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Surface-level comparison content that only praises your own product is distrusted by both humans and LLMs. Creating non-biased pages that honestly acknowledge competitor strengths signals credibility and provides the quality, balanced information that AI models are more likely to trust and cite.
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To shape the narrative presented by AI, valuable content previously hidden behind lead-gen forms (like PDFs and whitepapers) must be made publicly accessible. LLMs cannot consume gated content, so making it public and structuring it for them is crucial for your value propositions to be accurately represented.
To make product and service pages AEO-friendly, marketers should add specific structural elements. Including a 'TLDR' section, an accordion-style FAQ based on buyer questions, and direct competitor comparison content helps LLMs easily parse and surface key information.
Use interactive 'self-selection' tools on your website that guide prospects to the best solution for them, even if it's not yours. By occasionally recommending a competitor or different product type, you establish your brand as the most trusted and honest resource in the space.
AI search is the new overpowered marketing channel, with traffic converting up to 17x higher than Google. To get featured, invest heavily in comprehensive "alternatives to [competitor]" and "[your product] vs [competitor]" pages, as these are the bottom-funnel queries AI models cite most often.
Instead of gating its valuable review data like traditional analyst firms, G2 strategically chose to syndicate it and make it available to LLMs. This ensures G2 remains a trusted, cited source within AI-generated answers, maintaining brand influence and relevance where buyers are now making decisions.
Do not blindly trust an LLM's evaluation scores. The biggest mistake is showing stakeholders metrics that don't match their perception of product quality. To build trust, first hand-label a sample of data with binary outcomes (good/bad), then compare the LLM judge's scores against these human labels to ensure agreement before deploying the eval.
To improve your content's standing with AI models, don't just use AI to write. Research what sources tools like Perplexity and ChatGPT cite on a topic. Then, incorporate and reference those same sources in your article. This signals value and helps your content become a preferred source for AI.
Instead of general analysis, feed your AI a defined customer persona (e.g., "Growth Gabby") and ask it to evaluate a competitor's website copy from that specific perspective. This uncovers messaging weaknesses that directly relate to your target audience's concerns, like complexity or pricing.
Unlike traditional SEO where the top link wins, in LLMs, the answer is a summary of many sources. The brand mentioned most frequently across all citations is most likely to be recommended, even if it's not the top-ranked source. This changes the strategy from ranking to saturation.
To increase the chances of being cited in AI search, structure content in formats that directly answer user questions. FAQs and benchmark/evaluation tools perform exceptionally well because they provide clear, structured answers that LLMs can easily parse and present to users conducting research.
