6-Step SEO Competitor Analysis [+ How to Track Competitors in AI Search]

In this article, you’ll learn how to conduct a complete SEO competitor analysis that uncovers exactly why your competitors outrank you—and how to close the gap. You’ll also learn how to extend this analysis to AI search engines like ChatGPT, Perplexity, and Claude, where a growing share of your potential customers now discover products and services.

What is an SEO competitor analysis?

An SEO competitor analysis is the process of identifying which websites outrank you for your target keywords, then systematically examining their content, keywords, backlinks, and technical setup to understand why they rank higher than you do.

The goal is not to copy competitors. It’s to identify patterns that search engines reward in your niche—then apply those patterns better than anyone else.

A typical analysis answers questions like: What keywords do competitors rank for that you don’t? Which content formats perform best in your industry? Where do their backlinks come from? Are there technical advantages you’re missing?

When you map these factors across multiple competitors, patterns emerge. You’ll see that top-ranking sites in your space might all have comprehensive guides on certain topics, or they might all earn links from the same industry publications. These patterns become your roadmap.

You should conduct a competitor analysis when launching a new website, entering a new market, or whenever your rankings shift significantly. Most teams run quarterly analyses to stay current with competitive changes.

Where AI search fits in: The same logic applies to AI-powered search engines. When someone asks ChatGPT or Perplexity for product recommendations, certain brands appear consistently while others don’t show up at all. Understanding why requires a similar analytical approach—examining which sources AI engines cite, which content formats they prefer, and what signals drive visibility in AI-generated responses.

Why monitor competitor SEO?

Competitor monitoring reveals what’s working in your market right now. It shows you:

Keyword opportunities you’ve overlooked. Your competitors might rank for valuable terms you never considered targeting. A single competitor analysis often surfaces dozens of keywords with real search volume that aren’t on your radar.

Content formats that consistently win. If every top result for your target keywords is a comparison post, publishing another how-to guide probably won’t break through. Competitor analysis reveals which formats Google rewards in your specific niche.

Backlink sources worth pursuing. Instead of guessing which sites might link to you, you can see exactly which domains already link to competing content. These are sites with demonstrated interest in your topic—making them far more likely to link to your content too.

Technical benchmarks to hit. If competitors load faster, have cleaner site architecture, or better mobile experiences, you need to know. These technical factors directly impact rankings.

Monitoring also sharpens your focus. You can’t compete everywhere at once. By understanding where competitors are strongest (and weakest), you allocate resources to opportunities where you can actually win.

Why AI search monitoring matters now: AI engines increasingly influence buying decisions, particularly in B2B. When a marketing director asks ChatGPT to recommend CRM platforms, the brands mentioned in that response get consideration. The brands left out don’t. Tracking competitor visibility in AI search shows you where you’re losing mindshare in this emerging channel—before it costs you pipeline.

How to conduct an SEO competitor analysis

This 6-step process walks you through identifying competitors, finding gaps in your strategy, and building an action plan to outperform them—in both traditional search and AI-powered search engines.

Step 1: Identify your SEO competitors

Your SEO competitors aren’t necessarily your business competitors. They’re any websites that outrank you for the keywords you care about—even if they sell completely different products.

Start with manual research. Search your primary keywords in Google and note which domains consistently appear in the top 10 results. Look beyond the first keyword. Search 10-15 of your most important terms and track which sites show up repeatedly.

For example, if you sell project management software, search terms like “best project management software,” “project management tools for teams,” and “how to manage remote projects.” The domains ranking across multiple queries are your true SEO competitors.

Pay attention to the full SERP landscape. You’ll see Reddit threads, listicle sites, software review platforms, and direct competitors. They’re all competing for the same clicks—they all deserve analysis.

Use tools to scale discovery. Manual research works, but tools like Ahrefs Site Explorer accelerate the process. Enter your domain, navigate to the Organic Competitors report, and you’ll see a list of sites ranking for similar keywords. The report includes metrics like keyword overlap and traffic share that help prioritize which competitors to analyze deeply.

Document your findings. Create a spreadsheet with columns for competitor domain, estimated traffic, number of ranking keywords, and key observations. This becomes your working document for the rest of the analysis.

How to identify competitors in AI search

Traditional SEO competitor analysis shows who ranks in Google. But a different set of competitors may dominate AI-generated responses—and these deserve separate tracking.

AI engines like ChatGPT, Perplexity, and Claude pull from different source hierarchies than Google. A site ranking #15 in Google might get cited frequently in AI responses, while a site ranking #1 might never appear. The only way to know is to monitor AI outputs directly.

Manual AI competitor discovery. Start by asking the AI engines questions your customers would ask. If you sell CRM software, try prompts like “What are the best CRM platforms for small businesses?” or “Compare Salesforce alternatives for startups.” Note which brands get mentioned and which sources get cited.

Run 10-15 prompts relevant to your business and track: 

• Which competitor brands appear in responses 

• How often each competitor is mentioned

• What position they’re mentioned in (first recommendation vs. also-ran)

• Which sources the AI cites to support its recommendations

Scale with AI search tracking tools. Manual research reveals patterns, but tracking AI visibility over time requires automation. Analyze AI lets you monitor prompts across ChatGPT, Claude, and Perplexity on a scheduled basis—so you can see how competitor visibility changes week over week.

In your Competitors dashboard, you can track specific competitor brands and see how often they appear across your monitored prompts. The tool also suggests competitors you’re not yet tracking based on which brands appear alongside yours in AI responses.

This gives you a competitive map for AI search that parallels your SEO competitor list—but the overlap isn’t always what you’d expect. Some SEO leaders barely register in AI search, while smaller players with strong content strategies dominate AI recommendations.

Step 2: Find keyword gaps

Once you know who your competitors are, identify the keywords they rank for that you don’t. These gaps represent immediate opportunities—terms with proven search demand where you’re currently invisible.

Start with Google Keyword Planner. It’s free and provides a useful baseline. Go to Tools > Planning > Keyword Planner > Discover new keywords > Start with a website. Enter a competitor’s domain and browse the suggested keywords.

For a SaaS competitor, you might discover keywords like “workflow automation for small teams” or “project tracking software free trial”—valuable terms you hadn’t considered targeting.

Evaluate each keyword with these criteria:

• Search volume: Enough traffic to justify the effort? Even 500 monthly searches can be valuable for high-intent B2B terms.

• Keyword difficulty: Can you realistically rank with your current domain authority? Prioritize terms where difficulty matches your competitive position.

• Search intent: Is the searcher looking for information, comparing options, or ready to buy? Match your content format to intent.

Use dedicated gap analysis tools. Google Keyword Planner shows keywords a competitor targets. Dedicated tools like Ahrefs Content Gap or Surfer’s Topical Map show specifically which keywords competitors rank for that you don’t.

The output is a prioritized list of gaps—keywords where you have no ranking presence but competitors do. Sort by traffic potential to identify high-impact opportunities first.

Organize gaps by topic cluster. Don’t treat keywords as isolated opportunities. Group related terms together so you can address entire topic areas rather than picking off individual keywords.

How to find prompt gaps in AI search

Keyword gaps tell you where competitors beat you in Google. Prompt gaps tell you where competitors beat you in AI search—the queries where AI engines recommend competitors but don’t mention your brand.

The mechanics are different. In Google, you optimize pages for specific keywords. In AI search, you optimize for relevance to the questions people ask. A brand might rank for “best CRM” in Google but never appear when someone asks ChatGPT “What CRM should a 20-person sales team use?”

Start with prompt research. Your customer’s questions to AI engines are the “keywords” of AI search. Identify the prompts that matter to your business by thinking about what questions your buyers ask during their research process.

For each prompt category, consider variations: 

• General category queries: “Best [product category] tools” 

• Comparison queries: “[Competitor] vs alternatives” 

• Use case specific: “Best [product] for [specific use case]” 

• Feature specific: “[Product category] with [specific feature]”

If you don’t want to do this, Analyze AI’s Prompt Suggest feature can help. It suggests the prompts you should pay attention to based on your competitors and category.

Monitor prompts systematically. Tools like Analyze AI let you add prompts to your tracking list and monitor them across multiple AI engines automatically. The platform runs these prompts daily and records which brands appear, what sources get cited, and how visibility changes over time.

For each tracked prompt, you can see: 

• Visibility: Does your brand appear in responses? 

• Position: Where do you rank relative to competitors? 

• Sentiment: How positively does the AI describe your brand? 

• Trend: Is your visibility improving or declining?

Identify prompt gaps through the Opportunities feature. Analyze AI’s Opportunities dashboard shows prompts where competitors get mentioned but your brand doesn’t. These are the AI search equivalent of keyword gaps—direct opportunities to improve your visibility.

The report shows which competitors win each prompt and how many times you’re “unmentioned” across your tracked prompt set. Prioritize prompts where multiple competitors appear but you don’t—these represent the highest-visibility gaps.

Action on prompt gaps requires different tactics than SEO. You can’t just publish a new page targeting a prompt. Instead, you need to: 

• Create content that AI engines are likely to cite when answering that prompt 

• Earn mentions on third-party sources that AI engines already trust 

• Improve entity recognition so AI engines associate your brand with the relevant topic

We’ll cover these tactics in the content and citation analysis sections below.

Step 3: Analyze the competitor’s content strategy

Understanding what content competitors publish—and which content drives results—gives you a blueprint for your own strategy.

Audit competitor content formats. Use Ahrefs or Semrush to pull a competitor’s top pages by traffic. Sort by estimated visits and categorize each page by format:

• Blog posts (how-tos, guides, listicles)

• Landing pages (product features, pricing, solutions)

• Comparison pages (your brand vs. competitor)

• Alternatives pages (alternatives to X)

• Resource pages (templates, calculators, tools)

Create a spreadsheet tracking which formats drive the most traffic and links:

Identify patterns across competitors. When you audit 3-5 competitors, patterns emerge. Maybe comparison pages consistently outperform blog posts in your niche. Maybe long-form guides (3,000+ words) dominate while shorter content underperforms. These patterns should inform your content strategy.

Look for content gaps and weaknesses. As you audit competitor content, note:

• Outdated content: Pages with old screenshots, deprecated information, or stale statistics represent opportunities to publish something fresher.

• Thin content: Short pages ranking for competitive keywords are vulnerable to more comprehensive alternatives.

• Missing formats: If no competitor has a calculator or interactive tool for your topic, that’s a differentiation opportunity.

Assess content depth. Don’t just count pages—evaluate quality. For high-priority topics, read competitor content carefully. Ask:

• Does it answer the searcher’s question completely?

• What follow-up questions would someone have after reading?

• Is it well-structured with clear sections?

• Does it include original data, examples, or expert insights?

Every gap in competitor content is a potential advantage for your own.

How AI engines evaluate content differently

Google evaluates content based on links, keywords, and user engagement signals. AI engines evaluate content based on how useful it is for answering specific questions. This creates different optimization priorities.

AI engines favor content that’s easy to cite. When ChatGPT or Perplexity generates a response, it pulls from sources it can attribute clearly. Content with:

• Clear, factual statements

• Well-structured sections with descriptive headers

• Statistics and data points with sources

• Definitive answers rather than hedged language

…gets cited more frequently than content that’s vague, promotional, or poorly organized.

Blog content outperforms product pages in AI citations. Our analysis of 83,670 AI citations found that Claude cites blog content 43.8% of the time—nearly 4x more than ChatGPT’s 16.7% blog citation rate. Meanwhile, ChatGPT and Perplexity cite product pages more frequently (60.1% and 54.3% respectively).

This means your content strategy for AI visibility should emphasize educational, third-party-style content—not just product marketing pages.

Track which competitor content gets cited. Tools like Analyze AI show which specific URLs AI engines cite when responding to your tracked prompts. This reveals exactly which competitor content AI engines trust.

The Citation Analytics report shows: - Which domains get cited most frequently - Which specific URLs appear as sources - How many times each source has been used - Which AI engines cite each source

Analyze patterns in cited content. When you see a competitor’s blog post getting cited repeatedly, study it. What makes it citable? Usually you’ll find:

• Specific, factual claims (not vague marketing language)

• Original research or data

• Clear structure that answers specific questions

• Neutral tone that reads like journalism, not advertising

This analysis informs your own content creation. When you write content intended for AI visibility, model it on the characteristics that get existing content cited.

Step 4: Analyze the competitor’s backlink profile

Backlinks remain a critical ranking factor. Analyzing where competitors earn links shows you where to focus your own link building efforts.

Pull competitor backlink data. Use Ahrefs, Moz, or Semrush to generate a list of domains linking to each competitor. Focus on:

• High-authority domains (DR 70+): Links from authoritative sites carry more weight. Identify which premium sources link to competitors.

• Dofollow links: These pass ranking value. Nofollow links have less SEO impact.

• Topically relevant domains: Links from industry publications and related sites signal relevance to search engines.

Look for patterns in link sources. As you analyze multiple competitors, certain domains will appear repeatedly. If five competitors all have links from the same industry publication, that publication clearly covers your space and accepts outside content. It’s a proven link opportunity.

Common link patterns include:

• Roundup posts: “Best tools for X” articles that list multiple products

• Resource pages: Curated lists of useful tools or guides

• Guest posts: Contributed articles on industry blogs

• Data citations: Original research that other sites reference

Organize findings into an actionable list. Create a link prospecting spreadsheet that captures not just where competitors get links, but what type of content earned the link and what your next step should be.

Identify linkable asset opportunities. The best links come from content that’s inherently link-worthy. When you see competitors earning dozens of links to specific pages, study what makes those pages linkable:

• Original data or research

• Free tools or templates

• Comprehensive guides

• Industry benchmarks

If your competitors earn links through original research, you likely need original research too. If they earn links through free templates, template content should be part of your strategy.

How AI engines use citations differently than Google uses backlinks

Backlinks tell Google which sites are authoritative. AI citation sources tell AI engines which content to trust when generating responses. The mechanics differ significantly.

AI engines cite content in real-time. When you search Google, the ranking algorithm has already evaluated backlinks. When you prompt an AI engine, it decides which sources to cite as it generates the response. This means:

• Recently published content can get cited immediately (no waiting for links)

• Content quality matters more than domain authority

• Source relevance to the specific question matters most

Third-party sources dominate AI citations. Our analysis of 83,670 citations found that 82.9% come from external sources—not the brand’s own website. Only 17.1% of citations point to first-party brand content.

This matches findings from other researchers. Muck Rack’s December 2025 report found 82% of AI citations coming from earned media. Brands are roughly 6.5x more likely to be cited through third-party sources than their own domains.

Track which sources AI engines trust for your topics. Analyze AI’s Top Sources report shows which domains get cited most frequently across your tracked prompts.

This report reveals: - Which third-party sites AI engines trust in your space - How often each domain gets cited - Whether cited sources are competitors, media sites, or neutral third parties

The implication for your strategy: Instead of building backlinks to your own site, consider building presence on the sites AI engines already cite. Getting mentioned in a TechRadar article or an industry analyst report may do more for AI visibility than acquiring a backlink to your own blog.

Monitor competitor citation sources. When you track prompts in Analyze AI, you can see exactly which sources support competitor mentions. This shows you which third-party sites you need to be present on.

If a competitor gets recommended because an analyst report mentioned them favorably, you know earning coverage in that analyst report could improve your own AI visibility.

Step 5: Assess technical SEO aspects

Content and links don’t matter if technical issues prevent search engines from crawling and ranking your pages. Compare your technical performance against competitors to identify disadvantages.

Compare page speed and Core Web Vitals. Use Google PageSpeed Insights to test your pages and competitor pages on the same metrics. Focus on:

• Largest Contentful Paint (LCP): How quickly the main content loads

• First Input Delay (FID): How quickly the page responds to interaction

• Cumulative Layout Shift (CLS): Visual stability during loading

If competitors score significantly better, technical performance may be holding back your rankings. Common fixes include image compression, caching improvements, and removing render-blocking scripts.

Audit for crawl errors and indexing issues. Use Screaming Frog or a similar crawler to compare site structure. Look for:

• Broken links and 404 errors

• Redirect chains

• Duplicate content issues

• Pages blocked by robots.txt

• Missing or duplicate meta titles/descriptions

Document technical findings in a comparison format. Create a spreadsheet that benchmarks your technical metrics against competitors:

Prioritize fixes that close competitive gaps. You can’t fix everything at once. Focus first on technical issues where you significantly underperform competitors. A mobile speed score of 72 vs. competitor scores of 85+ suggests speed optimization should be a priority.

Check site architecture and internal linking. Well-organized sites rank better. Compare:

• URL structure (flat vs. deep hierarchy)

• Internal link distribution (do important pages get linked frequently?)

• Navigation clarity (can users and crawlers find content easily?)

If competitors have cleaner architectures—shorter URL paths, logical category structures, strong internal linking to key pages—consider restructuring your own site.

Technical requirements for AI search visibility

AI engines access content differently than traditional search crawlers, creating distinct technical considerations.

Ensure content is accessible to AI crawlers. AI engines like Perplexity actively crawl the web to update their knowledge. Make sure your content isn’t blocked:

• Check robots.txt for AI-specific crawler rules

• Verify important pages aren’t blocked from GPTBot, Anthropic-AI, or PerplexityBot

• Test that dynamic content loads without JavaScript (many AI crawlers don’t execute JS)

Structured data helps AI understanding. While not a ranking factor, structured markup helps AI engines understand what your content is about. Implement schema for:

• Product information (pricing, features, reviews)

• Organization details (company info, contact)

• FAQ content (question and answer pairs)

• Article metadata (author, publish date, topic)

Optimize for entity recognition. AI engines work with entities—recognized concepts that they understand as distinct things. Strong entity signals help AI engines:

• Associate your brand with relevant topics

• Understand product features and capabilities

• Connect your content to user questions

Tactics include consistent brand naming across all content, Wikipedia presence, and structured data that explicitly defines your brand and products.

Step 6: Set benchmarks and track performance

Analysis without action is just research. The final step converts your findings into measurable goals and tracks progress over time.

Set specific, time-bound KPIs. Based on your competitor analysis, define what success looks like. Vague goals like “improve rankings” don’t drive action. Specific goals do:

• Rank in the top 10 for 15 new keywords within 6 months

• Increase organic traffic by 25% quarter over quarter

• Acquire 20 backlinks from domains with DR 50+ this quarter

• Close the keyword gap with Competitor A by 30%

Track progress with the right tools. Different metrics require different tracking approaches:

• Keyword rankings: Use a rank tracker to monitor position changes for your target keywords weekly

• Traffic: Google Search Console and Google Analytics show organic traffic trends

• Backlinks: Monitor link growth in Ahrefs or Moz

• Competitor movement: Re-run competitor analyses quarterly to catch shifts in strategy

Build a regular review cadence. Set calendar reminders to review metrics monthly and conduct full competitor analyses quarterly. Markets move fast—a strategy based on 6-month-old competitor data misses important shifts.

Document what’s working. When tactics succeed, record them. When they fail, record that too. Over time, this creates an institutional playbook of what drives results in your specific market.

Setting benchmarks for AI search performance

AI search requires different KPIs than traditional SEO. You’re measuring visibility, sentiment, and citation patterns—not just rankings.

Key metrics for AI search benchmarking:

• Visibility rate: Percentage of tracked prompts where your brand appears

• Average position: Where you typically appear in AI recommendations (first, second, or lower)

• Sentiment score: How positively AI engines describe your brand (0-100 scale)

• Citation rate: How often AI engines cite your content as a source

• AI referral traffic: Actual visits from AI search engines to your site

Track AI traffic in your analytics. AI engines now send measurable traffic. Analyze AI integrates with GA4 to show you:

• Total sessions from AI referrals

• Which AI engines drive the most traffic

• Which pages receive AI traffic

• How AI traffic trends over time

The AI Traffic Analytics dashboard shows total AI referrals, 6-month trends, and which percentage of your overall traffic comes from AI search. This lets you set concrete traffic goals for AI search—not just visibility proxies.

Monitor traffic by AI engine. Different AI engines serve different audiences. Track which engines drive traffic to your site so you can prioritize optimization efforts.

If ChatGPT drives 60% of your AI traffic but Perplexity drives only 10%, you might prioritize understanding ChatGPT’s citation preferences.

Track which pages receive AI traffic. Not all content performs equally in AI search. The Landing Pages report shows which specific URLs receive AI referral traffic.

This reveals patterns. If your comparison posts consistently receive AI traffic while your product pages don’t, you know which content formats AI engines prefer to cite. Double down on what works.

Set AI search KPIs alongside SEO KPIs. Build AI metrics into your existing tracking framework:

The brands treating AI search as a measurable channel—not a mysterious black box—will build durable visibility advantages as AI search usage grows.

Key takeaways

For traditional SEO competitor analysis: - Your SEO competitors are websites outranking you for target keywords—not necessarily business competitors - Keyword gap analysis reveals terms competitors rank for that you don’t, creating immediate content opportunities - Content format patterns (guides, comparisons, templates) vary by niche; analyze what works in yours - Backlink sources repeat across competitors—identify patterns for your own link building - Technical performance gaps directly impact rankings; benchmark against competitors and close gaps - Regular monitoring (monthly metrics, quarterly analysis) keeps strategy current

For AI search competitor analysis: - Different competitors may dominate AI search than traditional search—track both - Prompt gaps (queries where competitors appear but you don’t) are the AI equivalent of keyword gaps - Third-party sources drive 83% of AI citations—presence on trusted sites matters more than your own domain authority - Different AI engines prefer different content types: Claude favors blogs, ChatGPT and Perplexity favor product pages - AI referral traffic is measurable—track it alongside organic search traffic - Set AI-specific KPIs: visibility rate, position, sentiment, citation rate, and referral traffic

The integrated approach: SEO and AI search aren’t competing channels—they’re complementary parts of organic visibility. The same foundational work (quality content, strong technical performance, authoritative presence in your industry) drives results in both. The brands that monitor and optimize for both channels will capture more organic demand than those focusing on traditional search alone.

Track your brand’s visibility across ChatGPT, Claude, Perplexity, and other AI engines with Analyze AI. See where competitors win, which sources get cited, and how AI referral traffic impacts your business.