How to improve visibility in AI search with Ane Wiese and Benjamin Thornton @saas.group

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In episode #34 of season 5, Anna Nadeina talks with Ane Wiese, SEO lead at saas.group, and Benjamin Thornton, product marketing specialist at Keyword.com, about Answer Engine Optimization (AEO) – the emerging practice of optimizing for AI-powered search platforms like ChatGPT, Perplexity, and Google’s AI Overviews to improve brand visibility in AI-generated answers.

Ane and Benjamin use AEO (Answer Engine Optimization) as the preferred term because it captures the broader idea of optimizing to appear inside answers generated by AI systems — not only in chat interfaces but in any place an AI model surfaces a synthesized response.

“AEO is a bit broader — it includes any interface where the answer is pulled into an answer engine, not just the chat window.” — Ane Wiese

Key differences from traditional SEO:

• AEO focuses on being included in a short, synthesized answer rather than only driving clicks to a webpage.
• Performance metrics change: ranking and organic traffic remain important but you also need to track mentions, citations and AI visibility.
• Content clarity and precision matter more — every sentence can be parsed and reused by a model.

Core principles that remain (and what’s new)

Google and others have stated that many traditional SEO fundamentals still matter for AEO: page structure, semantics, site architecture, Core Web Vitals and intent matching. At the same time, some priorities shift:

• Semantics and structured content get amplified — the clearer and better-connected your concepts, the easier for LLMs to consume and cite them.
• Brand mentions and the spread of your content across reliable sources matter more: LLMs rely on patterns and co-occurrence, so scale and signal help.
• Product positioning and feature parity can determine inclusion: if your product is labeled in ways LLMs expect (e.g., “keyword research tool”) and actually has the features to match that label, you are more likely to be cited.

Content strategy for AI platforms

Write for clarity, not creativity-first. Ane and Benjamin stressed that LLMs extract and reuse sentences — fluff and ambiguous phrasing reduce your chances of being accurately used. Practical guidance:

• Make paragraphs short and to the point (the community often recommends short, high-value paragraphs similar to featured snippet structure).
• Use clear headings and TL;DRs for quick extraction.
• Include precise terminology and map related concepts across pages so models can understand relationships (think of it as building a semantic web of content).
• Use schema markup where relevant to highlight key facts and data.

Digital PR, link building and brand mentions

Getting cited by the publications and resources LLMs already trust is one of the fastest ways to raise AI visibility. Ane and Benjamin outlined two complementary approaches:

1. Outreach & collaboration: Identify frequently cited articles or authors in the answers you want to rank for, then build partnerships or provide value so your brand gets mentioned in those sources.
2. Create content that becomes a preferred citation: Produce well-researched listicles, comparisons and feature-driven content that LLMs can reliably cite for specific queries (for example, “best rank trackers for SEO agencies”).

Both approaches take time, but they compound: solid SEO content can become the currency for PR exchanges, and PR mentions feed the citation signals AEO systems use.

Product positioning — the small detail that can make a big difference

LLMs often apply an expected definition to product categories. If your product is called a “keyword tool” but lacks a feature commonly associated with that label, AEO systems might exclude you. Benjamin gave a real example: after keyword.com added keyword research capabilities and updated product descriptions across directories and pages, its chances of being cited improved.

Practical checklist for product owners:

• Audit how you describe your product across all public touchpoints (company pages, directories, G2, LinkedIn, job listings).
• When you add a feature, update all those profiles systematically.
• Use consistent vocabulary you want associated with the brand and encourage partners/affiliates to use that language.

How to pick and track prompts (and the measurement challenge)

Unlike Google, most LLM platforms do not expose detailed query data or search volumes tied to specific prompts. That makes AEO measurement trickier. The panel recommends a hybrid approach:

• Think conversationally: craft prompts as a user question rather than a single keyword (e.g., “What are the best rank trackers for SEO agencies?”).
• Create a list of semantically similar prompt variations to track — by intent, use case and industry.
• Use available tools and signals: auto-complete in ChatGPT, trending topics, Bing Copilot’s reasoning breakdown, and keyword databases that now include long-tail query-like terms.
• Track citations frequency: measure how many times a page or URL is cited by an LLM over a 30-day window to estimate demand and visibility trends.
• Watch referral traffic from LLMs in GA4 and Search Console as a behavioral signal.

Benjamin noted that keyword.com built an AI visibility tracker to monitor when and where a brand is mentioned by multiple LLMs — a vital signal while query-level volumes remain unavailable.

Tools and integrations mentioned

• Screaming Frog — for extracting large-scale content and semantic data (has newer features helpful for AEO audits).
• Keyword tracking tools with AI visibility features — to monitor citations across LLMs.
• Bing Copilot — offers some prompt-reasoning insights.
• GA4 / referral tracking — to spot ChatGPT / LLM-driven traffic.

Limitations and risks to keep in mind

LLMs still hallucinate and can surface incorrect or inconsistent information. Key cautions:

• Always expect some degree of factual error; people still need to verify sources for critical topics (health, finance, legal).
• Content that is creative but ambiguous can be misunderstood — make facts and relationships explicit.
• Strategies that worked last month may stop working quickly — these platforms and their integrations change fast.

“One thing that people don’t think about is positioning — if your product doesn’t match the expected features for a label, you might be left out of answers.” — Ane Wiese

Quick hacks and implementation checklist

Short-term tactics you can start with today:

• Optimize the language on your LinkedIn company page, product directories and review pages — update them whenever you ship features.
• Audit top pages for clarity: short paragraphs, TL;DRs, clear headings and schema markup.
• Create or update authoritative listicles/comparison pages that LLMs frequently cite for your target prompts.
• Push scalable brand mentions: brief PR pieces in high-value publications, encourage affiliates to use consistent wording, and include product descriptors in job ads and company bios.
• Track citation frequency across LLMs and monitor referral traffic from ChatGPT / Perplexity in GA4 to measure impact.