AI Visibility Triples in One Month — Here's the Exact Playbook Local Businesses Need

Semrush ran a documented 30-day experiment optimising their own content specifically for LLM (large language model) visibility — meaning optimising to appear in ChatGPT, Perplexity, Claude, and other AI assistant answers rather than just Google search rankings. The result was a 3x increase in referral traffic from AI sources within one month. The experiment is fully documented with before/after data, specific tactics used, and the metrics tracked. This is one of the first public case studies with real numbers on AI search optimisation for a known brand.

The tactics that drove results, in order of impact: (1) adding concise, factual "summary boxes" at the top of key pages that AI can easily extract and cite; (2) using FAQ sections with direct question-and-answer formatting that mirrors how AI queries are phrased; (3) ensuring NAP consistency (Name, Address, Phone) across all citations and directory listings, since AI cross-references multiple sources; (4) building citations on authoritative local directories (Yelp, TripAdvisor, industry-specific sites). The study found that AI assistants heavily weight content that is structured, factual, and consistent across multiple sources.

Local businesses can apply every one of these tactics immediately. A coffee shop can add a summary box to its homepage: "Specialty coffee shop in [city]. Open Mon-Sat 7am-6pm. Known for single-origin espresso and remote-work-friendly space." A salon can add FAQ content: "How long does a balayage take? Typically 3-4 hours." A pet groomer can ensure consistent NAP across Google, Yelp, and their website. These are low-cost, high-impact actions that directly increase the chance of appearing when someone asks an AI assistant for a local recommendation.