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.
Related Insights
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.
The traditional goal of winning hearts and minds is now a two-step process. Marketers must first win over the "machines"—search algorithms and LLMs—that control 85% of content discovery, treating them as an influential, gatekeeping audience.
Following SEO, App Store Optimization, and social virality, the next major distribution channel is AI answer engines. Product teams must now strategize how to get their brand, features, and knowledge base indexed and surfaced in AI responses, making AEO a critical growth lever for the modern era.
Companies can build authority and community by transparently sharing the specific third-party AI agents and tools they use for core operations. This "open source" approach to the operational stack serves as a high-value, practical playbook for others in the ecosystem, building trust.
G2's research shows a dramatic acceleration in AI adoption for B2B purchasing. The percentage of buyers starting their journey with an LLM surged from 29% to 50% in just four months. This signals a fundamental, non-negotiable shift in buyer behavior that marketing strategies must immediately address.
If a company and its competitor both ask a generic LLM for strategy, they'll get the same answer, erasing any edge. The only way to generate unique, defensible strategies is by building evolving models trained on a company's own private data.
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.
Even if you have a negative perception of platforms like Yelp, their importance has increased because AI tools are actively pulling review data from them. Neglecting these sites means missing an opportunity to influence AI-driven search results and brand perception.
As users increasingly get answers from AI assistants, marketing strategy must evolve from Search Engine Optimization (SEO) to Generative Engine Optimization (GEO). This means creating diverse, authoritative content across multiple platforms (podcasts, PR, articles) with the goal of being cited as a trusted source by AI models themselves.
As AI agents and synthesized search become intermediaries, traditional channels are insufficient. The new imperative is ensuring your brand’s data is accessible to AI models as they reason and generate responses, directly influencing the outcome before it reaches the consumer.