Find Keywords Competitors Are Using in Search and AI

Uncovering the keywords your competitors are using isn't just about traditional search rankings anymore. You now have to analyze two fronts simultaneously: their classic Google rankings and their visibility inside AI answer engines. This means digging deeper than standard SEO tools to see how rivals get cited by models like ChatGPT or in Google's AI Overviews. The new goal is to own conversational topics, not just keywords.

The New Battlefield for Keyword Visibility

The game has definitely changed. For years, competitor analysis was simple: plug a rival's domain into your favorite SEO tool and export their top keywords. That's still a critical piece of the puzzle, but today, it only shows you half the picture. The rise of AI answer engines has opened up an entirely new and vital front for digital visibility.

This shift has given rise to a new discipline: Generative Engine Optimization (GEO). It’s all about getting your brand, your data, and your insights mentioned directly within AI-generated responses. Winning here requires a different mindset. It's less about hitting the #1 spot and more about becoming a trusted, citable source that AI models rely on.

From SEO to AEO

Think of Answer Engine Optimization (AEO) as the natural evolution of SEO. It’s a recognition that people now get answers from two very different places: a familiar list of blue links on a SERP, and a direct, synthesized answer from an AI. Your savviest competitors are already adapting their strategies to show up in both.

This dual landscape creates a massive opportunity. While your rivals might have a stranglehold on certain traditional keywords, they could be completely invisible in AI-generated answers. That leaves a wide-open lane for you to jump in and capture authority.

And this isn't some niche channel you can afford to ignore. The global AI search engine market was valued at USD 16.28 billion in 2024 and is projected to skyrocket to USD 50.88 billion by 2033, according to Grand View Research. That’s a clear signal of where user behavior is heading.

The job is no longer just about finding what keywords competitors rank for on Google. It's about mapping their entire information footprint—from top-ranking blog posts to the specific data points and brand mentions that AI models are picking up and citing in their answers.

Tracking the Unseen Landscape

Trying to track AI mentions manually is a nightmare. It's incredibly difficult and eats up way too much time. This is where a dedicated platform like LLMrefs becomes indispensable. It provides an elegant and powerful solution, automating the whole process by monitoring how your brand—and your competitors'—are showing up across various AI answer engines.

The platform lets you see exactly where your competitors are being cited for your target topics. For instance, if you're a CRM provider, you can track the topic "small business CRM" and LLMrefs will show you which competitors are mentioned most often in AI answers, giving you a clear benchmark for your own efforts.

This kind of data gives you a precise measurement of their influence in the AI search world, revealing strategic gaps you can exploit with your own content. Analyzing this new battlefield is the first and most important step toward building a truly dominant content plan that works for the modern search environment.

Getting to Grips with Traditional Competitor Keyword Research

Before you can even think about what’s happening with AI search, you have to get a handle on the classic stuff. It all starts with figuring out what’s already working for your competition on good ol' Google. This is about pulling apart their strategy to see what makes them tick, so you can build a better one for yourself.

The simplest way to start is just by looking at the search results. I know it sounds basic, but it’s surprisingly revealing. Pick a broad “seed” keyword for your industry, search for it, and see who shows up consistently. Then, click through to their highest-ranking pages.

As you browse, keep an eye out for patterns in their:

• Title Tags: What are the main keywords they're putting right up front? For example, for "project management software", you might see titles like "10 Best Project Management Software Tools of 2025" or "Free Project Management Software for Small Teams."
• URLs: Are they using specific phrases in the URL itself? Does it look like they have a clear topic structure? A good URL might be competitor.com/blog/agile-project-management.
• Meta Descriptions: How are they trying to grab attention and earn the click? What problems are they solving in that tiny snippet of text? A strong meta description might say, "Tired of missed deadlines? Discover the top 5 tools that help you manage tasks, track progress, and deliver projects on time."

This kind of hands-on review gives you a gut feeling for their strategy—something raw data from a tool can never fully capture.

Using SEO Tools to Find the Gaps

While a manual look-see is a great starting point, you’ll need some serious firepower to do this at scale. This is where platforms like Ahrefs or Semrush come in. They let you stop guessing and start making decisions based on hard data, analyzing a competitor’s entire domain in minutes.

The best feature for this job is usually called a “Keyword Gap” or “Content Gap” analysis.

It’s a game-changer. You plug in your site and a few competitors, and the tool spits out a list of all the keywords they rank for that you don't. It’s an absolute goldmine for finding easy wins and uncovering entire content areas you’ve completely overlooked.

A Quick Example: Running a Keyword Gap Analysis

Let’s say you run a project management software company and your biggest rival is “ProjectPro.” Using a tool like Ahrefs, here’s how it would work:

1. Navigate to the "Keyword Gap" tool.
2. Put your domain (yourcompany.com) into the main field.
3. Add projectpro.com as a competitor.
4. Hit the "Compare" button.

You’ll get back a massive, overwhelming list. The real work is in the filtering. I always start by looking for keywords where ProjectPro ranks in the top 10, but my site doesn’t even crack the top 100. This instantly shows you their top-performing terms that aren't even on your radar yet.

Don't get lost in the weeds trying to find every single keyword they rank for. The real goal is to find the high-intent, high-value keywords where they're winning and you're invisible. That’s where you'll find the biggest opportunities.

Manual vs Tool-Based Keyword Discovery Methods

When it comes to finding competitor keywords, you've got two main routes: digging in manually or letting a powerful SEO tool do the heavy lifting. Each has its place, and the best strategists I know use a mix of both.

Method	Pros	Cons	Best For
Manual SERP Analysis	Intuitive, provides context, free, helps understand user intent.	Time-consuming, not scalable, hard to spot all opportunities.	Getting a feel for a new niche, analyzing a single top competitor, understanding SERP features.
SEO Tool (Keyword Gap)	Fast, scalable, data-driven, uncovers thousands of keywords.	Requires a paid subscription, data can lack context without manual review.	Large-scale analysis, identifying content gaps across multiple competitors, finding quick wins.

Ultimately, tools give you the what—the list of keywords. A manual review gives you the why—the strategic context behind why certain pages are ranking.

Picking Apart Their Top-Performing Content

Okay, so you’ve got a list of keywords. Now what? The next step is to actually analyze the pages that are winning those top spots. Don't just stare at the keyword list; go look at the articles and landing pages themselves.

Ask yourself: What are they doing right on this page?

• Are they just focused on one keyword, or are they targeting a whole group of related terms?
• Is the content backed by data, unique research, or customer stories?
• How is the page structured? Is it set up to answer a bunch of common follow-up questions?

For instance, if a competitor is number one for "best agile workflow templates," dig into that page. You’ll probably find they aren’t just hitting that one phrase. They’re likely also ranking for "scrum workflow example," "kanban board setup," and "how to structure a sprint backlog." They're winning because they’ve built a comprehensive resource, not just a thin article stuffed with one keyword.

By the way, these same insights are incredibly useful for paid search, too. Understanding what works organically is often the first step in building stronger PPC campaign optimization strategies.

When you combine a bit of manual SERP detective work with the raw power of SEO tools and a deep dive into your competitor's content, you get a complete blueprint of their playbook. This is the foundation you need before you can start tackling the new world of AI answer engines.

How to Find Competitor Mentions in AI Answers

Welcome to the new frontier of competitor analysis. In this space, success isn't just about hitting the #1 spot on Google anymore. It’s about how often your brand gets cited as an authority within AI-generated answers. This is the heart of Answer Engine Optimization (AEO), and it demands a whole new way to find keywords competitors are using to build influence.

Instead of just tracking URLs, we now have to track brand mentions, data citations, and expert recommendations made by models like ChatGPT, Gemini, and Google's AI Overviews. These are the new "rankings." They show you exactly which competitors are successfully planting their flag as the go-to experts in your niche.

This isn't a small shift—it's happening at a massive scale. As of August 2025, AI search platforms were already pulling in 7.5 billion visits, with ChatGPT alone accounting for a staggering 5.8 billion of them. This data shows a critical trend: smart competitors aren't just focused on traditional search. They're actively diversifying their strategies to show up across this fragmented AI landscape.

Manual Probing for AI Visibility

Before you jump into specialized tools, you can get a surprising amount of intel just by manually asking targeted questions to different AI models. Think of it as hands-on reconnaissance. This approach helps you build an intuitive feel for how different AIs pull information and which brands they tend to favor on certain topics.

The secret is to craft prompts that force the AI to name names.

For example, if you're in the CRM software world, don't ask a generic question like, "what is a CRM." That's too broad. Instead, try these more revealing prompts:

• "Explain the different types of CRM software and list the top 3 companies for small businesses."
• "Create a table comparing the features of Salesforce, HubSpot, and Zoho. Cite your sources for the data."
• "Who are the most frequently cited experts on the topic of customer relationship management?"

Run these kinds of prompts across multiple AIs—like ChatGPT, Gemini, and Perplexity—and you'll quickly build a qualitative map of your competitors' AI footprint. You'll start seeing whose blog posts, white papers, or original research are being used as foundational knowledge.

Automating Discovery with LLMrefs

While manual spot-checks are great for getting a feel for the landscape, they aren't scalable. The AI world is wildly inconsistent; answers change daily based on model updates and new training data. This is where a specialized platform like LLMrefs gives you an incredible, almost unfair, advantage.

LLMrefs was built to solve this exact problem. It’s a fantastic tool that automates the messy, time-sucking process of tracking brand mentions and citations across dozens of AI engines. Instead of sitting there typing in endless prompt variations, you just define the keywords and topics that matter to your business.

The platform then does the heavy lifting, running hundreds of queries across different AI models and geographic locations. The result is a clear, quantitative picture of the competitive landscape.

The goal is to move from anecdotal evidence to a data-driven understanding of your AI "share-of-voice." You need to know not just if a competitor is mentioned, but how often, in what context, and on which AI platforms. This is the data that informs a winning AEO strategy.

Calculating Your Share-of-Voice

LLMrefs takes the unstructured, often chaotic output from AI models and distills it into clean, actionable metrics. It monitors your target keywords and calculates your share-of-voice, a percentage that shows how often your brand is mentioned compared to your competitors for a specific topic.

Let's say you're competing for the topic "content marketing automation." LLMrefs can show you that Competitor A is mentioned in 45% of relevant AI answers, Competitor B is in 20% of them, and your brand is only showing up in 5%.

That simple metric instantly tells you two critical things:

1. Who the current authority is in the eyes of the AI.
2. The size of the opportunity you have to close that gap.

This data-driven approach strips away all the guesswork. You can pinpoint exactly where you’re losing ground and which competitors have built the strongest AI footprint, giving you a clear roadmap for your content and optimization efforts. You can learn more about how to influence AI answer engines in our detailed guide.

This automated intelligence helps you see beyond traditional SEO. It reveals how your competitors are using their content to build authority and earn mentions in the next generation of search.

Turning Competitor Data Into an Actionable Strategy

So you've got a massive spreadsheet overflowing with your competitors' keywords. That's a solid start, but it's not a strategy—it's just a pile of raw data. The real work begins now, turning that intel into a smart, prioritized content plan that actually gets results.

It’s easy to fall into the trap of blindly chasing every keyword your competitor ranks for. Don't do it. A lot of those keywords are duds. Instead, you need to filter everything through a strategic lens that focuses on what will genuinely move the needle for your business.

From Raw Data to a Prioritized List

Your first job is to run that combined keyword list—pulled from both traditional search and AI answers—through a rigorous validation process. You're searching for that sweet spot where opportunity, relevance, and your own team's capabilities all overlap.

I always recommend assessing every potential keyword against three core metrics:

• Search Volume: Is anyone actually searching for this? While big numbers are attractive, don't dismiss lower-volume, high-intent queries. They often convert better.
• Keyword Difficulty (KD): Realistically, how hard will it be to rank? This helps you separate the quick wins from the long-term trench warfare.
• User Intent: What does the searcher really want? Are they just learning, actively comparing products, or are they ready to pull out their credit card? This is, by far, the most important factor.

A fascinating February 2025 study really puts this into perspective. It found that while 71.5% of people now use AI for search, a staggering 79.8% still turn to Google or Bing for their general queries. This split behavior means competitors are getting savvy, targeting long-tail, conversational phrases for AI engines. They know those users expect a comprehensive answer, not just a link. You can check out the full study on AI search engine market trends to see how this should shape your own strategy.

Mapping Keywords to the Customer Journey

Once you've got a handle on intent, the next step is to map these keywords to the different stages of the marketing funnel. This is where you can truly dissect your competitor’s game plan and spot the gaps where you can intercept their audience.

Think of it this way:

• Top-of-Funnel (Awareness): These are broad, informational questions like "what is project management software" or "how to improve team workflow." This is your competitor casting a wide net.
• Middle-of-Funnel (Consideration): Now, people are comparing their options. They're searching for "Asana vs Trello" or "best project management tools for small teams." This shows you exactly who your competitors see as their main rivals.
• Bottom-of-Funnel (Decision): These are the money keywords. Think "ProjectPro pricing" or "sign up for ProjectPro free trial." They signal a clear intent to buy.

By sorting their keywords into these buckets, you can see if they’re pouring resources into awareness content or if they’re aggressively going after ready-to-buy customers. This kind of insight is gold for building out your own paid search intelligence and fine-tuning both organic and paid campaigns.

Creating a Simple Scoring Framework

To cut through the noise and make prioritization dead simple, I recommend creating a basic scoring system. It takes the guesswork and emotion out of the equation, forcing you to focus on the highest-impact activities first. A simple 1-5 scale for each factor works perfectly.

A keyword isn’t just a phrase; it's a direct signal of user need. Your job is to score each signal based on its relevance to your business, the potential traffic it can drive, and your realistic ability to create content that is 10x better than what currently exists.

For instance, you could score a few keywords like this:

Keyword	Relevance (1-5)	Traffic Potential (1-5)	Ability to Win (1-5)	Total Score
"best agile tools for startups"	5	4	5	14
"what is scrum"	3	5	2	10
"project management history"	1	2	4	7

This simple table makes it crystal clear: "best agile tools for startups" is your top priority. It's perfectly relevant, has great traffic potential, and you're confident you can build the best resource on the web for it.

Analyzing Content Types for AI Citations

When you start analyzing your findings from AI answer engines, the game changes a bit. You’re not just looking at keywords anymore; you’re looking at the type of content that gets cited.

Let's say your LLMrefs data shows a competitor is consistently getting cited by AI for "marketing automation statistics." Go look at the source pages. My bet is you'll find they’ve published original research with unique data and charts. That gives you a clear blueprint. To win that topic, you can't just write another generic blog post—you need to produce your own data-driven content.

This is how you turn a simple list to find keywords competitors are using into a powerful, strategic roadmap for creating content that wins.

Building Your Competitor Monitoring System

Finding out what keywords your competitors are ranking for isn't a one-and-done project. It's a moving target. Their strategies change, new players pop up, and the way people search is constantly evolving. A one-time analysis is just a snapshot; what you really need is the motion picture—a system that reveals trends and spots opportunities as they happen.

The whole point is to weave this competitive intelligence into your regular marketing rhythm. You want to turn raw data into a repeatable process that steers your content strategy, both for traditional search and the new frontier of AI answers.

Establishing Your SEO Tracking Baseline

First things first, let's tackle traditional SEO. You need to set up a rank tracking system for those high-value keywords you’ve already identified. Grab your favorite SEO tool, create a new project, and start tracking your domain against your top three competitors for that core list of terms.

This gives you a baseline for performance. Suddenly, you can see week-over-week who’s gaining ground and who’s slipping on the keywords that actually matter to your business. This data becomes the heart of your monthly review, showing you exactly where you need to defend your turf or where a competitor's weakness has created an opening.

This isn't just about collecting data; it's about turning that data into a focused, actionable plan.

This flow—from data gathering to validation to real strategic action—is what separates successful research from a spreadsheet that just gathers dust.

Monitoring Your Share-Of-Voice in AI Answers

When it comes to the AI-driven world, the game is a bit different, but the principle holds. Instead of tracking rank, you’re tracking share-of-voice and citations. This is where a platform like LLMrefs becomes your command center. It offers a fantastic, automated way to keep a constant pulse on how visible you are in AI answers.

Setting up a project is simple. You just plug in your core topics and keywords, and LLMrefs will continuously query different AI models to see who gets mentioned.

This gives you some serious advantages:

• 24/7 Monitoring: It automatically tracks your share-of-voice for key topics, so you don't have to do it manually.
• Competitor Alerts: You get pinged when a rival scores new citations, letting you react in near real-time.
• Performance Tracking: You can actually measure how your AEO (Answer Engine Optimization) efforts are moving the needle over time.

This kind of automated system helps you find the keywords competitors are using to get cited by AI and gives you the intel to build a solid counter-strategy. To get started, we have a powerful ChatGPT fan-out query extractor that can help you discover related topics worth monitoring.

A good competitor monitoring system isn't about creating more spreadsheets; it's about building automated feedback loops. The system should tell you when something important changes, freeing up your team to focus on smart moves instead of manual data pulls.

The Monthly Competitor Review Workflow

To make all this intelligence stick, you need to bake it into your team’s routine. I recommend a concise monthly competitor review meeting. This isn't a soul-crushing deep dive; it's a 30-minute agile check-in to keep everyone on the same page.

Here’s a simple agenda that works wonders:

1. SEO Rank Tracker Review (10 mins):

   • Focus: Look at the biggest movers. Where did we gain or lose serious ground?
   • Action: Pick one competitor page that saw a huge jump in rankings. Assign someone to deconstruct what they did right.

2. LLMrefs Share-of-Voice Update (10 mins):

   • Focus: Any major shifts in AI citations? Did a new competitor suddenly appear on the radar?
   • Action: Find one topic where a competitor's share-of-voice shot up and dig into the content that AI models are citing.

3. Actionable Content Briefs (10 mins):

   • Focus: Based on the last 20 minutes, decide on the next two content briefs.
   • Action: Assign writers and set deadlines. For instance, "Let's create a new data-backed article on 'agile workflow templates' to go head-to-head with Competitor X's new ranking."

This simple, repeatable process ensures your team is always working with fresh insights, not reacting to last quarter's news. It turns competitor analysis from a sporadic research project into a dynamic, ongoing strategic engine that consistently fuels your content pipeline and builds a real, lasting edge.

Got Questions? We've Got Answers

Diving into competitor keyword research, especially with the rise of AI answer engines, can feel like navigating uncharted territory. Here are some straight answers to the questions I hear most often.

How Often Should I Actually Do Competitor Keyword Research?

This is a classic question. For a full, deep-dive analysis, I recommend doing it quarterly. This timing lines up nicely with most companies' strategic planning cycles and content calendars, giving you a solid, big-picture view of any market shifts.

But you can't just set it and forget it. For staying nimble, you should be doing a lighter review of your top three competitors monthly. That's often enough to catch a new content push or a shift in their keyword focus before they build up too much steam.

When it comes to the AI answer engine space, though? That’s a different beast entirely. Answers and the sources they cite can change literally overnight. For this, continuous monitoring is the only way to go. Using a tool like LLMrefs to automatically track your share-of-voice weekly is essential to stay on top of the changes.

What's the Single Biggest Mistake People Make?

Easy. The biggest blunder I see is when a team just scrapes a competitor's keyword list and then tries to copy their content one-for-one. It's a tempting shortcut, but it's a terrible idea.

Why? Their strategy might be a total dud, they could be chasing low-value traffic, or their entire approach might be completely wrong for your business goals.

The real gold is in the gaps. You want to find those high-intent keywords they're ranking for with thin, outdated, or just plain bad content. Or, even better, find the conversational questions in AI search where they aren't even showing up.

Always, always filter a competitor's keywords through the lens of your own goals. Ask yourself: "Can we create something genuinely better for this query?" If the answer is no, move on.

How Is Answer Engine Optimization (AEO) Different From Traditional SEO?

They're related, but the goals are fundamentally different.

With traditional Search Engine Optimization (SEO), your whole world revolves around getting a specific URL to rank high on a results page. The ultimate prize is earning that click-through to your site.

Answer Engine Optimization (AEO), on the other hand, is about injecting your brand's expertise directly into an AI-generated answer. The goal isn't just a click; it's to be cited as an authoritative source that the AI model trusts and references.

This means you're tracking different metrics, too. For AEO, success looks like:

• Citations: How many times do AI models point to your content as a source?
• Share-of-Voice: How often is your brand mentioned versus your competitors for a given topic?

It’s less about winning a single keyword and more about owning the conversation around an entire topic.

Can I Find Keywords for a Competitor Who Has Zero SEO Presence?

Absolutely. You just have to put on your detective hat. If you can't analyze them directly, you use proxies to piece together what their strategy should be.

First, pour over their product pages, service descriptions, and customer reviews. This is where you'll find the exact language their customers use and the problems they claim to solve. Then, look at more established competitors in an adjacent space to borrow some "seed keywords" that a new player would likely target.

Don't stop there. Dig into their press releases, recent job postings (especially for marketing roles!), and what people are saying about them on social media. These sources are often littered with the very phrases and terminology that will become the bedrock of their future SEO and AEO strategy.

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Ready to stop guessing and start measuring your visibility in AI answers? LLMrefs gives you the tools to track your share-of-voice, analyze competitor citations, and build a winning AEO strategy. Get started for free and see where you stand.