Yoast AI Brand Insights (2025): What the New AI-Answer Visibility Tool Means for SEO and Brand Teams

Updated on 2025-10-02

Yoast just entered the “AI search visibility” arena with AI Brand Insights, a beta feature packaged in Yoast SEO AI+. The tool tracks whether and how your brand shows up inside AI-generated answers across popular assistants, aggregates sentiment and citations, and benchmarks you against competitors. For teams struggling to quantify brand presence in AI responses—and to connect those insights to practical content actions—this is a timely development.

Change log

• 2025-10-02: Initial publication; confirmed beta launch and initial supported surfaces (ChatGPT, Perplexity, Gemini) and pricing.

1) What launched—and why it matters right now

Yoast announced on October 1, 2025 that AI Brand Insights is entering beta within the Yoast SEO AI+ package, with capabilities covering brand mentions in AI-generated answers, sentiment analysis, citation sources, trend monitoring, and competitor benchmarking, per the official announcement on the Yoast site: Yoast AI Brand Insights beta (Oct 1, 2025).

Pricing and access are listed on the product page, which notes a browser-based experience via MyYoast and defines the composite KPI: an “AI visibility index: A score out of one hundred that blends mentions, ranking, citations, and sentiment.” As of publication, pricing is “$29.90/month, billed annually ($358.80 plus VAT),” according to the Yoast SEO AI+ product page (2025).

Independent confirmation is early but emerging; Search Engine Journal’s coverage on October 2, 2025 frames the release as a new visibility tool focused on AI answers—see Search Engine Journal’s launch coverage (Oct 2, 2025).

Why this matters: as AI assistants intermediate more user journeys, brands need a way to measure presence and sentiment where links and clicks are not guaranteed. A directional, repeatable index plus concrete citation insight can help teams triage where to shore up authoritative sources and clarify brand narratives.

2) How “AI visibility” is measured in Yoast’s model

Yoast’s help documentation describes an onboarding flow: add your brand and location, generate and refine a query set, then run an analysis that typically completes in around five minutes before you review visibility, sentiment, citations, and competitor ranks—see the official guide: Yoast’s “How to use AI Brand Insights” (2025).

Key measurement components you’ll see in the dashboard:

• AI Visibility Index (0–100): A blended score of mentions, ranking, citations, and sentiment. Yoast publicly discloses the components but not the weighting formula (treat as directional).
• Mentions and ranking: Whether your brand appears in AI answers for selected queries, and how it stacks up among competitors.
• Sentiment: Positive/neutral/negative patterns, with shifts over time.
• Citations: The sources LLMs reference when mentioning your brand.
• Competitor benchmarking: Comparative presence and sentiment across your defined peer set.

Supported AI surfaces at launch are repeatedly referenced as tools like ChatGPT, Perplexity, and Gemini across Yoast’s materials. Notably absent (as of Oct 2, 2025) is explicit support for Google’s AI Overviews or Microsoft’s Copilot; treat these as out of scope until confirmed by Yoast.

If you’re used to composite SEO metrics, it can help to analogize this to a visibility score. For background on how blended indices work in traditional SEO, see our explainer on the search visibility score and its impact on SEO performance.

3) From dashboard to outcomes: an operational playbook

Below is a pragmatic loop I’ve used with brands exploring AI-answer visibility. It aligns with Yoast’s workflow while focusing on actions that influence inclusion, sentiment, and citations.

1. Measure and baseline

• Define query sets by funnel stage (awareness/problem vs product/brand) and by product/category lines.
• Establish baselines: AI Visibility Index, mention rate, sentiment distribution, citation domains, and competitor ranks.
• Tag queries for business priority so shifts map to revenue-relevant areas.

2. Diagnose gaps and opportunities

• “Not found” queries: Review which domains AI tools cite for these topics. Are they government standards, top-tier media, industry rating sites, or vendor docs? This hints at the evidence you need.
• Negative or muddled sentiment: Pinpoint phrases and cited sources driving the tone. Draft factual clarifications or publish corrected guidance.

3. Improve inclusion, citations, and sentiment

• Elevate canonical explainers: Publish or refresh concise, evidence-rich pages with updated dates, clear facts, and strong author E‑E‑A‑T. Use Organization and (where appropriate) FAQ schema judiciously.
• Build evidence density: Add original data, checklists, and comparison matrices that LLMs can cite easily.
• Earn authoritative citations: Run targeted digital PR to publications and aggregators AI tools frequently reference (e.g., standards bodies, reputable industry analyses), focusing on clarity and verifiability.
• Guide discovery: Consider implementing llms.txt to curate which pages LLMs should discover first—Search Engine Land describes it as a “treasure map” for AI in their llms.txt explainer (2025).

4. Monitor and report

• Re-run weekly for priority clusters; monthly for wider sets. Track changes in the AI Visibility Index, sentiment, and citation mix.
• Correlate movements to brand KPIs like branded search volume and direct traffic, noting that causality will be directional rather than absolute.

Teams can operationalize these steps with streamlined content production. For example, QuickCreator helps teams produce and update evidence-rich pages and push to WordPress in one click, aligning content updates with what Yoast surfaces in its dashboards. Disclosure: QuickCreator is our product.

For a practical walkthrough of planning, generating, and optimizing AI-assisted content in a repeatable way, see our step-by-step AI content workflow.

4) Limitations and risk framing (read before piloting)

• Beta coverage breadth: As of Oct 2, 2025, Yoast’s pages reference ChatGPT, Perplexity, and Gemini. There’s no explicit claim of coverage for Google AI Overviews or Microsoft Copilot; treat those as not included until stated by Yoast.
• Proprietary index methodology: Components of the AI Visibility Index are known, but weights are undisclosed. Use the score directionally, with emphasis on component metrics.
• Output variability: AI answers can change frequently based on model updates and prompts. Expect volatility; focus on trends rather than single-run readings.
• Data collection constraints: Terms-of-service and platform behaviors may evolve; check Yoast’s docs for updates over time.

5) Is this worth a pilot? A quick decision checklist

• Do we have clear business-priority query clusters (by funnel stage and product line) to monitor?
• Can we allocate at least 1–2 hours weekly to review changes and 1–2 content updates per month to act on findings?
• Do we have designated “canonical explainer” pages we can enrich with evidence and schema?
• Are we set up for targeted digital PR to earn citations from sources AI tools tend to trust?
• Do we have a remediation SOP for misinformation or negative sentiment (who drafts, who approves, what turnaround)?

If you can answer “yes” to most of the above, a 60–90 day pilot can produce meaningful learnings.

Mini glossary

• AI Visibility Index: Yoast’s composite score (0–100) blending mentions, ranking, citations, and sentiment. Defined on the Yoast SEO AI+ product page (2025).
• AI citations: The sources AI tools reference in their answers. These are signals of trust and evidence, not the same as backlinks.
• llms.txt: A site-level file proposing guidance to AI crawlers about what to ingest first. See the industry framing in Search Engine Land’s llms.txt explainer (2025).

AI citations vs backlinks: how they differ

What to watch next (and how we’ll update)

• Surface expansion: We’ll monitor whether Google AI Overviews or Microsoft Copilot support is added.
• Methodology clarity: Any public notes on AI Visibility Index weighting.
• Packaging/pricing changes: Adjustments to Yoast SEO AI+ tiers.

Bookmark this piece; we will update it as Yoast expands documentation and coverage. For broader discovery tactics beyond classic search, you can also review our practical guide to mastering Google Discover optimization.

Sources and further reading

• Yoast’s formal launch overview: Yoast AI Brand Insights beta (Oct 1, 2025)
• Pricing and index definition: Yoast SEO AI+ product page (2025)
• Onboarding and runtime: Yoast’s “How to use AI Brand Insights” (2025)
• Third-party coverage: Search Engine Journal’s launch coverage (Oct 2, 2025)
• Discovery guidance concept: Search Engine Land’s llms.txt explainer (2025)

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Forward look: Expect rapid iteration here. As AI assistants play a larger role in discovery and decision journeys, tying a directional AI visibility metric to an operational content workflow is a smart hedge. If you’re setting up that workflow now, a light, repeatable cadence—and the discipline to publish crisp, evidence-dense pages—will matter more than any single score. Teams already using QuickCreator can fold these reviews into their monthly optimization cycles and push updates to WordPress with minimal overhead.