AI search competitor analysis: a 5-step GEO guide (2026)

What is competitor analysis in GEO, and why compare competitors in AI search now?

In 2026, with AI search spreading fast, knowing "how AI search results treat your company" is no longer optional for marketers. But looking only at your own situation is not enough. Analyzing and comparing how competing brands are mentioned in AI search, in other words competitor analysis for generative engine optimization (GEO), is the key to strategic differentiation.

Traditional SEO competitor analysis compared search rankings, domain authority and backlink counts for specific keywords. AI search is fundamentally different. What matters is which brands are recommended, in what context and how often in the answers generated by each LLM (large language model), such as ChatGPT, Gemini, Claude and Perplexity.

Why do you need competitor analysis for GEO now? There are three reasons.

• AI search is gaining share: As of 2026, AI search use is growing rapidly in Japan too, and a growing group of users cannot be reached if you rely only on traffic from traditional search engines
• More zero-click searches: Because AI presents answers directly, more and more users make purchase decisions without visiting a website. If your company is not in the AI's answer, you are not even among the options
• Competitors' moves are hard to see: Traditional SEO had a clear metric in search rankings, but AI search generates answers dynamically, so it is hard to tell where competitors stand

Against this background, competitor analysis for GEO is set to become one of the most important efforts in digital marketing strategy. This article explains in detail how to compare competitors in AI search, with step-by-step procedures and the tools you can use.

Competitor analysis in AI search is no longer a "nice to have." It has entered the phase where not doing it means falling behind your competitors. In particular, understanding and using a new metric, mention share, will shape competitive advantage in the AI era.

Three ways to compare competitors in AI search results

There are three broad approaches to competitor analysis for GEO. Understand the pros and cons of each, then choose the one that fits your situation.

Method 1: Qualitative analysis via manual checks

The simplest method is to check manually by actually using AI search tools. Ask ChatGPT, Gemini, Claude, Perplexity and others questions in Japanese using keywords related to your business, the way your customers in Japan would, then record and compare the answers.

• Pros: It costs nothing. You can understand the nuance and context of AI answers in depth. You can start right away
• Cons: It takes time. Quantitative comparison is difficult. Continuous tracking is hard. It is prone to the bias of whoever does the checking
• Good for: Companies that want to get started with GEO. In-depth research on specific keywords

For manual checks, we recommend that you always ask several AIs the same question and record the answers in a spreadsheet. Record the date, the AI, the prompt, the brand names mentioned in the answer and the context of each mention (positive/neutral/negative).

Method 2: Systematic analysis via prompt design

One step beyond manual checks is to design prompts for analysis systematically. Asking questions from several angles gives you a more complete competitor comparison.

Effective prompt patterns include the following (for the Japanese market, ask them in Japanese):

• "Recommend five products for X" (recommendation)
• "Compare the well-known brands in the X space" (comparison)
• "Tell me how to solve X, with specific product names" (problem-solving)
• "Which service has the best reputation for X?" (ranking)
• "What criteria should I use to choose X, and which brands do you recommend for each criterion?" (criteria)

Combining these prompt patterns shows you the full picture of the contexts in which AI recommends each brand. However, this method still requires running the prompts by hand on a regular basis and tallying the results.

Method 3: Automated analysis with dedicated tools

The most efficient and accurate method is automated analysis with a dedicated GEO tool. A tool can send queries to multiple LLMs on a schedule, tally the results automatically and track them over time.

• Pros: Less work thanks to automation. Analysis based on quantitative data. Tracking of changes over time. Comparison across multiple LLMs
• Cons: The tool costs money. Choosing a tool can take time
• Good for: Companies taking GEO seriously. Cases that require continuous monitoring of multiple keywords

Understanding how mention share works and how it is calculated before you use a tool will help you read the data more deeply.

How to do GEO competitor analysis: the 5 steps at a glance

Start with the big picture. GEO competitor analysis can be organized into the following five steps. The flow is the same whether you work manually or with a tool.

1. Listing jobs (keywords): Starting from the problems (jobs) your customers want to solve, list keywords in the natural phrasing people use when they ask AI.
2. Preparing question templates for the major LLMs: Sort the questions you will send to ChatGPT, Gemini, Claude and others into patterns such as recommendation, comparison and problem-solving.
3. Recording the brands mentioned: Record the brand names, their positions and the context in each answer in a spreadsheet (an example format follows below).
4. Calculating mention share: From the recorded data, calculate each brand's count of answers that mention it as a share of the sum of that count across all tracked brands (mention share).
5. Running ongoing monitoring: Measure continuously on a weekly or daily basis, track how shares change and run a PDCA cycle.

Below, we go into detail on the three parts where people most often get stuck: recording (step 3), the formula (step 4) and ongoing monitoring (step 5).

Recording the brands mentioned (step 3): a spreadsheet example

If you analyze manually, a spreadsheet with the following columns makes tallying easy. Use one row per answer (one prompt × one LLM) as the basic unit.

Recording in this format makes it easy to tally by keyword, LLM and context, and you can use the data as is for the mention share calculation below.

The mention share formula (step 4)

Mention share is a metric that shows, across the AI answers for a given keyword, each brand's count of answers that mention it as a share of the sum of that count across all tracked brands. The basic formula is as follows.

Mention share of brand X (%) = number of answers that mention brand X ÷ sum of that count across all tracked brands × 100

For example, suppose you measure 5 prompts × 3 LLMs = 15 answers, and SleepWell appears in 9 of them, NightRest in 12 and DreamPillow in 6. The sum of these counts is 9 + 12 + 6 = 27, so SleepWell's mention share is 9 ÷ 27 × 100 = about 33.3%.

For a more precise picture, you can also take a weighted average based on each LLM's share of users. The thinking behind the calculation is explained in detail in What is mention share? How to measure and use it.

How often to monitor and how to run it (step 5)

GEO competitor analysis is meaningless if you do it only once; it assumes continuous, ongoing monitoring. Here are guideline frequencies by purpose.

Keeping up daily measurement by hand is hard in practice, so at the full-scale stage, companies usually consider automating it with a tool.

Ready-to-use competitor analysis prompts

Below are prompts you can copy and paste for GEO competitor analysis. Replace {keyword} with your job (the customer's problem) and paste them into ChatGPT, Gemini, Claude and others. For the Japanese market, ask them in Japanese, the way your customers would.

1. Recommend 5 products or services for {keyword}, with your reasons for each.

2. Compare the popular brands for {keyword} and show the strengths and weaknesses of each in a table.

3. Tell me how to solve problems with {keyword}, and name specific products you recommend.

4. Which service has the best reputation for {keyword}? Please explain why.

5. What criteria should I use when choosing {keyword}, and which brands do you recommend for each criterion?

6. Suggest 3 brands that someone new to {keyword} should consider first.

Send the same prompt to several LLMs and record the brands that appear in the answers in the spreadsheet described above. Answers change from day to day, so repeating the same question regularly is the key to accurate results.

Step-by-step GEO competitor analysis

From here, we explain in detail the five steps for actually carrying out GEO competitor analysis. The basic flow is the same whether you work manually or with a tool.

Step 1: Select the keywords to analyze

It is no exaggeration to say that the success of GEO competitor analysis depends on which keywords you choose to analyze. Here are the key points for choosing the right ones.

First, rather than reusing your SEO keywords as they are, think about the natural phrasing users use when they ask AI. In SEO, fragmented keywords such as "good sleep mattress recommended" are common, but in AI search, people ask in full sentences, such as "Please recommend a mattress for a good night's sleep" (both examples are translated from Japanese).

The specific steps for choosing keywords:

• List the jobs (customer problems) related to your core business: Identify the fundamental problems customers want to solve, such as "sleeping well," "relieving lower back pain" or "improving the bedroom environment"
• Imagine how people will ask AI about each job: Come up with several ways users might phrase their questions to AI
• Hypothesize which keywords competitors are strong or weak in: Separate areas where industry leaders are likely to dominate from niche areas where you might have a chance to win
• Prioritize and narrow down what you analyze: Do not try to cover everything at first; start with the keywords that have the biggest business impact

The Jobs-to-be-Done (JTBD) perspective matters here. "When it is cold, some people put on more clothes and others buy a hot coffee": competitors in AI search exist beyond industry boundaries. See also 5 steps to increase your AI mention rate.

Step 2: Check manually in each LLM (ChatGPT/Gemini/Claude)

Once you have chosen your keywords, actually ask each LLM and check the answers. The key point here is to always check on multiple AI platforms.

Each LLM has its own tendencies:

• ChatGPT: Has the most users and is increasingly integrated with web search, so it tends to reflect relatively recent information
• Gemini: Closely tied to Google's search ecosystem, it tends to cite information from sites that Google Search rates highly
• Claude: Strong at analyzing long texts, it tends to give relatively balanced answers
• Perplexity: Shows its cited sources explicitly, so it is easy to see which sources shape the AI's answers

When checking manually, record the following:

• The AI used and its version
• The prompt
• Brand names mentioned in the answer (in order of appearance)
• The context of each brand's mention (recommendation, comparison, warning, etc.)
• Whether your brand was mentioned, and where
• Date and time of the check

Step 3: Calculate and visualize mention share

Once you have collected answer data from each LLM, calculate the mention share. Mention share is a metric that shows, in AI answers for a specific keyword, each brand's count of answers that mention it as a share of the sum of that count across all tracked brands.

How to calculate mention share:

• Ask using multiple prompt patterns for each keyword (recommended: 5 or more)
• For each brand, count the answers from each LLM that mention it
• Calculate each brand's count as a share of the sum of that count across all tracked brands
• Calculate the average across LLMs (ideally a weighted average based on each LLM's share of users)

For visualization, a line chart over time works best. Charting how mention share measured weekly or daily changes lets you see trend shifts at a glance. Bar charts comparing mention share by LLM and pie charts by brand also work well.

For details on how to calculate mention share, see What is mention share?

Step 4: Analyze competitors' strengths and weaknesses

Once you have the mention share data, analyze competing brands' strengths and weaknesses from several angles. Qualitative analysis matters as much as simple mention counts.

Look at the following:

• Volume of mentions: For which keywords do competitors have a high mention share? Which keywords show a large gap compared with your brand?
• Quality of mentions: Are competitors recommended in a positive context? Are they introduced with positive words such as "recommended," "popular" or "highly rated," or in a context such as "be careful" or "there are drawbacks"?
• Consistency of mentions: Are competitors recommended consistently across multiple LLMs? If they are strong in only one LLM, why?
• Position of mentions: Are they introduced at the start of the answer or mentioned in passing near the end? In AI answers too, brands introduced first tend to stick in users' minds
• Trend changes: Is competitors' mention share trending up or down? If it changes suddenly, what is the cause?

Putting these findings together gives you a multidimensional competitor map that shows "which competitor is strong in which keyword area, and on which AI platform."

Step 5: Draw up an action plan

Based on the analysis, draw up a concrete action plan. Typical actions that come out of GEO competitor analysis include:

• Strengthen content: For keyword areas where competitors are mentioned but you are not, create or strengthen highly specialized content
• Improve E-E-A-T (experience, expertise, authoritativeness and trustworthiness): To be recognized by AI as a trusted source, increase expert-reviewed articles, reports based on real data, and citations and recommendations from third parties
• Strengthen PR and media exposure: Increase your exposure in industry media and on news sites, which influences AI training data. This is especially effective for AI that searches in real time, such as Perplexity
• Implement structured data: Implement Schema.org structured data properly on your website so AI can understand your brand information accurately
• Build up reviews: User reviews and word of mouth strongly influence the answers AI generates. Consider initiatives that increase honest, high-quality reviews

Manual vs. tool-based approaches

You can start GEO competitor analysis manually, but once it becomes an ongoing task, the gap with a tool grows large. We compared the two on four dimensions: effort, accuracy, continuity and cost.

What free GEO competitor analysis can and cannot do

If you want to "try it for free first," you can do the following at no cost.

• What you can do: Ask about your main keywords manually in the free versions of ChatGPT, Gemini, Claude and others, and record the brands mentioned in a spreadsheet
• What you can do: Get a rough idea of where you stand now with a one-off check covering a few keywords and a few runs

However, free manual methods have the following limits.

• Limit: AI answers change from day to day, so one-off measurements do not show accurate trends
• Limit: Measuring every day is almost impossible in terms of effort, and the work tends to depend on one person and miss measurements
• Limit: Once you multiply several LLMs × several keywords × time, manual tallying falls apart

In short, free manual checks work for "a first look at where you stand" but not for "ongoing competitor monitoring." A realistic approach is to assess where you stand for free first, then consider automation when you move to full-scale operations. To see how ChatGPT, Gemini and Claude currently answer Japanese users' questions about your brand, contact us.

Tools for GEO competitor analysis compared

Here is a summary of tools for running GEO competitor analysis efficiently. Compare their features, pricing and strengths in the table below.

Pricing and features change over time, so check each vendor's website for the latest details before you choose a tool.

Competitor analysis tips by industry

GEO competitor analysis works differently depending on the industry. Here are the key points for major industries.

Restaurants and food service

The restaurant industry sees a very large number of "recommendation" queries in AI search. For questions such as "recommended lunch spots in the X area" or "Italian restaurants for a date," which restaurants AI recommends has a direct effect on how many customers you attract.

• Keywords to watch: area name × cuisine × occasion (date, business entertaining, family outing, etc.)
• What to analyze: Reviews on Google Maps and ratings on Japanese restaurant review sites such as Tabelog and Retty strongly influence AI answers, so compare your review counts and rating scores with competitors'
• How to differentiate: Publish what sets you apart online, such as your story or your commitment to ingredients, so it is reflected in AI answers

SaaS and IT

In SaaS, queries such as "recommended X tools" and "X comparison" are common, which makes competitor analysis in AI search especially important.

• Keywords to watch: tool category × feature requirements × company size (SMB, enterprise, etc.)
• What to analyze: Ratings in comparison articles and on review sites (such as ITreview, a Japanese software review site, and G2) strongly influence AI recommendations. Also check how thorough competitors' technical documentation is
• How to differentiate: Publish your unique features and concrete customer case studies online, giving AI specific material to recommend you on

E-commerce and retail

In e-commerce, queries tied directly to purchase decisions, such as "recommended X products" and "how to choose X," are important.

• Keywords to watch: product category × use case × user type (beginners, professionals, etc.)
• What to analyze: Reviews on major online marketplaces (Amazon and Rakuten, one of Japan's largest online marketplaces), comparison sites and specialist media influence AI answers. Also check how recommendations differ by price range
• How to differentiate: Communicate your product expertise and brand story so that AI recommends you for your "value," not just in price comparisons

Medical and healthcare

Healthcare is an area where AI is especially careful when it answers (YMYL: Your Money or Your Life). Reliability and expertise carry great weight as criteria for AI recommendations.

• Keywords to watch: symptom × treatment × area (clinic searches)
• What to analyze: The credibility of medical institutions' websites, doctors' track records and citations of academic papers influence AI recommendations. E-E-A-T elements are especially important
• How to differentiate: Focus on initiatives that build credibility, such as content reviewed by specialists, published treatment outcome data and patient testimonials (where Japan's medical advertising rules allow them)

GEO initiatives to pull ahead of competitors

Based on the results of your GEO competitor analysis, here are concrete initiatives to close the gap with competitors and then overtake them.

1. Strengthen comparison content

AI tends to give weight to comparison articles and "top X picks" content in its training data. Create fair, detailed comparison content that includes your own brand, giving AI a source it can easily reference.

The key is not to promote your own brand one-sidedly but to lay out each brand's features against objective comparison criteria. AI tends to trust sources that are more impartial.

2. Improve the quality of brand mentions

It matters not only that your brand name is mentioned but that it is recommended in a positive context. To get there:

• Raise customer satisfaction and build up word of mouth
• Win recommendations from industry media and influencers
• Publish information backed by concrete data and track records
• Create content that directly solves users' problems

3. Optimize for multiple LLMs

If a competitor is strong in only one LLM, a strategy to win in the other LLMs also works. Understand each LLM's characteristics and prioritize initiatives that strengthen your mentions in the LLMs where you are weak.

For example, because Gemini is closely tied to Google's ecosystem, a better standing in Google Search translates directly into stronger mentions in Gemini. Perplexity reflects the latest web information in real time, so regularly updated press releases and blog posts are effective.

4. Find new keywords with Jobs-to-be-Done (JTBD)

This strategy is about finding keyword areas where competitors are thin and winning mention share there first. Use the Jobs-to-be-Done (JTBD) perspective to uncover new keywords beyond the boundaries of your industry.

For example, for the job of "sleeping well," a mattress maker can look beyond "mattress for good sleep" and widen the analysis to related jobs such as "creating a good sleep environment," "a night routine for better sleep" and "relieving stress to sleep better." This uncovers keyword areas that competitors are overlooking.

5. Regular monitoring and PDCA

GEO competitor analysis is not a one-off task. It is important to run a PDCA cycle that monitors regularly and verifies the effect of your initiatives. Track changes in mention share at least weekly, and ideally daily.

Key things to monitor:

• Trends in your own mention share (rising, falling or flat)
• Changes in competitors' mention share (including the emergence of new competitors)
• Sudden changes in a specific LLM (a possible algorithm update)
• Changes before and after an initiative (measuring its effect)

Track competitors' mention share automatically with AIOPulse

AIOPulse lets you automate the GEO competitor analysis described above without the manual work.

Key features of AIOPulse for competitor analysis:

• Automatically sends fixed Japanese-language prompts to three major LLMs (ChatGPT, Gemini and Claude) every day: No more manual checks
• Charts mention share over time automatically: Track daily changes in mention share and see them at a glance in line charts
• Detects and compares competitor mentions automatically: See your mention share side by side with competitors' and spot at a glance where the gaps are
• Analysis by LLM: See which AI platforms you are strong on and where you are weak, platform by platform
• Flexible per-site billing: Plans are set per site, and you can add keywords as you need them. Contact us for pricing

Doing competitor analysis by hand takes at least 1–2 hours per keyword, and doing that every day adds up to a huge cost. With AIOPulse, you just register your keywords: it tracks competitors' mention share in answers to Japanese-language prompts every day, and you can check the dashboard anytime.

Start by finding out where you stand in AI search today. To see how ChatGPT, Gemini and Claude answer Japanese users' questions about your brand, contact us.

You can also learn more about AIOPulse. Starting GEO ahead of your competitors is the first step to securing a competitive advantage in the AI search era.

Frequently asked questions

How is GEO competitor analysis different from SEO competitor analysis?

SEO competitor analysis compares "search engine metrics" such as search rankings, backlinks and domain authority. GEO competitor analysis, by contrast, compares how often and in what context each brand is mentioned (mention share) in the answers that AI such as ChatGPT and Gemini generates. The fundamental difference is that what you evaluate shifts from search results pages to AI answers.

Can I do GEO competitor analysis for free?

For a first look at where you stand, yes: ask questions manually in the free versions of each LLM and record the results in a spreadsheet. However, because AI answers change daily, an automation tool is the realistic choice for tracking trends accurately and measuring every day.

Which LLMs should I use for competitor analysis?

Rather than focusing on just one, we recommend checking across several, such as ChatGPT, Gemini, Claude and Perplexity. Each LLM draws on different sources and has different recommendation tendencies, so comparing several reveals competitors' true strengths and weaknesses.

How often should I measure?

It depends on your goal. As a guideline: a one-off check to see where you stand, weekly to measure the effect of initiatives, and daily for serious competitor monitoring. AI answers fluctuate a lot, so measuring as often as possible and judging by the average of several runs makes your results more accurate.

How is mention share calculated?

It is calculated as "number of answers that mention a brand ÷ sum of that count across all tracked brands × 100." Basing it on answers collected with several prompts and LLMs makes the figure more stable. For details, see What is mention share?

What does a tool automate?

With AIOPulse, sending prompts in Japanese to multiple LLMs every day, detecting brand names in the answers, tallying mention share and charting it over time are all automatic. It fully automates "daily measurement and tallying," the most time-consuming part of the manual approach.

Summary

As AI search spreads, GEO competitor analysis is becoming an essential digital marketing skill. Here are the key points of this article.

• GEO competitor analysis means systematically investigating and comparing "how AI search answers treat your competitors", and its approach is fundamentally different from traditional SEO competitor analysis
• There are three methods: manual checks, prompt design and tools, and it is important to choose among them based on your goals and budget
• The procedure has five steps: keyword selection → checks in each LLM → mention share calculation → strengths and weaknesses analysis → action plan
• Using the quantitative metric of mention share lets you compare competitors based on data rather than gut feeling
• The key points of competitor analysis differ by industry, so you need an approach that reflects your industry's characteristics
• The key to results is continuous monitoring and PDCA, not a one-off analysis

The most important thing in competitor analysis in the AI search era is "taking action." Rather than aiming for a perfect analysis, first understand where you stand and start with small improvements. Manual checks are a fine place to begin. Start your GEO competitor analysis today and get ahead of your competitors.

Automate your GEO competitor analysis, starting today

The standard approach to GEO competitor analysis is to first understand where you stand manually, then move on to continuous monitoring. Still, asking multiple LLMs questions every day and continuing to record and tally the brands they mention is a heavy burden. AIOPulse is a GEO tool that automates this "daily competitor analysis" end to end.

It handles daily Japanese-language prompts to ChatGPT, Gemini and Claude, automatic tallying of competitors' mention share and charts over time, all in one workflow. Contact us for pricing. If you are starting to feel the limits of manual analysis, consider switching to automation.

Ask about AIOPulse's paid plan / Find out first how AI answers Japanese users' questions about your brand

Related articles: What is GEO? A complete guide from the basics | The PDCA cycle for GEO: a complete 2026 guide | What is mention share? How to measure and use it | Measuring the ROI of GEO: a complete 2026 guide