Challenges: The brokerage's buyers research extensively before contacting an agent. That research was shifting away from traditional Google and into AI engines like ChatGPT, Perplexity, and Google's AI Overview. The client had strong local presence but near-zero visibility in AI-generated answers. The search landscape was dominated by national portals: Zillow, Redfin, LandWatch with massive domain authority and content budgets.

The Problem: Competing on traditional SEO alone wasn't moving the needle. Every high-intent search query "Utah land for sale," "recreational land for sale"  was returning results dominated by national platforms with years of domain authority. The client was invisible in the places buyers were increasingly going to make decisions.

The Approach: The strategy centered on Answer Engine Optimization, structuring content so AI models would surface the client as the authoritative answer for high-intent land search queries. This required a different content architecture than traditional SEO: entity-building, semantic clarity, and structured authority signals rather than keyword volume. Alongside AEO, paid media was restructured across Meta, Google, TikTok, and YouTube with a focus on reducing CPL while scaling to $70K+/month in ad spend. Lead-to-tour conversion systems were rebuilt from 6.8% to 19% through improved marketing-to-sales handoff.

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Conclusion: The client now ranks #1 in AI search for "Recreational Land for Sale" against RE/MAX, Sotheby's, Coldwell Banker, and Keller Williams and #4 for "Utah Land for Sale" against Zillow, Redfin, and LandWatch. LLM visibility reached 39.4%, AI search share of voice hit 32%, organic keywords grew 160% in one quarter, and revenue increased 52% YoY. The result is a compounding advantage: buyers encounter the brand in an AI answer, see a retargeted ad, and the trust transfer accelerates the close.