Adapting Veterinary SEO Strategies For AI Search Requires Familiar Foundations And New Signal Tracking

As search patterns move toward AI-driven discovery, many local businesses are experiencing a roller coaster of organic traffic. A visibility gap has opened between well-resourced corporate operators and independent practices, and it comes down to how each side is showing up in AI-generated recommendations. Large corporations dominate AI citations through sheer scale of content and structured data, even when their internal execution runs into the corporate silos slowing down their search strategy. Independent organizations working to close the gap tend to combine solid technical SEO with the authentic customer signals that make a smaller business legible to an LLM.

Samantha Quinones, Founder and Chief Visibility Architect of Paw & Prosper, built her career running global enterprise SEO for giants like Arrow Electronics and IHS Markit. Today, she brings that enterprise playbook to a highly specialized niche. She helps independent veterinary clinics, animal shelters, and pet wellness brands navigate local search to help them keep a strong presence in large language models.

"Marketing teams can easily get overstimulated by all the noise around AI, but the foundational elements are still what we traditionally call technical SEO. We’re adding another layer so LLMs can understand and surface the content," says Quinones. The additional layer she describes runs on the same signals SEO practitioners have used for years, applied to the way LLM agents parse the web. Structured data, schema markup, clear entity definitions, and consistent Name, Address, and Phone records are the mechanical inputs the AI systems parse to determine what the business is and what it does. Because Google now uses AI assistants to place routine phone calls to verify local businesses, the precision requirement extends beyond the digital layer.

Emotion as the AI differentiator

Once the technical foundation is in place, the differentiator becomes the emotional signal a business generates through its customer relationships. Quinones' specific observation is that pet wellness is one of the categories where customer emotion drives decisions ahead of product features, and the AI systems now reading review corpora pick that emotional signal up when they decide which local operators to surface. "With pet owners, they're wearing their heart on their sleeve," Quinones says. "Their emotions are driving their decisions more so than deciding what color shoes to buy."

The extension of that observation is that appearing in AI results is only half the work. The sentiment attached to those mentions determines whether the recommendation converts, and customer reviews are what the AI systems weigh most heavily when they interpret how a brand is perceived. "The sentiment that chats are giving back about how your company is perceived is huge," Quinones notes. "Beyond simply appearing in ChatGPT results, the goal is to actively influence the sentiment of those brand mentions."

The tactical response Quinones runs is a straightforward pairing of FAQ-structured content with patient stories that carry emotional weight. Her execution rule for the pet wellness vertical draws on marketing wisdom she treats as unchanged by the arrival of AI. "When all else fails, include puppies or babies," Quinones says. "Audiences always want to hear a success story about a pet they've been following, or feel like they're making an impact by sharing that story." The other half of Quinones' approach is human oversight of the tools themselves. The strategy has to be intelligible enough that she can walk a client through it without hiding behind the technology. "I take the time to really understand the strategy myself. It's about making sure you understand the flow of what your AI tools are doing."

From snapshot to sustained execution

Measurement work is worth doing now that the discoverability gap between operators has grown. Quinones points to a recent study finding three corporate-owned vet chains under a single parent company accounted for roughly a third of veterinarian AI citations, which she reads as a structural advantage LLMs give operators with the largest data footprints. Independent practices with substantive expertise often stay invisible to the AI systems because their signal density isn't the same as a corporate chain's. Closing the gap comes down to sustained execution on foundational signals. "I want to speak up for those 80% independent veterinarian clinics and make sure they're checking the boxes of the LLM strategy," Quinones says.

The AI visibility work Quinones runs begins with a snapshot of where a client is currently showing up, measured through the Unmissable Index, her proprietary scoring framework for animal wellness discoverability. "Whenever I'm onboarding a client or talking with a prospect or lead, what I focus on is taking a snapshot of where that client is today," she concludes. "I look at the number of times they are cited. How many times are they referenced in an LLM? In Search Atlas, you can set which topics you want to monitor relevant to your business. It's about seeing where you're at, then driving your content strategy around that to influence showing up for those topics, which are long-tailed queries or questions people are actually asking."