Competitor AI visibility analysis: what to track

Competitor AI visibility analysis is the practice of measuring how often rival brands appear and get cited in AI-generated answers from ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews. It surfaces the queries, publications, and topics driving their share of voice, and the gaps you can credibly fill. AI-generated answers now influence a large and growing share of how buyers research products, which means the brands that understand this layer first will define their category’s default answer.

Here is how to set up competitor monitoring and use it to improve your own AI visibility.

Setting up competitive monitoring

Identify your competitors

AI search rewards three distinct sets of competitors. Track all three, because the brand outranking you in Google rarely matches the brand the model cites.

Direct competitors: companies selling the same product to the same buyer. These are the brands your prospects are comparing you against in “[Category] alternatives” and “X vs Y” prompts.

Content competitors: publishers, analysts, and educators creating content in your topic areas. AI models often cite their explainers over vendor pages, which is why they matter even when they do not sell anything competitive.

AI visibility competitors: brands that consistently appear in model responses for your core prompts, even if they are not direct competitors. These are the incumbents in the model’s training data and retrieval index. They set the ceiling for your share of voice.

Once you have a list, configure your primary brand and competitors in Bourd so every run tracks mentions automatically. See Setting up brands and competitors.

Choose your tracking queries

Build a set of queries (in Bourd these are called prompts) that cover the full buyer journey. Aim for 15-30 in your first set, then expand from there.

Product and service queries:

• “Best [your product category]”
• “How to choose [your product type]”
• “[Your industry] solutions for [use case]”

Informational queries:

• “[Your topic area] best practices”
• “What is [your expertise area]?”
• “[Your industry] trends in 2026”

Comparison queries:

• “[Competitor A] vs [Competitor B]”
• “Alternatives to [major competitor]”
• “[Product category] comparison”

For prompt templates and the framework we recommend, see Writing effective prompts and Creating and managing prompts.

Key metrics to track

1. Mention frequency

What to measure:

• How often each competitor appears in AI responses
• Which queries trigger competitor mentions
• Frequency trends over time

Analysis approach:

Mention Rate = (Responses mentioning the brand / Total responses analyzed) × 100

Track weekly if you are actively publishing or running PR; monthly is enough for steady-state monitoring. Bourd exposes Mention Rate as a headline KPI on the Reports dashboard. See Viewing results and analytics.

2. Share of voice

What to measure:

• Your percentage of total industry mentions
• Competitor percentages within your category
• Changes in relative positioning

Calculation:

Share of Voice = (Your mentions / Total mentions of all tracked brands) × 100

Share of Voice is the single most useful competitive metric because it controls for prompt volume. A rising Mention Rate can hide a falling Share of Voice if the whole category is growing faster than you are. Bourd calculates Share of Voice automatically across your configured brand and competitor set. See Viewing results and analytics.

3. Citation quality and context

Not every mention is worth the same. A brand cited as the primary recommendation with a linked source is worth far more than a brand listed fourth in a pros-and-cons comparison.

Evaluation criteria:

• Position: Primary mention vs. secondary reference
• Context: Positive, neutral, or negative framing
• Detail level: Brief mention vs. detailed discussion
• Authority: Cited as expert vs. example

Scoring system (1-5 scale):

• 5: Primary recommendation with positive framing
• 4: Prominent mention with neutral or positive context
• 3: Standard mention among several options
• 2: Brief reference or secondary mention
• 1: Mentioned negatively or as a counter-example

Equally important is understanding which sources the model cited to generate that mention. Bourd aggregates every citation across your runs, grouped by domain and by URL path, so you can see which publications AI models treat as authoritative in your category. See Analyzing citations.

4. Topic coverage analysis

What to track:

• Which topics competitors own
• Content gaps where no competitor has strong presence
• Emerging topics with low competition

Gap identification process:

1. Map all industry topics and subtopics
2. Track competitor mentions across topic areas
3. Identify underrepresented topics
4. Prioritize gaps based on business relevance

The fastest version of this workflow inside Bourd: filter citations by the URLs where competitors are mentioned but your brand is not. Those are the articles AI models are using to answer questions about your category without you. See the content gap workflow in Analyzing citations.

Competitive analysis framework

Monthly competitor report

Executive summary:

• Overall Share of Voice changes
• Key competitive movements
• Emerging threats and opportunities

Detailed findings:

• Mention frequency by competitor
• Citation quality scores
• Topic coverage analysis
• Notable quotes or mention examples

Strategic recommendations:

• Content gaps to address
• Competitive response strategies
• Emerging opportunity areas

To produce this report on a reliable cadence, schedule your prompt set to run weekly or monthly against every model you care about. See Scheduling and automation.

Competitive content audit

Analyze competitor content that gets cited:

• Content formats that perform well
• Topics that generate citations
• Writing styles and structures
• Source attribution patterns

Content gap identification:

• Topics where competitors are weak
• Content formats underutilized
• Audience questions not being answered
• Emerging trends not covered

Response strategies

When competitors own the category

Direct response:

• Create superior content on the same topics
• Address gaps or weaknesses in competitor coverage
• Provide more recent or accurate information
• Offer different perspectives or approaches

Flanking strategies:

• Focus on related but underserved topics
• Target different audience segments
• Develop unique angles or frameworks
• Build authority in adjacent areas

When you’re losing ground

Immediate actions:

• Audit your existing content for accuracy and completeness
• Update outdated information and statistics
• Improve content structure and readability
• Strengthen your source citations and authority signals

Long-term improvements:

• Develop deeper subject matter expertise
• Build relationships with authoritative sources
• Create deeper, more authoritative content
• Improve your overall digital footprint

Tools and automation

Manual tracking methods

• Systematic query testing across AI platforms
• Spreadsheet-based tracking and analysis
• Regular screenshot documentation
• Qualitative assessment of mentions

Manual tracking is fine for 10 prompts across 2 models. It stops scaling at around 30 prompts × 4 models × weekly: roughly 480 responses a month to read, score, and trend by hand.

Automated solutions

Dedicated GEO platforms run your prompts across every major model, extract citations and competitor mentions, and track Share of Voice trends over time. Bourd does this for ChatGPT, Claude, Perplexity, Gemini, Grok, and Meta out of the box. For a side-by-side of how Bourd compares to Profound, Peec AI, Scrunch, PromptWatch, and Passionfruit, see the AEO tool comparison hub. If you are starting from scratch, the quickest path is:

1. Set up your brand and competitors
2. Create your first set of prompts
3. Run a baseline analysis
4. Schedule it to repeat weekly or monthly
5. Review the Reports dashboard and Citations page

Turning analysis into action

Content strategy adjustments

• Prioritize topics where competitors are weak
• Develop content that directly challenges competitor positioning
• Create deep resources that become go-to references
• Build thought leadership in emerging areas

Distribution strategy

• Focus on platforms where competitors have less presence
• Build relationships with sources that AI systems trust
• Improve your content’s discoverability and accessibility
• Enhance your brand’s authoritative signals

Measuring success

Track the impact of your competitive response strategies:

• Changes in your Mention Rate and Share of Voice
• Improvements in citation quality and context
• Growth in topic coverage breadth
• Overall AI visibility improvements

The goal is not to match competitors prompt-for-prompt. It is to find the topics, prompts, and models where you can credibly be the default answer, and invest there.

Run this loop monthly. The citations shift as models update their training data, as retrieval indexes re-crawl, and as competitors publish. A strategy that worked last quarter may already be losing ground.

Frequently asked questions

What is competitor AI visibility analysis?

Competitor AI visibility analysis is the process of measuring how often rival brands appear in responses from AI search tools like ChatGPT, Perplexity, Gemini, and Google AI Overviews. It covers mention frequency, share of voice, citation quality, and the source URLs that models rely on to generate their answers.

How is AI visibility different from traditional SEO rankings?

Traditional SEO measures where your page ranks on a results page. AI visibility measures whether your brand gets named, described, and cited in the answer itself. A page can rank fifth in Google and still be the source AI Overviews cites, or rank first and never be mentioned by ChatGPT at all.

How often should I analyze competitor AI visibility?

Monthly is the baseline for most teams. Move to weekly if you are actively publishing, running PR, or tracking a product launch. Anything less frequent than monthly will miss the drift caused by model updates and competitor content shipping.

Which AI platforms should I monitor?

Prioritize ChatGPT, Google AI Overviews, Perplexity, Gemini, and Claude. Add Grok and Meta if your audience skews toward their user bases. Model choice matters: a brand strong in ChatGPT can be nearly invisible in Perplexity because the two systems pull from different source sets.

How many prompts should I track?

Start with 15-30 prompts that span product, informational, and comparison queries. Expand from there as you identify which prompts drive meaningful traffic or surface meaningful competitive signal. Most teams end up tracking somewhere between 50 and 150 prompts once their coverage is mature.

Next steps

• Set up your brand and competitors in Bourd
• Write your first monitoring prompts
• Analyze citation sources to find content gaps
• Compare Bourd to other AEO/GEO tools
• See Bourd pricing and credit math