See How AI Recommends
Your Brand
AI assistants are the new gatekeepers of product discovery. Linksii gives you a real-time visibility score that measures how often, how prominently, and how positively AI platforms mention your brand when users ask for recommendations.
What the tracker measures
Six core metrics that give you a complete picture of your AI brand presence
Visibility Score
0–100%A composite score measuring how frequently and prominently AI platforms mention your brand across all tracked prompts. Updated daily as new responses are analysed.
Mention Rate
Per promptThe percentage of tracked prompts where your brand appears in the AI response. A 60% mention rate means your brand is referenced in 6 out of every 10 monitored queries.
Sentiment Analysis
Positive / Neutral / NegativeEach brand mention is classified by sentiment. Linksii detects whether the AI platform recommends your brand enthusiastically, neutrally, or with caveats and concerns.
Position Ranking
1st, 2nd, 3rd…When an AI response lists multiple brands, Linksii records your position in that list. Being mentioned first carries more weight than appearing fifth in a recommendation.
Source Citations
URL + credibilityTrack which web sources AI platforms cite when mentioning your brand. Each source is rated for credibility so you understand what content drives your AI visibility.
Competitor Benchmark
Side-by-sideCompare your visibility score, mention rate, and sentiment against up to 10 competitors. See exactly who AI platforms prefer and why.
AI visibility vs. traditional SEO monitoring
Traditional SEO tools were built for a world of ten blue links. AI assistants have changed the game entirely.
Why teams use Linksii for AI visibility tracking
Automated daily tracking
No manual prompting. Linksii runs your tracked queries automatically every day across all platforms and geographies, building a time-series of your AI visibility.
Multi-platform coverage
ChatGPT, Claude, Gemini, and Perplexity each use different data pipelines. Linksii normalises results across all four so you get one unified visibility score.
Actionable gap analysis
Discover the prompts where competitors appear but you do not. Gap analysis turns raw data into a prioritised list of content and PR opportunities.
Funnel-stage mapping
Tag prompts by buyer journey stage — awareness, consideration, decision. See where in the funnel AI platforms recommend your brand most effectively.
Historical trend data
Track how your visibility score changes week over week. Correlate improvements with content launches, PR coverage, or product updates.
Team collaboration
Share dashboards with your team. Pro plans include up to 5 seats; Enterprise plans include unlimited seats for large marketing, SEO, and PR teams.
Explore platform-specific tracking
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What an AI visibility score actually measures
An AI visibility score is a composite. The simplest version is just mention rate — how often your brand appears across a tracked prompt set. That number is useful but thin; it answers “am I in the conversation?” without answering the questions that actually predict pipeline. A defensible visibility score combines four signals into a single index.
Mention rate. The percentage of tracked prompts where your brand appears anywhere in the response, across all four AI platforms. This is the floor — if mention rate is below 20% on category-level prompts, no other metric matters until that's fixed. Most healthy brands sit between 30% and 70% on category queries; below 20% indicates fundamental visibility work.
Position weighting. Where you appear in the response matters as much as whether you appear. A brand mentioned first in 50% of responses outperforms a brand mentioned sixth in 80% — click-through and retention both correlate strongly with position. Visibility scores that don't weight position miss this signal entirely.
Sentiment and framing. Being recommended favourably matters more than being mentioned generically. A brand described as “the leading option for X” outperforms a brand described as “another option in the space”, even at identical mention rates. Sentiment analysis on the actual response language captures this.
Stage-of-journey segmentation. Awareness-stage prompts (“what is X”) and decision-stage prompts (“best X for Y use case”) behave completely differently. Most brands score significantly higher on awareness than on decision; the gap between them is one of the most diagnostic numbers in AI visibility. Decision-stage scores predict pipeline; awareness scores predict brand recognition over time.
Cross-platform consistency. The fifth signal is whether you score similarly across ChatGPT, Claude, Gemini, and Perplexity. A brand strong on one platform and weak on the others is exposed to platform-specific risk and has platform-specific work to do. A brand consistent across all four is more durable in AI search.
Different tracking tools weight these signals differently. Linksii's Brand Visibility Score is a normalised 0–100 composite of all five, calibrated against the brands tracked across the system. The composite is what you watch over time; the per-component breakdown tells you which specific dimension to act on next.
How to use AI visibility tracking data
The patterns that turn tracking from a vanity dashboard into a marketing operating discipline.
Treat the decision-stage gap as your primary metric
Most brands have a respectable awareness mention rate and a poor decision-stage one. The gap between them is the single most diagnostic number you can track. Pipeline impact is driven by decision-stage visibility, not awareness, so this is where your monitoring program should focus first when the gap is wide.
Identify your top three losing prompts and treat them like a content brief
Filter the data to prompts where you don't appear and a competitor does. Pick the three with highest commercial intent. Each becomes a content brief: what does the buyer want to know, what does the competitor say, what would a better answer look like. Ship one piece of content per prompt over the next quarter.
Audit the source citations driving competitor visibility
Every AI response includes (explicitly or implicitly) the sources it's leaning on. Pull the list of citation domains AI references when competitors are recommended in your category. Those domains are your outreach target list — guest content, listings, reviews, podcast appearances. Five new citations on cluster domains move the needle further than fifty on irrelevant ones.
Track per-country if revenue is geographically distributed
AI brand visibility varies significantly by country and language. A brand strong in English-language responses can be invisible in German or Japanese. If revenue concentration crosses borders, multi-country tracking is necessary — the playbook then includes localised content and citations in each priority market.
Wire alerts on visibility drops and competitor surges
Without alerts, monitoring becomes a quarterly review artefact. Slack or email alerts on a visibility drop of more than 10 points, or a competitor surge of more than 15, keep the loop tight enough that you act in days rather than quarters. The half-life of an actionable AI visibility shift is short — alerting is the difference between catching it and discovering it.
Tie the monthly visibility review to a concrete content/PR backlog
Each month, the tracking data should produce one or two concrete items added to the content or PR backlog. Without this, monitoring drifts into pure observation. The discipline is: data review → pick one priority gap → ship one piece of work → measure impact next month. Repeated, this is the compounding loop.
Frequently asked questions
How is the AI visibility score calculated?
The visibility score combines mention rate (how often your brand appears), position ranking (where in the response you appear), sentiment (how positively the AI frames your brand), and platform coverage (how many AI platforms mention you). The score is weighted to reflect the relative importance of each factor and normalised to a 0-100 scale.
How does an AI visibility tracker differ from Google Search Console?
Google Search Console tracks your rankings in traditional search results. An AI visibility tracker monitors what happens when users ask AI assistants for recommendations. These are fundamentally different channels: search results show links, while AI assistants give direct answers. Both matter, but AI-driven answers are growing rapidly.
Can I export visibility data for reporting?
Yes. Linksii supports CSV exports on all plans. Enterprise plans include API access and a Looker Studio connector so you can integrate AI visibility data into your existing reporting stack.
How many prompts should I track?
Most brands start with 10-25 prompts covering their core product categories and competitor comparison queries. As you discover gaps, you can expand. Starter plans include 25 prompts, Pro plans include 100, and Enterprise plans support 300 or more.
Does the tracker work for any industry?
Yes. Linksii works for any brand that could be recommended by AI assistants — SaaS, e-commerce, professional services, hospitality, finance, healthcare, and more. If people ask AI platforms about your category, Linksii can track your visibility.
What happens when AI platforms update their models?
Model updates can change how AI platforms recommend brands. Linksii's daily tracking captures these shifts immediately. You will see changes in your visibility score and can investigate which prompts were affected and how.
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