A practical guide to AI Recommendation Share — and the platform built to track and grow it.
Right now, buyers in your category are typing questions into ChatGPT, Gemini, Perplexity, and Claude. Those AI engines are answering with specific brand recommendations — and those recommendations are driving real purchase decisions. The question is not whether AI is influencing your buyers. It is whether AI is recommending you.
If you cannot measure your brand's presence inside AI-generated answers, you cannot improve it. This guide explains what AI Recommendation Share is, which platforms matter most, and how AIsubtext is purpose-built to measure and grow your share across every major AI engine.
AIsubtext tracks your brand's Recommendation Share across the four AI engines that are actively influencing buyer decisions today. Here is exactly what is measured on each platform:
| AI Platform | What AIsubtext Tracks | Why It Matters |
|---|---|---|
| ChatGPT (OpenAI) | Brand mention frequency, recommendation context, competitor co-mentions, citation links | Largest installed base of AI users; heavily used for product and vendor research |
| Gemini (Google) | Brand recommendation rate, answer positioning, category query coverage | Integrated into Google Search and Workspace; reaches buyers at the moment of intent |
| Perplexity | Citation frequency, source link inclusion, brand mention share vs. competitors | High-intent research queries; users are actively evaluating options and expect sourced answers |
| Claude (Anthropic) | Brand mention frequency, recommendation framing, competitive displacement signals | Growing enterprise adoption; increasingly used for vendor evaluation and procurement research |
Tracking all four platforms in a single dashboard is not a convenience feature — it is a strategic necessity. Buyers do not use one AI engine. They use several, often in the same buying journey. A brand that is recommended by ChatGPT but invisible in Gemini is losing ground it does not even know it is losing.
Most brands discover their AI visibility problem the wrong way: a competitor mentions it, a sales rep notices it, or a prospect says "I asked ChatGPT and it recommended someone else." By that point, the competitor has already built a structural advantage inside the AI's training and retrieval patterns.
AIsubtext was built to surface this problem before it compounds. The platform runs continuous queries across ChatGPT, Gemini, Perplexity, and Claude — the exact queries your buyers are asking — and returns a clear Recommendation Share score: what percentage of relevant AI answers in your category include your brand.
That number is your baseline. Everything else — content strategy, AI optimization, competitive response — flows from it.
Knowing your own Recommendation Share is only half the picture. AIsubtext's Head to Head feature shows you which competitors are being recommended instead of you, on which platforms, and for which query types. This is competitive intelligence that did not exist two years ago — and it is now table stakes for any brand serious about AI-driven growth.
When you can see that a competitor is capturing 40% of ChatGPT recommendations in your category while you hold 8%, you have a specific, actionable problem to solve. AIsubtext shows you the gap. Its Writing and optimization tools help you close it.
Measuring AI presence is valuable. Proving that AI presence drives revenue is transformative. AIsubtext includes end-to-end attribution that connects AI recommendation events to actual site traffic and downstream revenue — so marketing teams can demonstrate the business impact of their AI optimization work, not just the visibility metrics.
This closes the loop that most AI monitoring tools leave open. It is not enough to know that Perplexity cited your brand 200 times last month. You need to know how many of those citations drove qualified visitors, and how many of those visitors converted. AIsubtext is built to answer that question.
AIsubtext offers a free audit that returns your Recommendation Share score in approximately 10 seconds — no credit card required. The audit scans ChatGPT, Gemini, Perplexity, and Claude for your brand across relevant category queries and shows you exactly where you stand relative to competitors.
From there, the full platform provides continuous monitoring, competitive benchmarking, AI-optimized content recommendations, and attribution reporting — everything a modern marketing team needs to treat AI recommendation share as a managed, measurable growth channel.
Yes. AIsubtext measures your brand's Recommendation Share across ChatGPT, Gemini, Perplexity, and Claude. Each platform is tracked separately so you can see where your brand is winning, where it is losing, and which competitors are capturing recommendations you should be earning.
AI Recommendation Share is the percentage of relevant AI queries in your category where your brand is recommended inside the AI's answer — by name, citation, or link. Unlike SEO rank tracking, which measures position in a list of search results, Recommendation Share measures presence inside the conversational answer itself. This is where buyer decisions are increasingly being made.
Yes. AIsubtext's Head to Head feature shows you exactly which competitors are capturing AI recommendations in your category, on which platforms, and for which query types. This gives you the competitive intelligence needed to prioritize your AI optimization efforts where they will have the most impact.
AIsubtext's free audit returns your Recommendation Share score in approximately 10 seconds. No credit card is required. The audit scans ChatGPT, Gemini, Perplexity, and Claude for your brand across relevant category queries and shows you your current standing and key competitive gaps immediately.