Get a Customized Website SEO Audit and Online Marketing Strategy and Action Plan
Reaching a top-ranked page on search engines is a sought-after accomplishment for companies and content creators in the constantly changing digital market. Large Language Models (LLMs) such as ChatGPT have emerged as powerful tools for analyzing and optimizing web pages for search engine rankings. By fine-tuning these models, you can uncover more profound insights into user behavior, keyword intent, and competitor strategies, all essential for crafting high-performing pages.

In this blog, we delve into the nuances of fine-tuning LLMs for top-ranked page analysis, exploring their capabilities, techniques, and best practices for maximizing their potential.
Understanding Large Language Models and Their Role in SEO
What are LLMs?
Large Language Models (LLMs) are sophisticated AI systems trained on extensive datasets to understand and generate human-like text. These models are designed to perform various natural language processing tasks, including text generation, summarization, and analysis. ChatGPT, developed by OpenAI, is a prominent example of an LLM known for its versatility and adaptability. By applying fine-tuning techniques, these models can be tailored to specific applications such as:
- Content generation: Automating the creation of high-quality, engaging articles, blogs, and website content.
- Keyword analysis: Identifying the most relevant and effective keywords for SEO campaigns.
- Competitor benchmarking: Analyzing the strategies and performance of competing websites.
- User intent prediction: Understanding the underlying intent behind search queries to create more relevant content.
The Importance of LLMs in SEO
Applying LLMs in search engine optimization (SEO) has revolutionized how businesses approach digital marketing. These AI-driven tools streamline and enhance numerous aspects of SEO, enabling teams to work more effectively and achieve better results. Key benefits include:
1. Streamline Content Creation: LLMs can generate well-structured, keyword-rich content that resonates with target audiences. This significantly reduces the time and effort required to produce high-quality material, allowing businesses to maintain a consistent publishing schedule.
2. Enhance Keyword Research: LLMs can identify high-traffic, low-competition keywords with greater precision by analyzing vast amounts of data. These insights help businesses focus on opportunities that drive the most value.
3. Analyze Competitors: LLMs can process and analyze competitor web pages to uncover strategies contributing to their rankings. This includes identifying successful keywords, backlink strategies, and content structures.
4. Improve User Experience: By understanding user intent more effectively, LLMs enable businesses to create content that aligns closely with searchers’ needs. This leads to improved engagement metrics, such as lower bounce rates and higher dwell times, which are critical for SEO success.
Why Fine-Tuning LLMs Matters
While general-purpose LLMs like ChatGPT are exceptionally powerful, they may not fully meet the specific requirements of niche applications, including SEO, without customization. Fine-tuning these models is critical in unlocking their full potential for specialized tasks. Hereās why fine-tuning matters:
1. Specialize the Model
Fine-tuning allows you to adapt an LLM to your domain or industry. For instance, in SEO, a fine-tuned model can:
- Generate content that adheres to specific formatting and style guidelines.
- Analyze niche-specific keywords and topics with greater relevance.
- Understand the nuances of industry-specific language and trends.
By tailoring the model, businesses can ensure it aligns more closely with their unique objectives and challenges.
2. Improve Accuracy
General-purpose models may produce outputs that are too broad or imprecise for specialized tasks. Fine-tuning enhances the accuracy of the model by training it on a curated dataset that reflects the target domain. This results in:
- More relevant keyword suggestions.
- Better understanding of user intent within specific contexts.
- High-quality insights for competitor analysis.
For example, a fine-tuned LLM trained on SEO-related data will be better equipped to generate actionable recommendations for improving page rankings.
3. Optimize Performance
Fine-tuning reduces irrelevant outputs, making the model more efficient and effective for analysis tasks. This is particularly important in SEO, where precision and relevance are key. Benefits of optimized performance include:
- Faster analysis of SERP data and competitor pages.
- More concise and targeted content suggestions.
- Reduced time spent filtering through irrelevant or low-quality insights.
Fine-tuning also enables businesses to maximize the return on investment (ROI) from LLMs by ensuring that the outputs directly contribute to their SEO goals.
Key Steps in Fine-Tuning LLMs for Top-Ranked Page Analysis
Fine-tuning Large Language Models (LLMs) is an intricate process that involves multiple stages to achieve optimal results. Each step plays a crucial role in enhancing the modelās ability to analyze and optimize content for top-ranked pages. Letās explore these steps in detail.
1. Define Objectives
The first step in fine-tuning an LLM is to clearly outline the objectives you aim to achieve. A well-defined objective ensures that the entire process is aligned with your end goals. Here are some common objectives to consider:
- Generating SEO-Friendly Content: Create content that incorporates target keywords seamlessly and appeals to both users and search engines.
- Identifying Gaps in Competitor Strategies: Use the model to analyze competitor pages and uncover areas where your content can outperform theirs.
- Optimizing Existing Web Pages: Enhance the quality, structure, and keyword relevance of your current pages to improve rankings.
By identifying your goals upfront, you establish a clear direction for data collection, model selection, and evaluation.
2. Collect and Prepare Data
Data preparation is critical for the fine-tuning process. A well-curated dataset ensures the model learns effectively and generates accurate outputs. Follow these steps for data collection and preparation:
Gather Relevant Data
Start by collecting high-quality and relevant data to train the model. The following types of data are particularly useful:
- Web Pages That Rank Highly for Target Keywords: Analyze content that consistently appears on the first page of search engine results.
- User-Generated Content: Include reviews, comments, and forum discussions to understand real user queries and preferences.
- Search Engine Results Pages (SERPs) Data: Gather snippets, meta descriptions, and rankings to identify patterns in top-performing content.
Label the Data
Data labeling ensures the model understands the context and structure of the content. Some common labeling techniques include:
- Keywords: Highlight primary and secondary keywords within the content.
- User Intent: Categorize queries into navigational, informational, or transactional intents.
- Content Sections: Identify sections like introductions, body paragraphs, and conclusions to improve structural understanding.
Clean the Data
Remove irrelevant or low-quality data that could skew the modelās performance. Cleaning involves:
- Eliminating duplicate or redundant information
- Correcting grammatical errors
- Standardizing formats for consistency
3. Choose the Right LLM
Selecting the right LLM is vital for achieving your objectives. Here are the primary options:
- GPT Models: These general-purpose models are versatile and widely adopted for a range of tasks.
- Domain-Specific Models: If your focus is on a specific industry, such as finance or healthcare, choose models tailored to those domains.
- Custom Models: For unique requirements, consider creating a model from scratch, though this requires more resources and expertise.
Evaluate the trade-offs between these options based on your use case, budget, and technical capabilities.
4. Fine-Tune the Model
Fine-tuning involves adapting the LLM to your specific dataset and objectives. This process includes the following steps:
Configure Hyperparameters
Adjust the modelās settings to optimize its performance. Key hyperparameters include:
- Learning Rate: Determines how quickly the model updates its weights during training.
- Batch Size: Defines the number of samples processed before updating the model.
- Epochs: Refers to the number of times the model iterates over the entire training dataset.
Use Transfer Learning
Leverage pre-trained models to save time and computational resources. Transfer learning allows the model to build on existing knowledge, requiring fewer resources compared to training from scratch.
Evaluate Performance
Continuously test the modelās outputs using validation datasets. Monitor metrics like accuracy, precision, and recall to ensure the model aligns with your objectives. Make adjustments as needed based on the results.
5. Test and Deploy
Before deploying the fine-tuned LLM, conduct thorough testing to validate its effectiveness. Consider the following steps:
- Evaluate Output Quality: Use test datasets to assess how well the model performs in generating relevant and accurate content.
- Align with SEO Objectives: Verify that the outputs meet your goals, such as incorporating target keywords and improving readability.
- Integrate into Workflows: Deploy the model using APIs or custom software solutions, ensuring seamless integration into your content creation or analysis processes.
Practical Applications of Fine-Tuned LLMs in Top-Ranked Page Analysis
Fine-tuned LLMs offer transformative capabilities for analyzing and optimizing web pages. Here are some practical applications:
1. Keyword Research and Optimization
Fine-tuned LLMs excel at identifying and analyzing keywords. They can:
- Discover Long-Tail Keywords: Find less competitive, highly specific keywords that align with user queries.
- Highlight High-Traffic Terms: Identify keywords with significant search volume and potential for driving traffic.
- Generate Semantic Variations: Suggest synonyms and related phrases to enrich content while maintaining keyword relevance.
By leveraging these insights, you can create content that aligns with search engine algorithms and user intent, improving your chances of ranking higher.
2. Competitor Analysis
Understanding your competition is key to outperforming them. LLMs can:
- Identify Content Gaps: Highlight areas where competitorsā pages lack depth or fail to address user needs.
- Analyze Backlink Strategies: Gain insights into the types of websites linking to competitorsā content.
- Highlight Top-Performing Keywords: Determine which keywords drive the most traffic to competitor pages.
These insights enable you to craft superior strategies and create content that fills gaps while leveraging competitor weaknesses.
3. User Intent Prediction
User intent is at the heart of effective SEO strategies. Fine-tuned LLMs can categorize search queries into different intent types:
- Navigational Intent: Queries where users seek a specific website or page.
- Informational Intent: Searches aimed at finding answers or learning more about a topic.
- Transactional Intent: Queries indicating a desire to purchase or take specific actions.
Understanding these intents allows you to create content that resonates with users, improving engagement metrics such as dwell time and click-through rates.
4. Content Optimization
Optimizing existing content is one of the most effective ways to improve rankings. Fine-tuned LLMs can:
- Enhance Readability: Rewrite content to make it more engaging and accessible to readers.
- Improve Keyword Density: Suggest subtle ways to incorporate keywords without overstuffing.
- Generate Meta Titles and Descriptions: Create compelling snippets that boost click-through rates from search results.
- Suggest Structural Improvements: Recommend headings, subheadings, and content layouts to improve clarity and usability.
By utilizing these capabilities, you can ensure your content meets both user expectations and search engine criteria.
What We Found When Fine-Tuning LLMs?
Scenario: I was trying to analyse the competitorās top ranked pages of the particular keyword āclean portable toiletsā, so I did all the traditional methods like using tools, page analysis but all I get are some numbers of the KPI gaps , and few basic things which is creating a lot of confusions to create a definitive guide and plan of actions for the target page to improve for ranking higher.
Challenge: Finding key gaps from the perspective of the users and search engine algorithm
Here are target pages that are ranking on the 2nd page of Google,
Keyword: āclean portable toiletsā
https://cleanportablerestrooms.com/
Current position: 4
Competitors page those are ranking higher:
https://greengobbler.com/blog/how-to-clean-your-portable-toilet
Current Positions: 1, 2 respectively
Analysis And Solution For Finding The Key Gaps And Plan Of Actions:
Here, I have used the most common and popular three LLMs, Gemini, ChatGPT, and Claude for analyzing the websiteās content, and tried different prompts but couldnāt get the desired results.
Unfortunately, Gemini failed to analyze in-depth, and Claude could not retrieve data from the URLs directly.
So, here, ChapGPT wins the race for accessing and analyzing the website data. However, the challenge was still creating the proper prompt for getting the desired customized results, unlike any generic one.
After doing different prompt experiments, I have created the following prompt for analyzing the ranked pages and developing a plan of action based on the key gaps to improve further.
Here is the Prompt I have used after doing several finetuning:
Output:
Scan the target URL and the competitor’s URL, find the gaps and opportunities for the target URL, and provide a detailed SEO analysis focusing on the following elements:
- Topical Authority: Assess the topic coverage in the target pages and rate the pages with topical authority rating, as well as provide a list of potential semantic topics or keywords for improving the topical authority of the target page.
- Content Depth and Quality: Assess the comprehensiveness of the content, including user testimonials, personal experiences, and update frequency.
- First Paragraph Analysis: scan the first paragraph of the target URL and competitor’s URLs and list out suggestions for better content structure for the users and covering the main target keyword more precisely
- URL Structure: Evaluate the length, descriptiveness, and inclusion of relevant keywords.
- H1 Title Tag: Check the clarity and keyword optimization of the H1 title tag.
- Internal Links: Analyze the presence and relevance of internal links to related articles and resources.
- Meta Description: Review the meta description for accuracy, keyword inclusion, and call-to-action effectiveness.
- Anchor Texts Assessment: analyze the anchor texts present on the pages and create a maximum list of anchor texts for enhancing the keyword’s interlinking distribution
- Readability: Examine the organization, use of headings, bullet points, paragraph length, and overall readability.
- Structure Data: Analyse the structure data of the target URL and Competitor’s URLs and list out the opportunities for further improvement
Additionally, specific action items based on the analysis will enhance the SEO and user experience.
Here Is The Following Final Output I Have Got From ChatGPT:
After analyzing the target URL Clean Portable Restrooms and competitor URLs LetLoos and Green Gobbler, here is a detailed SEO analysis focusing on the specified elements:
1. Topical Authority
- Assessment: The target URL primarily offers information about renting various types of portable restrooms and related services. In contrast, the competitor URLs provide comprehensive guides on cleaning portable toilets, including step-by-step instructions, necessary supplies, safety tips, and additional maintenance advice.
- Topical Authority Rating:
- Clean Portable Restrooms: Low
- LetLoos: High
- Green Gobbler: High
- Opportunities: To improve topical authority, the target site can expand its content to include:
- Detailed guides on cleaning and maintaining portable toilets.
- Safety protocols for handling and servicing portable restrooms.
- Information on eco-friendly cleaning solutions and waste disposal methods.
- Tips for choosing the right portable toilet for specific events or construction sites.
- FAQs addressing common concerns about portable restroom hygiene and maintenance.
2. Content Depth and Quality
- Assessment: The target URL focuses on service offerings with brief descriptions of products like the Standard Portable Toilet and Luxury Flushable Portable Toilet. It lacks in-depth content such as user testimonials, personal experiences, or detailed guides. Competitors provide comprehensive guides with actionable steps, enhancing user engagement and trust.
- Opportunities:
- Incorporate detailed cleaning and maintenance guides.
- Add user testimonials and case studies to build credibility.
- Regularly update the blog with relevant industry news, tips, and best practices.
3. First Paragraph Analysis
- Clean Portable Restrooms: The homepage begins with: “Clean Portable Restrooms rents Standard, Deluxe, Luxury and Wheelchair Accessible Portable Toilets (porta potty rental) and Handwash Station Rental throughout Eastern Massachusetts, South of Boston, Metro West to Rt. 495 and Cape Cod.”
- LetLoos: Starts with: “It is essential to know how to clean a portable toilet. These facilities must be cleaned to a high standard before, during, and after an event.”
- Green Gobbler: Begins with: “Getting ready to get on your boat this summer? Taking a trip in an RV? Regular toilets can get disgusting quick if not taken care of and cleaned regularly, so you can only imagine how gross portable toilets can get after several uses.”
- Suggestions:
- Revise the first paragraph to include the target keyword more prominently.
- Clearly state the services offered and the unique value proposition.
- Engage users by addressing common pain points or questions related to portable restrooms.
4. URL Structure
- Assessment: The target URL is concise but lacks descriptive keywords related to cleaning portable toilets.
- Opportunities:
- Create dedicated pages with URLs like /how-to-clean-portable-toilets or /portable-toilet-maintenance-tips to target specific keywords.
5. H1 Title Tag
- Assessment: The target site’s H1 tag is “Clean Portable Restrooms,” which is clear but generic.
- Opportunities:
- Enhance the H1 tag to include primary keywords, e.g., “Clean Portable Restrooms: Your Guide to Maintaining Hygienic Portable Toilets.”
6. Internal Links
- Assessment: The target site has limited internal linking, primarily directing users to product pages.
- Opportunities:
- Develop internal links to new informative content, such as cleaning guides, maintenance tips, and related services.
- Ensure a logical flow between service pages and informational content to enhance user navigation.
7. Meta Description
- Assessment: The current meta description is not provided in the available data.
- Opportunities:
- Craft a compelling meta description that includes target keywords and a clear call-to-action, e.g., “Discover expert tips on how to clean portable toilets and maintain hygiene at your events. Learn more at Clean Portable Restrooms.”
8. Anchor Texts Assessment
- Assessment: The target site uses generic anchor texts like “More Information” and “Request a Quote.”
- Opportunities:
- Use descriptive anchor texts such as “Standard Portable Toilet Features” or “Luxury Flushable Portable Toilet Details” to improve keyword distribution and SEO.
9. Readability
- Assessment: The content is organized but could benefit from more headings, bullet points, and shorter paragraphs to enhance readability.
- Opportunities:
- Break down content into digestible sections with clear headings.
- Use bullet points to list features or steps.
- Ensure paragraphs are concise to maintain reader engagement.
10. Structured Data
- Assessment: The analysis did not provide specific information on the use of structured data.
- Opportunities:
- Implement structured data markup (Schema.org) for services, products, and FAQs to enhance search engine understanding and improve SERP features.
Action Items to Enhance SEO and User Experience
- Expand Content: Develop comprehensive guides on cleaning and maintaining portable toilets, incorporating relevant keywords.
- Enhance Meta Tags: Revise meta
Conclusion
We can utilize ChatGPT better by fine-tuning the prompts or trained data for Advanced SEO analysis because it has a search engine-like algorithm that helps us get more insights from the Search Engine and User Experience perspective.
Thatware | Founder & CEO
Tuhin is recognized across the globe for his vision to revolutionize digital transformation industry with the help of cutting-edge technology. He won bronze for India at the Stevie Awards USA as well as winning the India Business Awards, India Technology Award, Top 100 influential tech leaders from Analytics Insights, Clutch Global Front runner in digital marketing, founder of the fastest growing company in Asia by The CEO Magazine and is a TEDx speaker and BrightonSEO speaker.