LLM search optimization (AEO)
Optimize your content to appear as a cited source in AI-generated answers from ChatGPT, Perplexity, and Google AI Overviews.
Why this can grow a startup
AI search engines like ChatGPT, Perplexity, and Google AI Overviews synthesize answers from multiple sources rather than ranking pages. Fewer than 10% of sources cited by AI engines overlap with top Google organic results, so traditional SEO alone is insufficient. Brands that earn third-party mentions, maintain fresh content (updated quarterly), and structure pages with clear entity data and citations get cited more often. Zero-click searches now account for 60% of all queries, making AI citation the new front door to discovery. B2B SaaS sites saw AI search traffic grow 127% in just three months in late 2025.
Source-backed example
eMarketer reports fewer than 10% of sources cited in ChatGPT, Gemini, and Copilot rank in top 10 Google organic results — meaning traditional SEO won't guarantee AI visibility. Zero-click searches hit 60% in 2025 (77% on mobile). GEO is now a distinct discipline from SEO.
Source-reported evidence
Source: forbes.com
10% of sources cited in ChatGPT
Attributed to the cited source; GrowthDex has not independently verified it. Use this as context, not as a forecast, benchmark, or recommended target.
Evidence scope: claims and metrics are attributed to the linked source; GrowthDex has not independently replicated the reported result. Check the original context and validate fit before applying it. Read the evidence methodology.
Source discovered: March 19, 2026
When to use it
Use this when SEO is relevant to 0-100, 100-1K and you can run a bounded test with a free budget.
When not to use it
Do not use it as a substitute for customer evidence, a clear owner, or a measurable stop condition. Local platform rules and market behavior still need checking.
How to do it
- Choose one target segment and define the exact next action this tactic should prompt.
- Adapt the tactic to SEO, using evidence from forbes.com as context—not as a promised result.
- Record a baseline for: Qualified search visitors who complete the intended next action. Set a guardrail that would make you pause the test.
- Run a narrow pilot and choose a test window that fits the normal decision or use cycle; do not scale before you have observed the full cycle.
- Compare the signal with its baseline. Scale only if the intended action improves without crossing the guardrail; otherwise revise one variable or stop and record what you learned.
Compare a stack for your situation
Compare source-backed tactics against your product, stage, budget and channel strengths, then choose one experiment to test.
Explore the context
Did you launch this experiment?
Report a launch to help us understand which growth ideas founders put into practice.
Apply this with an operator
Turn isolated search tactics into a crawlable visibility system tied to demand and proof.