Visibility You Cannot Measure
Your brand is being mentioned, recommended or ignored by AI platforms every day and most businesses have no idea which. Traditional analytics tools were not built for this. Google Analytics tells you nothing about how ChatGPT or Perplexity respond when someone asks about your industry or services.
Structured LLM Monitoring
Priority Pixels tracks your brand presence across ChatGPT, Gemini, Copilot and Perplexity using systematic prompt testing and response analysis. We monitor how AI platforms describe your business, which competitors they recommend instead and where your content gets cited or overlooked. Learn more about our complete AI SEO services.
Actionable Intelligence
Tracking alone is not enough. We turn LLM performance data into specific content and technical recommendations that improve how AI platforms represent your brand. Every report identifies what to fix, what to create and what to reinforce so your visibility improves month on month.
AI Platforms We Optimise For
Our LLM Tracking Services
Brand Mention Tracking Across ChatGPT, Gemini, Copilot and Perplexity
We run structured prompt queries across all major LLM platforms to track when, how and in what context your brand gets mentioned. This includes monitoring competitor mentions, identifying which prompts trigger your brand as a recommendation and flagging instances where AI platforms give inaccurate information about your business.
Competitor Visibility Analysis in AI Search Results
Understanding where competitors appear and you do not is the fastest route to improvement. We benchmark your LLM visibility against direct competitors across industry-specific queries, tracking shifts in recommendation patterns and identifying content gaps that give rivals an advantage in AI-generated responses.
Citation Source Tracking and Content Attribution Analysis
When AI platforms cite sources in their responses, knowing whether your content makes the list matters. We track which of your pages get cited, which competitor pages get chosen instead and what content characteristics drive citation selection across different LLM platforms.
Prompt Pattern Research and Query Intelligence
The way people ask questions in AI platforms differs from traditional search queries. We research the prompt patterns your target audience actually uses, identify high-value query categories where you should be visible and track how LLM responses evolve as these platforms update their models.
Monthly Performance Reporting with Clear Recommendations
Every month you receive a report showing your LLM visibility trend, brand mention accuracy, competitor positioning and specific actions to take. No vanity metrics. Each recommendation ties back to a measurable improvement in how AI platforms represent your business to potential customers.
Content Optimisation Guided by LLM Performance Data
Tracking data is only useful if it drives action. We use LLM performance insights to guide content creation, restructuring and technical optimisation. If an AI platform consistently recommends a competitor for a query you should own, we identify exactly what content needs to change and why.
Our AI SEO Case Studies
See how our answer engine optimisation work has helped B2B businesses appear in AI-generated responses across ChatGPT, Perplexity and voice search platforms.
The team behind your LLM performance tracking
LLM tracking isn’t just a dashboard. It’s the difference between guessing where AI search visibility is moving and acting on what’s actually happening. The team that runs tracking for your account also runs the work that responds to it. You’re not handed off to an analyst with no context.
Cara Vallance
Content Lead
Cara turns tracking data into content priorities. Citation share trends, query-level visibility data, competitive positioning and the prompts your content is getting picked for versus the ones it isn't feed into what gets briefed next, so the work responds to what the data is actually surfacing.
Owen Lewis
Senior Web Developer
Owen runs the tracking infrastructure. Citation capture across ChatGPT, Perplexity, Copilot and Gemini, log file analysis for AI agent crawls, third-party tracking integrations and the data pipelines that feed our reporting platform are his to build and maintain.
Monica Johnson
Senior Designer
Monica designs how the tracking gets presented. Dashboard layout, data visualisation choices and the way complex AI visibility data renders cleanly for clients who don't want a wall of numbers get decided at her stage. Your reporting reads like a document, not a database export.
Jess Pearce
Digital Marketing Administrator
Jess keeps tracking visible to your team. She runs monthly review meetings, handles ad-hoc reporting requests, manages briefing handovers between the tracking work and the content or technical work that responds to it and keeps the review schedule on the calendar.
Tracking Built to Read at a Glance
LLM visibility data is only useful if you can act on it. Every Priority Pixels client on our tracking service gets access to our branded reporting platform that holds citation data per LLM-powered tool, query-level visibility broken down by prompt language, competitive citation share against the brands actually showing up alongside (or instead of) you and the trend lines that say whether the work is winning ground week on week.
Filter by tool, by query cluster, by competitive set. Compare citation share against named competitors on the queries that drive qualified pipeline. Every month we schedule a call to walk through the tracking together. What’s moved, what hasn’t and what the next round of content, technical or design work should respond to. Tracking without action is wasted data, so the reporting always feeds into the roadmap.
Sectors We Work With
You cannot improve what you cannot measure. AI search visibility is harder to track than traditional rankings, but the signals are there for those who know where to look. We monitor your presence across ChatGPT, Claude, Perplexity, Google AI Overviews and Bing Chat across sectors with their own query patterns.
B2B
B2B buyers query AI search for vendor shortlists, product comparisons and category overviews. We track your share of voice across these queries, monitor sentiment in AI-generated answers and report the citation patterns shaping how buyers perceive your business.
Technology, IT & SaaS
SaaS buyers ask AI search for product recommendations, alternatives and feature comparisons. We track your visibility across these queries, monitor citation depth in comparison answers and report the LLM signals that show whether your product surfaces at decision stage.
Healthcare
Healthcare AI search results carry regulatory weight and patient impact. We track your visibility across patient queries, monitor sentiment in AI-generated health answers and report the citation patterns that show whether your practice surfaces at research stage.
Shipping & Maritime
Maritime AI search queries are sparse but high-intent. We track your visibility across technical queries, monitor citation depth in niche maritime answers and report the LLM signals that show whether your business surfaces in a sector with thin AI training data.
Construction
Construction AI search queries cover project types, regional providers and specification questions. We track your visibility across these queries, monitor citation patterns in AI-generated construction answers and report the LLM signals shaping buyer perception across project stages.
Professional Services
Professional services AI search queries lean on named-practice recommendations, specialism queries and regulated terms. We track your visibility across these queries, monitor citation patterns in AI-generated advisory answers and report the LLM signals that show how your practice surfaces.
How We Track and Improve LLM Performance
LLM performance tracking requires a structured methodology because AI platforms do not provide analytics dashboards or visibility reports. We have built our own monitoring framework that systematically tests how these platforms respond to queries relevant to your business, tracks changes over time and converts the data into actionable improvements.
Baseline Audit and Platform Mapping
Before we can improve anything, we need to know where you stand. We run an initial audit across ChatGPT, Gemini, Copilot and Perplexity using queries your target audience would actually ask. This establishes your baseline visibility, identifies brand accuracy issues and maps which competitors currently dominate the AI responses in your space.
Prompt Library Development and Testing Framework
We build a library of prompts tailored to your industry, services and target audience. These are tested systematically across all platforms on a recurring schedule. The framework captures response content, citation sources, competitor mentions and sentiment so we can track meaningful changes rather than relying on one-off spot checks.
Data Analysis and Trend Identification
Raw data from LLM monitoring gets analysed for patterns. We identify which content changes correlate with improved visibility, which platform model updates affected your positioning and where emerging query patterns represent new opportunities. This analysis separates meaningful trends from noise so recommendations are grounded in evidence.
Content and Technical Recommendations
Every tracking cycle produces specific recommendations. These might include creating new content to fill gaps AI platforms currently fill with competitor information, restructuring existing pages to improve citation likelihood or updating factual claims that LLMs are currently getting wrong about your business. Each recommendation includes priority, expected impact and implementation guidance.
Ongoing Monitoring and Performance Reporting
LLM visibility is not static. Platform model updates, competitor content changes and shifts in user behaviour all affect how AI tools respond to queries about your business. Our ongoing monitoring catches these changes early so you can respond before visibility drops. Monthly reports track progress against baseline, highlight wins and set priorities for the next cycle.
LLM Performance Tracking FAQs
What is LLM performance tracking?
LLM performance tracking monitors how AI platforms like ChatGPT, Gemini, Copilot and Perplexity respond when users ask questions relevant to your business. It measures whether your brand gets mentioned, how accurately it is described, which competitors appear instead and whether your content gets cited as a source. Traditional SEO tools do not capture this data.
Which AI platforms do you track?
We monitor ChatGPT, Google Gemini, Microsoft Copilot and Perplexity as standard. These four platforms represent the majority of AI-assisted search behaviour. If your audience uses additional platforms relevant to your industry, we can extend monitoring to cover those as well.
How often do you run LLM tracking reports?
We run monitoring on a monthly cycle as standard, with reporting delivered alongside specific recommendations for the next period. For businesses in fast-moving sectors or during active content campaigns, we can increase frequency to fortnightly. The key is consistency so trends become visible over time.
Can you fix inaccurate information about our business in AI responses?
Yes, though it is an indirect process. AI platforms pull information from publicly available sources. If an LLM gives inaccurate information about your business, we identify the source content causing the issue and work to correct, update or create authoritative content that these platforms will use in future model updates. Results typically improve within one to two model refresh cycles.
How is LLM tracking different from traditional SEO reporting?
Traditional SEO reporting measures rankings, clicks and impressions in search engines. LLM tracking measures something entirely different: whether AI platforms recommend, mention or cite your business when users ask relevant questions. A company can rank number one on Google and be completely invisible in ChatGPT. Both matter, but they require different monitoring approaches.
What kind of businesses benefit most from LLM performance tracking?
B2B organisations, professional services firms, healthcare providers and technology companies see the most value because their target audiences increasingly use AI platforms to research suppliers, compare services and shortlist providers. If your sales cycle involves a research phase where potential customers gather information before making contact, LLM visibility directly affects your pipeline.
Our Technology Partners
Our AI SEO News
How AI is reshaping search, from generative engine optimisation and answer engine visibility to AI-driven content strategy.
AI Search and Professional Services: How LLMs Are Changing Client Research
The way prospective clients find law firms, accountancy practices and consultancies is shifting. Where a business owner might once have asked a colleague for a recommendation or typed a query into Google, a growing number are turning to AI tools like ChatGPT, Perplexity, Microsoft Copilot and Google’s AI Overviews to research their options. These tools […]
