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People expect answers from search — whether that’s Google’s blue links or an AI assistant summarizing results. The problem is double: teams still report on classic rankings while large language models (LLMs) are quietly steering discovery and referral traffic. That mismatch creates friction — missed opportunities, fractured reporting, and arguments about where to invest. Enter Semrush One: a single product that combines keyword-level SEO metrics and new AI-search signals so teams can measure and act on total visibility across search engines and LLMs. The solution helps close the reporting gap, surface where AI finds (and mentions) your brand, and gives tactical steps to improve how and when models surface your content.
What Semrush One actually is
Semrush One is Semrush’s unified offering that merges traditional SEO tooling with new AI-search monitoring and recommendations — tracking visibility in Google plus several AI platforms (ChatGPT, Gemini, Perplexity, and others), surfacing an AI visibility score, prompt-level mentions, and cross-channel reporting. The product launched publicly at the end of October 2025 as Semrush repositioned its suite around “total visibility” for both search engines and LLMs.
Why this matters now
Search behavior is shifting. Users increasingly get answers from AI overviews and chat assistants, not just SERP results; brands that aren’t present in those answers lose visibility.
Reporting is fragmented. SEO teams track rank and traffic; PR and content teams may monitor brand mentions; few teams connect those dots into a single narrative about discovery → conversion.
Signal types differ. LLMs cite community sources, knowledge panels, and high-trust content differently from Google’s link-and-query signals; understanding those signals is now part of search strategy. Semrush One promises a single workflow to see both kinds of signals.
What Semrush One includes
Core features (as announced):
AI visibility tracking: how often LLMs mention your brand and how that compares to competitors.
Prompt monitoring: discover the questions people ask LLMs related to your business.
Competitive AI research: identify visibility gaps where competitors are being cited more in AI answers.
Website AI readiness audits: technical checks to help LLMs crawl and cite your content.
Unified reporting: combine SEO and AI metrics in one stakeholder-friendly report.
Weekly data updates and large LLM prompt coverage (100M+ prompts reported).
These items are designed to let teams move from “Did an LLM mention us?” to “How do we improve the likelihood it will?” — and to connect that activity back to outcomes.
A real example: what the landing page shows (and what to read between the lines)
Semrush highlights a case where Coalition Technologies reportedly saw a 429% increase in AI referral traffic, credited in part to Semrush’s AI visibility tools. That’s an eye-catching number — useful as an example of the kind of lift possible when a site is surfaced by AI engines — but it’s one case, not a guarantee for everyone. Use case studies like this to form hypotheses, then benchmark your own performance and traffic sources before drawing conclusions.
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A practical 90-day playbook for early adopters
Why this is new: many writeups only list features. Below is a hands-on sequence you can apply immediately to turn the Semrush One signals into measurable gains.
Days 1–14 — Baseline and discovery
Run an AI visibility audit for your brand and top 3 competitors. Capture: AI visibility score, brand mentions, top prompts.
Map the top prompts to existing content: which pages answer those prompts now? Where are gaps?
Days 15–45 — Quick wins
Update 5–10 pages that already rank but appear thinly in AI answers. Add fact blocks, structured data, and one-sentence answer snippets that directly map to discovered prompts.
Publish 2 short “answer” pages or FAQ snippets targeted to the exact prompts LLMs report. These should be factual, cited, and easy to parse by crawlers and models.
Days 46–90 — Scale and report
Build an “AI discovery” dashboard (use Semrush One’s unified reporting) that shows AI mentions → organic traffic → conversion events.
Run an experiment: pick 10 prompts, optimize content for those prompts, and compare AI mentions and referral traffic vs. a control group.
Add a governance rule: every new product or help doc includes a short canonical “prompt answer” section optimized for LLM discovery.
KPIs to track: AI visibility score, monthly AI mentions, AI-driven referral sessions, prompt share of voice, and conversions from AI referrals.
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Risks and caveats
Correlation ≠ causation. An increase in AI mentions doesn’t always mean more revenue; track conversions.
Data freshness and transparency. Semrush reports weekly updates; for real-time crises or PR spikes you’ll still need other monitoring systems.
Content quality still matters. Trying to game prompts with low-quality “answer pages” can backfire; focus on factual, well-sourced content.
What this means for teams and budgets
SEO + content + PR must coordinate. SEO teams should share prompt data with content and PR to prioritize authoritative content creation and fact corrections where LLMs cite outdated sources.
A new line item in reporting. Expect executives to ask for “AI visibility” alongside organic traffic and paid ROI; Semrush One is positioned to provide that single source of truth.
Early advantage for brands that act. The product frames speed as an advantage (“Be found in AI before the competition”); that matters most in categories where timely, factual answers are competitive (tech docs, health, finance).
Key Takeaways
Semrush One unifies SEO and AI-search signals so teams can measure “total visibility” across Google and LLMs.
AI visibility score and prompt monitoring turn opaque LLM mentions into actionable data.
Immediate playbook: baseline → optimize existing pages → publish prompt-targeted answers → measure conversions.
Watch for over-reliance on raw mentions; measure downstream impact (traffic → conversions).
Coordination across SEO, content, and PR is now essential to influence both search and AI discovery.
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FAQs — People Also Ask
Q: What is the Semrush One AI visibility score?
A: It’s a benchmark (0–100) summarizing your brand’s presence in AI outputs — how often LLMs mention your brand relative to competitors — updated weekly via Semrush’s dataset. Use it as a comparative indicator, not a sole success metric.
Q: Which LLMs and AI platforms does Semrush One monitor?
A: Public announcements list ChatGPT, Gemini, Perplexity and broader LLM coverage; Semrush also reports a large dataset of prompts (100M+ relevant prompts cited on the product page).
What Challenge Does Generative AI Face with Respect to Data?
Q: Will Semrush One replace traditional SEO tracking?
A: No — it’s complementary. Traditional ranking and backlink signals still matter; Semrush One adds a new layer (AI discovery) that teams should track alongside classic SEO metrics.
Q: How should small teams prioritize Semrush One signals?
A: Start with the prompts that map closely to your commercial pages or knowledge resources. Optimize a small set, measure results, then scale based on proven gains.
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Conclusion
This new tool is a logical next step for teams that want a single place to see how they appear in both classic SERPs and AI-driven discovery. It doesn’t replace content quality or brand building, but it gives new signals — AI mentions, prompt tracking, and a consolidated visibility metric — that planners can use to set priorities and justify investment. If your role touches content, SEO, or brand measurement, try a focused 90-day experiment: measure where LLMs currently cite you, optimize a set of pages to answer those prompts, and track whether mentions turn into measurable traffic and conversions. Want to test it? Semrush One launched publicly on October 29, 2025 and offers trial options.
Try Semrush One’s trial to capture your baseline AI visibility, and subscribe to SmashingApps for step-by-step experiments, templates, and case studies on turning AI mentions into real traffic.
Sources (official)
Semrush One (Semrush). Semrush
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