15 Best LLM AI SEO Prompts for Data Analysis

Leveraging AI tools for data analysis in SEO can transform your approach to understanding metrics, identifying trends, and making data-driven decisions. The right prompts can help you extract meaningful insights from complex datasets, automate routine analysis tasks, and discover opportunities that might otherwise remain hidden.

What Are Best LLM AI SEO Prompts for Data Analysis? These are carefully crafted instructions that guide AI language models to analyze SEO data, interpret patterns, generate reports, and provide actionable recommendations. These prompts help SEO professionals and marketers extract maximum value from their data by asking the right questions in ways that AI can effectively process and respond to.

What are the Best LLM AI SEO Prompts for Data Analysis?

1. Keyword Performance Analysis

The Prompt: "Analyze the attached keyword performance data for the past 3 months. Identify the top 10 performing keywords by click-through rate, the bottom 10 by conversion, and suggest 5 optimization opportunities based on these patterns."

When to Use It: When you need to quickly understand which keywords are driving traffic and conversions, and where to focus your optimization efforts.

Variations:

• "Compare keyword performance between mobile and desktop users for the past quarter."
• "Identify seasonal trends in our keyword performance data from the past 2 years."

Additional Information Required: CSV or spreadsheet of keyword data including metrics like impressions, clicks, CTR, position, and conversion data if available.

2. Competitor Backlink Gap Analysis

The Prompt: "Compare our backlink profile with our top 3 competitors. Identify high-quality domains linking to at least 2 competitors but not to us, and suggest outreach strategies for each opportunity."

When to Use It: When planning link building campaigns or conducting competitive analysis to find link opportunities.

Variations:

• "Find industry-specific websites linking to our competitors but not to us."
• "Analyze the anchor text distribution of our backlinks compared to competitors."

Additional Information Required: Your domain and competitor domains, current backlink data for all sites (can be exported from tools like Ahrefs, Semrush, or Moz).

3. Content Performance Audit

The Prompt: "Analyze the attached content performance data. Identify content pieces with high traffic but low conversion rates, low traffic but high conversion rates, and content that ranks for unexpected keywords. Recommend specific improvements for each category."

When to Use It: When conducting content audits to determine which pieces to update, optimize, or repurpose.

Variations:

• "Identify content gaps based on high-volume keywords we're not targeting."
• "Analyze our blog posts to find correlation between content length, format, and performance metrics."

Additional Information Required: Content performance data including URLs, traffic metrics, conversion data, and current keyword rankings.

4. Technical SEO Issue Prioritization

The Prompt: "Review the attached technical SEO audit data. Categorize issues by severity (critical, high, medium, low) and potential impact on rankings. Create a prioritized action plan with estimated level of effort for each fix."

When to Use It: After running technical SEO audits when you need to determine which issues to address first.

Variations:

• "Analyze crawl data to identify patterns in site errors and recommend solutions."
• "Compare pre and post-migration technical SEO metrics to identify new issues."

Additional Information Required: Technical SEO audit data from tools like Screaming Frog, Sitebulb, or Google Search Console.

5. Search Console Data Analysis

The Prompt: "Analyze the attached Google Search Console data for the past 6 months. Identify pages with declining impressions but stable or improving positions, pages with improving CTR, and keywords with high impressions but low CTR. Suggest specific actions for each category."

When to Use It: For regular monitoring of search performance and identifying quick-win opportunities.

Variations:

• "Compare mobile vs. desktop performance in Search Console data."
• "Identify seasonal patterns in our Search Console data from the past 2 years."

Additional Information Required: Export of Search Console performance data including queries, pages, CTR, impressions, and position.

6. Local SEO Performance Analysis

The Prompt: "Analyze the attached Google Business Profile insights for our 5 locations. Compare performance metrics, identify the best and worst performing locations, and recommend specific improvements for underperforming locations based on the successful ones."

When to Use It: When managing multiple business locations and need to standardize best practices across them.

Variations:

• "Compare review sentiment analysis across locations and identify common themes."
• "Analyze local search visibility for each location against local competitors."

Additional Information Required: Google Business Profile insights for each location, including views, searches, direction requests, and review data.

7. Core Web Vitals Optimization

The Prompt: "Analyze the attached Core Web Vitals data for our top 20 landing pages. Identify common issues affecting LCP, FID, and CLS scores. Prioritize fixes based on page traffic and severity of issues, and suggest specific technical solutions for each problem."

When to Use It: When working to improve page experience signals and overall site performance.

Variations:

• "Compare our Core Web Vitals against top 3 competitors and identify competitive advantages."
• "Analyze mobile vs. desktop Core Web Vitals and recommend device-specific optimizations."

Additional Information Required: Core Web Vitals data from PageSpeed Insights, Search Console, or other performance monitoring tools for your key pages.

8. SERP Feature Opportunity Analysis

The Prompt: "Analyze the attached keyword data to identify opportunities for winning SERP features. Find keywords where competitors have featured snippets, knowledge panels, or other SERP features that we could target. Suggest content optimization strategies for each opportunity."

When to Use It: When looking to increase visibility through SERP features and enhance click-through rates.

Variations:

• "Identify question-based keywords in our niche that trigger featured snippets."
• "Analyze video SERP feature opportunities based on our existing content."

Additional Information Required: Keyword data including SERP feature information (from tools like Semrush, Ahrefs, or STAT).

9. Conversion Path Analysis

The Prompt: "Analyze the attached user journey data for organic search visitors. Identify the most common paths to conversion, pages with high exit rates in the conversion funnel, and landing pages with high bounce rates but good keyword rankings. Recommend specific improvements for each issue."

When to Use It: When optimizing for conversions and trying to understand how organic search visitors interact with your site.

Variations:

• "Compare conversion paths between new and returning organic visitors."
• "Identify content that assists conversions but rarely gets direct conversion credit."

Additional Information Required: Google Analytics path data, bounce rates, exit rates, and conversion data segmented for organic search traffic.

10. Content Gap Analysis

The Prompt: "Analyze the keyword rankings for our site and our top 3 competitors. Identify valuable keywords (search volume > 1,000, CPC > $2) where at least 2 competitors rank in the top 10 but we rank lower than position 20 or don't rank at all. Suggest content creation or optimization strategies for these opportunities."

When to Use It: When planning content strategy and identifying untapped keyword opportunities.

Variations:

• "Find topic clusters where competitors have comprehensive coverage but we have gaps."
• "Identify informational keywords in our industry with low competition scores."

Additional Information Required: Keyword ranking data for your site and competitors, including search volumes, competition metrics, and current positions.

11. Seasonal Trend Prediction

The Prompt: "Analyze the attached historical organic traffic data from the past 3 years. Identify seasonal patterns, calculate year-over-year growth rates for each season, and predict traffic volumes for the next 12 months. Highlight keywords and pages with the strongest seasonal fluctuations."

When to Use It: When planning seasonal content and campaigns or forecasting traffic and resource needs.

Variations:

• "Predict next year's traffic based on current growth trends and historical seasonality."
• "Identify keywords with counter-seasonal trends that could balance our traffic patterns."

Additional Information Required: Historical organic traffic data by month/week, keyword seasonal performance data, and historical page performance metrics.

12. User Behavior Analysis

The Prompt: "Analyze the attached user behavior data for organic search visitors. Compare behavior metrics (time on page, scroll depth, click patterns) across different page types and user segments. Identify pages where behavior metrics contradict traditional engagement metrics and suggest reasons for these discrepancies."

When to Use It: When trying to understand how users interact with your content beyond basic analytics metrics.

Variations:

• "Compare user behavior between converting and non-converting organic visitors."
• "Analyze how scroll depth correlates with content length and conversion rates."

Additional Information Required: User behavior data from tools like Hotjar, Crazy Egg, or similar heat mapping and session recording tools, segmented for organic traffic.

13. Algorithm Update Impact Analysis

The Prompt: "Analyze our organic traffic and ranking data before and after the [specific algorithm update]. Identify pages and keywords most affected (positively and negatively), common characteristics of affected pages, and recommend specific recovery strategies for negatively impacted content."

When to Use It: After Google algorithm updates when you need to understand impact and plan recovery actions.

Variations:

• "Compare our algorithm update impact against industry averages."
• "Analyze historical algorithm update impacts to identify vulnerability patterns."

Additional Information Required: Traffic and ranking data from before and after the algorithm update, information about the specific update's focus areas.

14. E-commerce SEO Performance Analysis

The Prompt: "Analyze the attached product performance data for organic search. Identify product categories with strong rankings but poor conversion rates, products with high potential but poor visibility, and seasonal product trends. Recommend specific optimization strategies for each category."

When to Use It: When optimizing e-commerce sites and need to align SEO efforts with revenue goals.

Variations:

• "Compare product description characteristics with organic ranking performance."
• "Identify correlations between product review counts/ratings and organic rankings."

Additional Information Required: Product performance data including traffic, conversions, revenue, and current keyword rankings by product and category.

15. Internal Linking Optimization

The Prompt: "Analyze our site structure data and identify pages with high authority but few internal links, important pages receiving insufficient internal link equity, and orphaned pages with ranking potential. Create a prioritized internal linking strategy to better distribute link equity."

When to Use It: When optimizing site architecture and internal link structure to improve overall site authority distribution.

Variations:

• "Identify topic clusters that could benefit from pillar-cluster internal linking."
• "Analyze anchor text distribution in our internal links and suggest improvements."

Additional Information Required: Site crawl data showing internal link structure, page authority metrics, and current organic performance data.

Tips on How to Write Best LLM AI SEO Prompts for Data Analysis

1. Be specific about data formats: Clearly state what data you're providing and in what format (CSV, Excel, JSON) to help the AI process it correctly.
2. Define clear objectives: State exactly what insights you're looking for rather than asking for general analysis.
3. Provide context: Include background information about your industry, competitors, and previous findings to get more relevant analysis.
4. Set metric thresholds: Define what constitutes "good" or "poor" performance in your prompt (e.g., "CTR below 1%" or "bounce rate above 70%").
5. Request actionable recommendations: Ask specifically for actionable next steps, not just observations.
6. Break complex analyses into steps: For complicated data analysis, structure your prompt as a series of steps for the AI to follow.
7. Specify output format: Request data in specific formats like tables, bullet points, or prioritized lists for easier consumption.
8. Include time frames: Clearly define the time periods you want analyzed and compared.
9. Ask for visualizations: Request that the AI describe potential visualizations that would help illustrate the findings.
10. Use SEO-specific terminology: Incorporate industry-standard SEO terms and metrics to ensure the AI understands your requirements.

How AirOps Aids Your Content Marketing & SEO

AirOps transforms how SEO professionals work with data by providing a powerful platform for creating, managing, and executing AI prompts at scale. Instead of crafting one-off prompts each time you need to analyze data, AirOps allows you to build reusable templates specifically designed for SEO data analysis tasks.

With AirOps, you can:

• Store and organize your most effective SEO data analysis prompts
• Standardize data analysis across your team
• Process large datasets more efficiently
• Automate routine SEO reporting and analysis
• Create custom workflows that combine multiple analytical steps

The platform integrates seamlessly with your existing SEO tools and data sources, allowing you to pull in data from Google Analytics, Search Console, rank tracking tools, and more for comprehensive analysis.

By systematizing your approach to SEO data analysis, AirOps helps you uncover insights faster, make more confident decisions, and focus your time on implementing strategies rather than getting lost in spreadsheets and data.

Ready to transform your SEO data analysis process? Visit AirOps today to see how our platform can help you extract more value from your SEO data and drive better results for your business.

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