. Content creation, finding FAQs, and using the site to find keywords with high-ranking possibilities are some of the numerous features provided. Moreover, it is compatible with multiple search engines.
Features and capabilities of Ahrefs
- Content explorer
- Rank tracker
- Content gap analysis
- Keyword explorer
- Website SEO audit
4. Google Keyword Planner
It is a simple tool providing minimal facilities. The accuracy of the tool makes it worth using. Even the tool lists the most accurate keyword data source.
Features and capabilities of Google Keyword Planner
- Reliability and accuracy
- Best and recommended for business-based websites
- Accurate search volume based on Google search
- Option to find a specific list of commercial keywords
This AI-powered keyword discovery tool is best suited for marketers and bloggers. It provides the most searched keywords to quickly reach the top search results. They also provide a new and unique feature of content outline generation. The latter can be based on word count, header, images, keywords, links and other options. There are other options as well, such as backlink data and Google/Facebook Ads.
Features and capabilities of GrowthBar
- On-page word count
- Keyword rank tracking
- Long tail keyword suggestion
- Generate content outlines with AI
- Exportable keyword data
- Accurate ranking difficulty
Additionally, ChatGPT, the trending AI tool, can also be used for AI keyword research. It is not very effective for keyword research, but it can help find seed keyword ideas.
Techniques for Artificial Intelligence Keyword Research
The below-mentioned techniques will help in AI-powered keyword discovery:
- Create a broad list of topics for the specific product or service of interest
- Further, specify the list by looking for primary and secondary keywords through phrases or words appropriate or linked to the product.
- Look for keywords or terms.
- Analyze the keyword quality by identifying search volume, competition ranking, and other parameters.
- Refine the keyword suggestions
- Check your competition and find how you stand out from them
- Understand the intention of the search and answer accordingly for better ranking
NLP and its Role in AI Keyword Research
Natural language processing is the branch of artificial intelligence that deals with the communication of computers with humans. It helps in analyzing written texts and spoken language interpretation. NLP can translate the programs, thus finding usage in GPS systems, Siri, Alexa, and business operations and increasing employee productivity.
NPL keyword research is crucial because it can analyze and extract keywords through written and oral searches. It is also beneficial for evaluating search content intent due to the ability to understand sentiments in comments and messages. NLP finds function in text classification and content creation through the collection and analysis of unstructured data.
Sentiment Analysis and its Role in Keyword Research
Sentiment analysis refers to the recognition of emotions. It becomes a challenge when you have to perform it for a given text, which often lacks punctuation when searched. However, Machine learning keyword research is required to understand the sentiments or emotions of the customers. The analysis helps extract social media and customer feedback information and provides relevant keywords for potential content.
Keeping sentiment analysis results in mind while curating content is essential to answer the customer correctly. Otherwise, your content might fail to get the visitors hooked, and they may exit the site without going through the content.
Predictive Analytics and its Role in Keyword Research
Predictive analytics for keyword research refers to historical data usage for predicting future events. The constant change of demands among customers requires blogs directed towards the future. As a content curator or search engine optimizer, you should be able to be aware of future possibilities of products or services.
Applying predictive analytics for keyword research is different from reactive analysis, wherein the results are in response to user search queries. In predictive SEO, predictions are made via thorough analysis for upcoming keywords and search trends. Incorporating these keyword suggestions helps you stand a stronger chance of ranking high on search engines.
For example: Optimizing your content for an upcoming iPhone is a simple example of predictive SEO. An AI keyword research tool with predictive analysis can help you find many such keywords that have a high ranking possibility.
How to do AI KW Research?
Though AI intervention has eased the process of keyword research, we are yet to explore the full potential of its capabilities. AI/ Machine learning keyword research can be further optimized through stated practices:
- Understanding the intent behind the keywords
Search intent or user intent refers to understanding the requirement of a user looking for a specific query. The search intent can be navigational, informational, transactional or commercial. Based on the service, ensure that your research meets the correct search intent. Then optimize the content for the best user experience through video, images, usage or subheadings. You must also improve the existing content of old web pages by updating them according to current needs.
- Identifying long-tail keywords using AI
The lengthy keywords marked by more than three words are queried as sentences, questions and phrases. These are of high value due to the specificity of the query and are linked with high purchase intent. To identify the same, first examine the autocomplete suggestions in Google. Use question modifiers and qualifiers and analyze the internal site search history to gain information on the user requirement. Check the gap as well to know the missing link in the availability of topics. Remember, long tail keywords come with lower competition and give you an opportunity to rank higher!
- Analyzing competitor keywords using AI
Ranking above the competitor requires insight into their services and strategy. Use AI keyword research to find the competitor keywords. It is a time taking process. But with AI keyword research tools, you can find a competitive analysis template, generate a list of SERP competitors and find their keywords. Compare the keyword and content gaps and optimize your older content or curate new content to meet the gap.
How to Use AI Keyword Research for SEO?
Search Engine Optimization is an important method to reach the top of the search query page. Here is AI’s contribution to the same:
1. Integrating AI Keyword Research into your SEO strategy
Integrating the two results in enhanced performance and facilitates reaching the top ranks on SERPs. The combination focuses on identifying the context, concept, and customer satisfaction. It helps reach efficient results by discovering hidden ranking opportunities, allowing content creation and optimization. Moreover, it extracts keywords from voice search, scales the SEO and is linked with user experience.
2. Creating optimized content using AI Keyword Research
AI keyword research helps optimize content by focusing, prioritizing and evaluating the content for indexing. You can place relevant keywords in the content, meta tags and headings to attract users. It helps in content optimization by suggesting crucial links and different elements necessary for the content to improve the search rankings.
3. Measuring the success of AI Keyword Research in SEO
The best performance of content curated through the help of AI keyword research is possible by analyzing the following aspects:
- Gain insight into the organic search traffic
- Analyze the SEO traffic quality through the interpretation of assisted conversions
- Have detailed information on the efficiency of click-throughs from different keywords, estimated cost-per-click, and other similar data.
Future of Keyword Research
AI-powered keyword discovery is constantly optimized for better efficiency results. Here is how it has impacted:
1. Advancements in AI technology for keyword research
The AI keyword research has advanced enough to create SEO content, audit and monitor, optimize content, and improve keyword research and analysis. It helps analyze anchor text usage, traffic and ranking growth analysis and search engine algorithms. The blogs can further control and modify the SERP rankings, along with the potential to remain consistent on top.
With exponential technological advancements, we can expect AI to further ease keyword research with more efficient predictive algorithms.
2. Integration of AI with other SEO techniques
Besides keyword research, numerous other SEO techniques, such as discovering competitors’ best-performing keywords and pages, identifying and addressing toxic or non-functional links, effective backlinking, and more, can help optimize blogs. The AI intervention in the same, along with gap analysis, optimization for image SEO and other methods, is a potential futuristic idea for AI integration with SEO techniques.
3. Predictions for the future of AI Keyword Research
The coming years will surely witness increased SEO for visual content. The SERP rankings will be based on relevance and quality rather than the simple presence of keywords. The SEO for mobile and voice searches will be significantly more important than web browsing.
Revolutionize Your Blog Growth with AI
AI keyword research is one of the most promising methods to reach the top of the search engine results pages. Additionally, it is not just about incorporating the keywords; with AI intervention, businesses can measure success through different criteria and focus on curating relevant content for increased reach. Employing sentiment analysis and predictive analysis and understanding the search intent will help you stand stronger amidst SERP rankings.Keep following Anaytics Vidhya blogs to know more about AI and its imapct on marketing!
Frequently Asked Questions
A. Yes, there are AI-powered SEO tools that use machine learning algorithms and data analysis to provide insights on keywords, content optimization, link building, and other SEO- tasks. These tools can help improve a website’s search engine ranking and drive organic traffic by providing data-driven insights and recommendations.
A. To generate keywords for SEO, start by brainstorming relevant topics and terms to your website and target audience. Use keyword research tools to identify high-potential keywords based on search volume, competition, and relevance. Analyze user search behavior and search intent to create a list of long-tail and semantic keywords to target in content creation.
It is unlikely that AI will completely replace Google search in the near future. While AI and machine learning technologies are used by Google to improve search results, the search engine’s complex algorithm and vast infrastructure are still essential components of the search process.
By Analytics Vidhya, March 28, 2023.