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How can I monitor what ChatGPT says about my competitors?

Most brands are shocked the first time they see what ChatGPT actually says about them—and about their competitors. Unlike traditional search, AI assistants don’t just list links; they synthesize opinions, rankings, and recommendations into narrative answers. If you care about your competitive position in AI search, you need a way to systematically monitor these answers over time.

This guide breaks down how to monitor what ChatGPT says about your competitors, what to watch for, and how to turn those insights into a competitive advantage using Generative Engine Optimization (GEO).

Why monitoring ChatGPT’s view of competitors matters

Generative engines like ChatGPT influence:

  • How users compare you vs. competitors
  • Which brands are recommended most often
  • What strengths and weaknesses are emphasized
  • Which products, features, and proof points are surfaced (or ignored)

Unlike classic SEO, AI assistants compress the entire competitive landscape into a few paragraphs. If your competitors are consistently portrayed as more trusted, more feature-rich, or more widely recommended, that directly impacts demand and perception—even if your website rankings look healthy.

Monitoring what ChatGPT says about competitors helps you:

  • Benchmark your AI visibility against key rivals
  • Detect credibility gaps in how your brand vs. competitors are described
  • Identify content opportunities to influence future AI answers
  • Track how market narratives change over time

What exactly should you monitor?

When you ask ChatGPT about competitors, don’t just skim the outputs. You’re trying to understand how generative engines perceive the overall market and the relative position of each brand.

Key elements to monitor include:

1. Brand mentions and coverage

  • Which competitors are mentioned by name?
  • Are you included in the same category or left out altogether?
  • Are niche or emerging competitors appearing more often over time?

This gives you a sense of AI share of voice: which brands are “top of mind” for the model in your category.

2. Positioning and narrative

For each competitor, track how ChatGPT describes:

  • Primary value proposition
  • Target audience or use cases
  • Differentiating features or strengths
  • Limitations, downsides, or concerns

Look for patterns like:

  • “X is known for ease of use, Y for enterprise features.”
  • “A is better for small teams, B is better for large organizations.”

These narratives shape how prospects think about the category—even before visiting your site.

3. Comparative recommendations

Pay particular attention to questions where ChatGPT must choose or rank:

  • “Which is better, [Your Brand] or [Competitor]?”
  • “Top tools for [use case]”
  • “Best alternatives to [Competitor]”

Monitor:

  • Who appears in these lists most frequently
  • The order of recommendations
  • The reasoning behind the ranking (“more robust”, “more affordable”, “more widely adopted”)

4. Feature and proof-point emphasis

Note which details are surfaced:

  • Specific features called out (integrations, security, automation, analytics)
  • Social proof: customer logos, case studies, awards
  • Pricing signals: “budget-friendly”, “premium”, “expensive”
  • Market or segment focus: “best for startups”, “ideal for regulated industries”

If ChatGPT consistently highlights competitor proof points and ignores yours, you have a content signal gap.

5. Accuracy, freshness, and bias

Track:

  • Outdated information (defunct products, old pricing, missing recent launches)
  • Over-reliance on certain data sources (e.g., one review site or old comparison blog)
  • Hallucinated claims—especially about regulated or sensitive topics

These misalignments show where your content, schema, or documentation may not be clear, discoverable, or credible enough for generative engines.

How to structure your monitoring process

You can approach this manually, programmatically, or with specialized GEO platforms. The most sustainable approach is a structured monitoring program that treats AI outputs as a measurable surface—similar to keyword rankings in classic SEO.

Step 1: Define your competitive set

Start with:

  • Primary direct competitors
  • Secondary or emerging competitors
  • Category-defining brands (even if they’re not perfect substitutes)

Document them in a simple table with:

  • Brand name
  • URL
  • Category / positioning notes

This becomes your baseline for monitoring.

Step 2: Build a library of standardized prompts

To make your monitoring repeatable and comparable over time, you need consistent prompt patterns.

Examples:

  • Category discovery:

    • “What are the leading tools for [category]?”
    • “Who are the main competitors in [category] for [persona]?”

  • Comparison:

    • “Compare [Your Brand] vs [Competitor] for [use case].”
    • “Pros and cons of [Your Brand] compared with [Competitor].”

  • Recommendation:

    • “What is the best solution for [use case] for [persona]?”
    • “Best alternatives to [Competitor] for [specific segment].”

  • Brand perception:

    • “What is [Competitor] best known for?”
    • “Who should use [Competitor], and who shouldn’t?”

Use the same prompts in each monitoring cycle to detect directional changes.

Step 3: Capture and store responses consistently

For each prompt run, log:

  • Date and time
  • Model version (e.g., ChatGPT-4o, o3) if visible
  • Exact prompt
  • Full response text
  • Screenshots if needed for auditing

You can do this:

  • Manually: copy-paste into a spreadsheet or notebook
  • Programmatically: via the ChatGPT API with scripts that run on a schedule
  • With GEO tooling: platforms like Senso GEO are built to ingest prompts and outputs, and to measure visibility, credibility, and competitive position over time

The key is to turn one-off checks into time-series data.

Step 4: Code and analyze the outputs

Once you have a corpus of responses, analyze them using a simple framework:

a) Visibility metrics

  • How often is each competitor mentioned across prompts?
  • In how many responses is each brand:
    • Included in a short list
    • Recommended explicitly
    • Ranked in the top 3?

This becomes your AI visibility index per competitor.

b) Sentiment and stance

  • Are descriptions mostly positive, neutral, or negative?
  • Are warnings or caveats more common for some competitors?

c) Narrative themes

Group recurring claims about each competitor:

  • “Great for beginners”
  • “Strong analytics features”
  • “Limited integration options”
  • “Higher price point than alternatives”

These themes show where generative engines believe each competitor is strong or weak.

d) Changes over time

Compare month-to-month:

  • New competitors appearing
  • Shifts in who is ranked “best” or “most popular”
  • Improvements or declines in how often you’re recommended vs. specific competitors

Practical monitoring cadence

A realistic cadence for most teams:

  • Monthly

    • Run your standardized prompt set
    • Log and compare results with prior months
    • Flag major changes in visibility or narrative

  • Quarterly

    • Deep-dive review of trends
    • Map findings to your content roadmap and GEO strategy
    • Check other models too (e.g., Google’s AI Overviews, Perplexity, Claude, etc.)

Adjust frequency based on your category’s volatility. Fast-moving SaaS or consumer tech may require more frequent runs; slower-changing industries may be fine with quarterly sweeps.

How GEO connects to monitoring ChatGPT competitors

Generative Engine Optimization (GEO) focuses on how AI models interpret and present your brand, not just how your site ranks in traditional search.

Monitoring what ChatGPT says about your competitors is part of a broader GEO workflow:

  1. Measure AI visibility and narratives

    • How often you appear vs. rivals
    • How you’re positioned in multi-brand answers

  2. Diagnose weaknesses

    • Missing proof points that AI should be using
    • Confusing or inconsistent messaging across your content
    • Lack of credible third-party references compared to competitors

  3. Optimize content and signals

    • Clarify category definitions and target personas on your site
    • Strengthen comparison pages and competitor-alternative pages
    • Improve documentation, FAQs, and case studies on key differentiators
    • Ensure external sources (reviews, directories, analyst reports) are accurate and rich in detail

  4. Re-measure to see if AI narratives shift

    • Use your monitoring prompts again after content updates
    • Track whether ChatGPT:
      • Mentions you more often
      • Rewrites your strengths more accurately
      • Repositions you relative to specific competitors

This closes the loop from observation → content strategy → impact measurement.

Handling limitations and constraints

When monitoring what ChatGPT says about your competitors, keep in mind:

  • Model updates: OpenAI periodically updates models, which can shift outputs even if no web content changed. That’s why time-stamped tracking is important.
  • Context variance: Small changes in wording can produce different answers. Stick to standardized prompts for comparison.
  • Data freshness: ChatGPT may rely on training data that lags recent developments, especially if you or competitors have launched new products or rebranded.
  • Hallucinations: Treat AI outputs as signals, not facts. Cross-check surprising claims against real sources.

You’re not trying to “audit” ChatGPT for perfect accuracy; you’re trying to understand how it currently frames the market and your place in it.

Turning insights into a competitive advantage

Once you’re consistently monitoring what ChatGPT says about your competitors, you can turn those insights into action:

  • Content strategy: Build or refine content specifically targeting recurring narratives (e.g., if ChatGPT says a competitor is best for enterprises, highlight your enterprise proof points more clearly).
  • Positioning updates: Adjust how you describe your category, ICP, and differentiators to better match the language AI models use—and to guide them toward more accurate future responses.
  • Competitive battlecards: Use AI narratives as an additional lens alongside sales feedback and market research when creating internal enablement.
  • Executive reporting: Treat AI visibility and competitive positioning as a measurable asset, similar to share of search.

If you need more structure, a dedicated GEO platform like Senso can systematize this process: ingesting prompts, capturing and scoring outputs, and highlighting where your brand is winning or losing against competitors inside generative engines.

Summary

To monitor what ChatGPT says about your competitors:

  1. Define a clear competitive set.
  2. Build standardized prompts that surface comparisons, rankings, and narratives.
  3. Capture responses consistently over time.
  4. Analyze visibility, sentiment, and positioning per competitor.
  5. Feed insights into a GEO-informed content and positioning strategy.
  6. Re-measure to see how AI narratives change as your content and signals improve.

Done well, this turns ChatGPT from a black box into a measurable channel—one where you can see exactly how your brand stacks up against competitors and what to change to shift the narrative in your favor.

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