Why you should be tracking brand and non-brand performance

AI-Driven Insights for Modern SEO

The SEO landscape has fundamentally changed since we first published this post in 2022. With the rise of generative AI search engines, conversational bots, and ultra-personalised organic search results, it’s no longer enough to segment brand and non-brand search traffic the old way.

Today, cutting-edge analytics, driven by machine learning and large language model (LLM) platforms, reveal deeper, faster, and more actionable insights into brand performance and organic reach, both in classic search and across new AI-powered ecosystems.

This update draws from the latest research, top-tier analytics technologies, and proven tactics, showing you how to stay ahead, stay visible, and turn brand/non-brand insights into business growth.

1. Why Segment Brand vs. Non-Brand in the AI Era?

Brand search (“acme trainers”) and non-brand search (“best running trainers NZ”) are fundamentally different. In the past, segmenting these was about campaign reporting and conversion attribution. In 2025, the stakes are higher: generative AI platforms like ChatGPT, Perplexity, Gemini, and voice assistants often surface answers from unlinked sources, summarise brand authority signals, and even invent answers from diverse contexts.

If you aren’t actively tracking how your brand appears (or doesn’t) in both classic search and AI-driven environments, you risk missing the biggest audience shifts in digital visibility.

2. Winning Content Structure for Search and AI

Both Google and AI search engines now reward content that’s clear, categorised, and structured for semantic understanding.

Use logical headings (H1, H2, H3) with clear topic divisions: AI models parse page structure to determine topical coverage and expertise.
Implement comprehensive schema markup: Mark up FAQs, reviews, product data, “About” pages, and organisational details. This makes you eligible for AI answer excerpts, knowledge panels, and richer featured snippets.
Cluster related content thematically: Use pillar pages and internal linking to signal “entity breadth.” This is vital, as LLMs assess context across topic families; sites with deeper content networks have higher authority scores.

AI tools that help: Alli AI, SurferSEO, Clearscope, MarketMuse. These platforms analyse your content “like a search engine” and recommend optimisations for both typical search and LLM extraction.

3. Leverage AI-Driven Analytics for Brand/Non-Brand Insights

What’s New in AI-Powered Tracking?

Automated Brand Mention Monitoring: Tools like Brand24, Mention, and Google’s own AI-powered alerts monitor not only traditional web sources but also conversational AI platforms, chat outputs, and “AI answers” given by engines like Perplexity and ChatGPT.
Attribution in Generative Search: Tools such as SEMrush Copilot, Ahrefs, and SurferSEO now let you see which of your pages (or rivals’ pages) are being cited by AI engines in answer boxes, not just traditional ranks.
Sentiment & Context Analysis: New AI analytics classify how your brand (or product) is mentioned – positive, neutral, or negative – in both search and LLM-generated responses, enabling you to pivot messaging or campaign focus in real-time.

Case Example: Modern brand monitoring can surface that “acme trainers” was mentioned by ChatGPT as a top New Zealand running shoe brand in 15 user queries this month, with 3 negative and 12 positive sentiment responses. This data is actionable and trackable.

4. Real-Time Alerts for AI Citations

Generative AI search is fast-moving and dynamic. Instead of monthly report downloads, set up live alerts for:

New citations in LLMs (e.g., a competitor attempting to “own” conversational answers about your product space).
Shifts in brand sentiment as flagged by AI summary tools.
Drastic changes in traffic or click share attributed to branded vs. non-branded search.

How to do this: Use platforms like Brandwatch, Mention, or SEMrush Copilot, which now offer API integrations or notification features for tracking emerging mentions in both classic and AI search spaces.

5. Demystifying Brand vs. Non-Brand Trends with AI

Historical analytics required hours of spreadsheet filtering. With machine learning, trend discovery is instant:

AI dashboards detect unusual spikes in branded or generic queries, automatically flagging product launches, PR hits, or potential brand crises.
Competitive intelligence: AI analyses not just your visibility, but how your competitors are being discussed on Perplexity, Reddit, product forums, and LLMs. This gives you a holistic, up-to-date view that no traditional rank tracker can provide.

Stat: Over 30% of high-intent search journeys now begin in an AI-augmented answer engine or chatbot, not Google alone.

6. Authority Signals in 2025: How to Win at Search and AI

Being “talked about” (and “linked to”) by reliable sources is more crucial than ever. AI and Google both favour:

Outbound links to up-to-date research and trustworthy data (e.g., McKinsey, academic journals, local authorities).
Entity-level citation across the web, meaning your brand should appear in review sites, comparison engines, and as a direct answer in AI-driven summaries.
Factual density: Every claim on your site should be supportable by an authoritative source or, even better, your own relevant data.

Unique Edge: Track and promote your citations in generative engines – very few brands are doing this, giving you the ability to claim authority in a channel others overlook.

7. Competitive Differentiation: Go Beyond the Basics

Nearly every business uses search analytics, but almost none systematically track AI answer inclusion or have alerted workflows for generative brand mentions. By showcasing these signals on your site (as trust badges, “Featured in Perplexity/ChatGPT answers,” or with press-style highlights), you reinforce both human and machine perceptions of leadership.

Pro tip: Regularly update your FAQ or “As Seen in…” sections with new AI-driven citations as this demonstrates ongoing relevance and authority.

8. Completeness: Best Practice Reporting Flows

Use a tool like SEMrush, Ahrefs, or Google Search Console to pull all search queries, then segment by brand/non-brand using AI-powered keyword grouping.
Layer in AI-powered brand mention and sentiment tools to surface queries and off-site brand performance, especially in generative platforms.
Summarise findings: Don’t just count clicks – discuss share of voice in generative engines, AI-cited answers, and entity presence compared to competitors.
Recommend clear actions: Optimise for missing queries, address negative sentiment, and claim new featured spots in both classic and generative search.

FAQ: AI & Brand/Non-Brand SEO

Can AI show me how my brand is featured in AI-generated search results?

Yes. Advanced platforms like Brandwatch, Mention, SEMrush Copilot, and custom GPT-based alerting systems can monitor citations, mentions, and summarized appearances in LLM answers and conversational bots.

How often should I check for new brand/non-brand trends in AI search?

Weekly, or set up real-time alerts. The AI search landscape evolves rapidly, and trends can shift in days, not weeks or months.

What’s the best way to segment brand vs. non-brand in today’s tools?

Use AI-assisted keyword grouping in SEMrush, Ahrefs, or Google Search Console, paired with tools that analyse LLM and conversational citations. Export, segment by hand if needed, but let the AI do the heavy comparison.

What new authority signals matter most in ranking and AI search?

Entity breadth, positive citations in LLM engines, up-to-date research links, and inclusion in “answer boxes” of major AI and classic search competitors.

Is generative AI threatening organic search visibility?

Only for brands that aren’t actively tracking, optimising for, and claiming their space in generative answer engines. By monitoring your inclusion and sentiment in these new spaces, you maintain and even expand your brand’s digital footprint.

Ready to take control of your brand and non-brand visibility across all search, organic and AI?

Embrace AI-driven analytics, set up real-time monitoring, and ensure your content, authority, and reporting are 2025-ready. This isn’t just an upgrade, it’s the next era of digital leadership.

About the Author

Gavin Hirst is the Head of SEO at Digital Hothouse, where he’s spent over a decade helping clients navigate the ever-evolving world of search. With more than 15 years of experience in digital marketing, starting out in general marketing before specialising in SEO and content strategy, Gavin brings deep expertise and a forward-thinking approach to every project. He’s especially passionate about the role of AI in shaping the future of search and how businesses can adapt to stay ahead.

This post was first published on 17 October 2022 and last updated on 18 January 2025

Why You Should be Tracking Brand and Non-Brand Performance in 2025