Comparing your AI visibility to a competitor's means running the same patient questions through ChatGPT, Gemini, Perplexity, and Google's AI Overviews that a real patient would ask, then noting whose practice gets named, which sources the engine cites, and where your own site is thin or absent. The practice that gets recommended usually has clearer directory listings, more specific procedure content, and visible credentials like board certification through the American Board of Colon and Rectal Surgery (ABCRS). The comparison itself takes less effort than fixing what it reveals.
See who AI recommends in your area
AI search tools answer patient questions by pulling from a mix of directories, hospital system pages, review platforms, and practice websites, then synthesizing an answer that names one or two providers. If a competitor's name comes up for "best colorectal surgeon near me" or "who treats diverticulitis in your city" and yours doesn't, that gap is measurable and specific, not a vague brand perception problem. You can see it directly by asking the same questions the engines are already answering for patients.
Prompts to test the way patients search
Testing your visibility means asking the questions patients actually type, not marketing language about your practice. Try variations like "who is the best colorectal surgeon for diverticulitis near your city," "which surgeons treat Crohn's disease surgically in your region," "find a colorectal surgeon who does colonoscopies and removes polyps," and "board certified colorectal surgeon near me." Note whether your practice appears, whether a competitor appears instead, and what specific detail the engine used to justify the recommendation.
Run these prompts across ChatGPT, Gemini, Perplexity, and Google AI Overviews separately, since each draws on different sources and can produce different answers. A competitor might rank in Google's Overview because of a well-optimized service page, but show up in Perplexity because of a strong local directory listing or a hospital affiliation page that lists their name. Recording which engine favors which competitor tells you where to focus first.
Reading which sources engines cite for rivals
When an AI engine names a competing practice, it is almost always pulling from an identifiable source: a hospital system's physician directory, Healthgrades or Vitals profile, a condition-specific page about colorectal cancer screening or diverticulitis treatment, or patient reviews mentioning a procedure by name. Look at the citations or linked sources the engine shows alongside its answer. That list is a direct map of what convinced the engine to trust that practice's authority on the topic.
Pay attention to specifics: does the competitor's cited page mention ABCRS board certification, list minimally invasive or robotic-assisted procedures by name, or describe experience with inflammatory bowel disease and colorectal cancer surgery? Engines tend to favor pages that answer a specific clinical question clearly rather than general "about us" language. If a rival's hospital bio page states plainly that they perform low anterior resections or treat ulcerative colitis surgically, and your own site only says "comprehensive colorectal care," that specificity gap is likely what tips the recommendation in their favor.
Content gaps that explain the difference
A content gap is any patient question an AI engine can answer clearly from a competitor's material but not from yours, and these gaps are usually the direct explanation for a visibility difference. Common gaps for colorectal surgery practices include missing condition-specific pages for diverticulitis, Crohn's disease, ulcerative colitis, and colorectal cancer, no clear statement of board certification credentials, and thin descriptions of procedures like colonoscopy, colectomy, or robotic-assisted surgery.
Directory completeness is another frequent gap. If a competitor's profile on a hospital system site, Healthgrades, or a colorectal-specific referral directory includes detailed procedure lists, accepted insurance, and patient-facing condition explanations, while your listings are outdated or sparse, AI engines have less material to draw from when considering your practice for the same query. Reviews that mention specific conditions or procedures by name also feed engines more directly than generic five-star ratings without detail.
Closing the visibility gap
Closing the gap means matching or exceeding what made the competitor visible in the first place: clear condition-specific content, complete and accurate directory listings, visible board certification, and reviews that mention real procedures and conditions patients search for. Prioritize the queries where a competitor consistently outranks you and address the exact source type that keeps surfacing in that engine's citations.
Start with directory and profile corrections, since inaccurate or incomplete listings on hospital systems, Healthgrades, Vitals, and other referral sites are the most straightforward fix and give engines cleaner, more current information to cite. Follow with content that answers specific patient questions directly, such as a page explaining what to expect from diverticulitis surgery or how colorectal cancer screening and treatment works at your practice, rather than general overview pages. Reviews that reference specific conditions and procedures, gathered over time from real patient experience, reinforce that content and give engines more to work with.
The fastest changes tend to be directory corrections and credential visibility, since those are discrete facts an engine can pick up once the listing is accurate. Content that answers specific condition questions takes longer to influence engine recommendations because it depends on the page being crawled, judged relevant, and weighed against what competitors already have published. Reviews mentioning specific procedures and conditions build gradually as patients naturally reference their experience.
What changes first is usually the accuracy of what is already public: your board certification, procedure list, and directory details start reflecting reality instead of an outdated snapshot. What takes longest is earning the recommendation itself, since AI engines weigh accumulated signals across multiple sources before consistently naming a practice for a given condition or procedure. Patients researching diverticulitis, Crohn's disease, or a colorectal cancer diagnosis are the ones this work is ultimately for. Closing the gap means that when they ask an AI engine who to see, the answer is your practice, described accurately, for the condition they actually have.