Last week, Fire&Spark’s founder Dale Bertrand attended the first-ever Generative Engine Optimization (GEO) Conference in Austin, Texas. The GEO Conference focused on strategies for optimizing websites for generative search, as well as AI trends and insights that all marketers should know.
As there have been many recent advancements with generative AI search, many marketers are wondering how they should prepare their websites to gain AI visibility. Although the GEO Conference sessions weren’t recorded, we took detailed notes and are sharing a recap of what leading experts in the GEO space had to say about adapting your marketing strategy for generative search.
Why GEO Matters
Generative Engine Optimization (GEO) is still in its early stages, which makes it particularly difficult to execute effectively. Whereas SEO strategies have been refined over decades with well-understood rules and ranking signals, GEO targets rapidly evolving AI search platforms with far less predictability. Despite these challenges, GEO offers a compelling upside:
- Higher intent traffic: Users who click through from AI-generated answers are often further along in the decision-making process. AI systems have already synthesized context for them, so by the time they get to your website they are informed and ready to convert.
- Stronger brand visibility: GEO helps ensure your brand appears accurately and authoritatively in AI responses, especially critical when AI answers might otherwise hallucinate or misrepresent information.
- Control over AI narratives: GEO gives marketers the tools to influence how their brand is perceived by AI.
However, the consensus at the conference was clear: GEO isn’t for everyone. It may not be worth the investment for low-volume verticals, B2B brands focused on first-touch conversions, or companies with limited content resources. It’s important for brands not just to ride the wave of GEO investment, but to strategically understand its limitations and evaluate how it aligns with their unique products and services.
New GEO Strategies Are Emerging: Here’s What Works
While proven GEO playbooks are still taking shape, here are some actionable strategies shared by conference speakers and panelists:
1. Think in Semantic Space, Not Keyword Space
Search engines rank links, while AI models synthesize answers from content. To be included, your content must activate the right parts of an LLM’s latent space. That means:
- Covering a topic deeply and from multiple angles
- Including both general and niche information
- Writing for all experience levels (from beginner to expert)
2. “Citation Building” Is the New Link Building
LLMs cite sources from Reddit, Wikipedia, forums, and trusted niche sites — not just high-DA media publications. To be included in generative answers, your content needs to appear on the kinds of pages AI deems credible.
Tip: Publish bios, case studies, or thought leadership content on high-authority platforms, conferences, and podcasts where AI scrapes data.
3. Use AI for Research, Not Just Writing
GEO isn’t just about being included in AI results; it’s about understanding how AI sees your brand. Use AI tools to:
- Grade your content’s coverage and completeness
- Identify adjacent concepts you might be missing
- Analyze which sources are most often cited for your target queries
You can also test prompts with different personas to see how AI personalizes answers across demographics and intents.
4. Inject Human Vibrancy into Your Content
AI models are explicitly trained to detect and filter out low-value or “robotic” content. Add human elements, such as customer stories, expert opinions, real-life use cases, and detailed reviews, to make your content feel authentic and avoid triggering the “AI-written detector.”
5. Mine Niche Forums and Reddit for Content Ideas
Reddit and online communities are rich sources for nuanced, long-tail content ideas. Tools like Reddit APIs or scraping tools can help uncover real-world phrasing, pain points, and feature requests, all of which feed semantically rich content.
6. Embrace Structured Content and Clear Hierarchy
AI models interpret page structure as part of semantic understanding. Use a strict heading hierarchy (H1 > H2 > H3), include summary statements, and clearly define sections. This helps LLMs parse the relationships between concepts and surface your content more reliably.
7. Track the Right Metrics (Beyond Clicks)
Since GEO traffic can’t always be directly attributed, shift your focus to incremental lift and qualitative feedback. Use “How did you hear about us?” fields, analyze AI referral traffic in GA4, and compare downstream behavior across channels.
8. Don’t Just Optimize for AI: Serve Humans First
Despite the name, GEO isn’t about creating content for AI. It’s about ensuring your human-centered content is visible to AI. The most resilient strategy is creating genuinely helpful, comprehensive content that AI models will increasingly be trained to recognize and reward.
Case Study Spotlight: Wei Zheng’s High-Volume, High-Intent GEO Strategy
One of the most compelling, and revealing, case studies at the GEO Conference came from Wei Zheng, who shared how she developed a GEO strategy for a large retailer with an extensive product catalog. Her talk stood out because it illuminated the practical contradictions GEO marketers face today.
At first glance, some advice from the conference seemed paradoxical:
- “Optimize for humans, not AI” – yet GEO’s goal is to appear in AI-generated results.
- “AI won’t recommend AI-generated content” – yet many successful case studies involved AI-generated pages.
- “Create content for your customers” – yet the best results came from producing massive volumes of narrowly targeted content.
Wei embraced these tensions and built a strategy that worked for both AI and human audiences. Using detailed product data, she created hundreds of ultra-specific pages answering granular queries like “Best watch for automatic timezone detection when flying westward from Europe.” These long-tail, semantically rich landing pages were designed to serve both as AI-friendly citations and high-converting pages for users referred by platforms like ChatGPT.
Key Takeaways from Wei’s Approach:
- Ultra-specific content scales well in high-volume markets: Her strategy proved that niche, long-tail pages are more likely to be cited in AI answers, especially in competitive consumer markets.
- Useful product insights can come from Reddit and forums: Not all content needs to come from the product catalog. Wei mined Reddit threads, Facebook groups, and forums to enrich content with real user insights.
- AI values specificity over generality: Pages that clearly addressed highly specific user questions had a better chance of being cited in AI-generated responses.
- GEO demands more scale than SEO: Where SEO might rely on tens of high-quality pages, GEO may require hundreds or thousands of strategically targeted ones to gain traction in generative platforms.
Wei’s case study served as a powerful reminder: you can’t approach GEO like traditional SEO. To succeed, marketers must embrace a new kind of content discipline rooted in semantic understanding and large-scale execution.
Final Takeaways: The Future of GEO
The GEO Conference made one thing clear: generative search is already reshaping the way users discover brands. While the tactics are still evolving, early movers are finding success by:
- Investing in content depth and specificity
- Understanding how LLMs evaluate content
- Using AI to both generate and evaluate content
- Building visibility on pages and platforms that AI trusts
For most brands, optimizing for ChatGPT and Google’s AI Overviews should be the short-term priority. As AI continues to shape consumer behavior, GEO will only become more essential to content strategy and digital visibility.
