Case Studies

Results: 60 days after making a vet clinic citable by AI

Sixty days after an AI-EO pass on a vet clinic site: first-party citation rate rose 29% to 38%, blog posts began getting cited by name, and Bing logged 1,544 AI citations.

ByAdpharm Digital||7 min read
Reviewed byBen Honda

Sixty days after the AI-EO pass on sixteenmilevet.com, first-party citation rate across ChatGPT, Claude, and Google AI rose from 29% to 38%, the informational blog posts that were invisible on day 0 now get cited by name, human visitors tripled while crawler and AI-bot traffic jumped roughly 14×, and Bing’s AI Performance report logged 1,544 citations with a 6.5× ramp across the window. The “best vet in Oakville” query and Powassan are the laggards.

This is the measured follow-up to Making a vet clinic citable by ChatGPT, Perplexity, and Claude, which covers what we shipped and why. Here we report what sixty days of crawl-and-cite actually produced.

Start with who showed up, measured in Silo CDP. First the people searching — the 61 days before launch laid over the 61 days after, day for day. Then the machines, over that same post-launch stretch, broken out by crawler.

Line chart of daily human visitors to sixteenmilevet.com as a 7-day rolling average, comparing the 61 days before launch against the 61 days after. The two lines track together until mid-June, when the post-launch line climbs to several times the pre-launch level.

Stacked area chart of daily bot requests over the 61 days after launch, broken out by crawler — Googlebot, Bytespider, and other bots. Requests stay low until mid-June, then surge, led by a Googlebot re-crawl and ByteDance's Bytespider.

Both run on the same clock. The human lines track together for five weeks, then the post-launch line pulls away in mid-June. The crawlers do the same — near-silent until mid-June, then a Googlebot re-crawl and ByteDance’s Bytespider pour in, everything else stacked behind them. That timing, five to six weeks after launch, is exactly when Google re-indexed the site and Bing’s AI citations started climbing.

What happened around day 40?

Launch was day 0, but nothing moved for five weeks — because getting cited by AI is a chain, not a switch. Google and Bing first had to re-crawl the rebuilt pages (the new robots policy, router-driven sitemap, and /llms.txt all point them in), then re-index them, and only then could answer engines retrieve and quote them. That pipeline took roughly five to six weeks to clear, which is why human visitors, crawler hits, indexed-page count, and AI citations all inflect together in mid-June rather than at the May launch. The practical takeaway: AI-EO is a re-crawl story — budget four to eight weeks before the needle moves.

We re-ran the same seven queries through the same three engines (ChatGPT with search, Claude with web search, and Google’s AI surface), from a logged-in Canadian session, on day 0 and again at day 60. The queries did not change between runs. “Cited” means the clinic’s own domain appears in the engine’s citation panel; first-party citation — the clinic’s site, not a directory or review aggregator — is the harder bar, and it is the bar every one of these citations clears.

Headline numbers (day-0 → day-60)

metric day-0 (2026-05-09) day-60 (2026-07-09) Δ
Cited rate (any) 29% 38% +9
First-party rate 29% 38% +9
Brand-mention rate 33% 38% +5

By engine:

engine day-0 cited day-60 cited Δ
ChatGPT 3/7 (43%) 3/7 (43%) flat
Claude 1/7 (14%) 2/7 (29%) +1
Google AI 2/7 (29%) 3/7 (43%) +1

Grouped bar chart of AI citation rate by engine from day 0 to day 60: ChatGPT flat at 43%, Claude rising from 14% to 29%, Google AI rising from 29% to 43%, and any engine rising from 29% to 38%.

What moved

  1. The slug-match informational queries. Heartworm, ticks, and Powassan — the three queries pointed at specific blog posts — were 0 for 9 across all engines on day 0. This was the load-bearing test: does publishing the answer actually surface the page once it is crawled? At day 60, the heartworm post is cited first-party by both ChatGPT and Google (Google quotes the “June 1 through November 1” window straight from it), and the tick post is cited first-party by Claude and ranks first in Google’s organic results. Two of the three landed. Powassan is the holdout and stayed at zero.

Google's AI answer for "When should I start heartworm prevention for my dog in Ontario?" citing Sixteen Mile Veterinary Clinic and quoting the June 1 to November 1 window from the clinic's own blog post.

  1. The /pricing.md and SMVC Club content. Google’s wellness-plan answer now reads “Sixteen Mile Vet in Oakville charges a flat $40/month for unlimited exams, plus 20% off vaccines and blood work” — quoted from the clinic’s own plan page. That query returned generic Banfield and Forbes content on day 0. The machine-readable pricing got read and repeated verbatim.

Google's AI answer for "Are monthly vet wellness plans worth it in Ontario?" quoting Sixteen Mile Veterinary Clinic's flat $40/month unlimited-exam plan as a local example.

  1. Claude moved off training data. On day 0 Claude cited the clinic once. At day 60 it cites the clinic first-party on both the branded reputation query and the tick query, pulling the reviewer-aware detail (in-house ultrasound, full-mouth dental radiography) that the E-E-A-T work put on the page.

What didn’t move

  • “Best vet in Oakville” is still a wall. Claude and Google both leave the clinic out of their top-list answer for the head local-commercial query; only ChatGPT ranks it (third). The answer both engines now lead with is Southeast Oakville Veterinary Hospital, which trades on accreditation badges (AAHA, Fear Free, Cat Friendly) the clinic does not currently hold.
  • ChatGPT’s count held at 3/7, but the mix improved: it dropped a weak, buried pricing citation and picked up the heartworm post at a real position.
  • Powassan stayed at zero across all three engines — the one content bet that has not yet paid out.

Supporting signals

  • AI citations, measured directly (Bing AI Performance report — citations in Microsoft Copilot and Bing AI summaries): the site was cited 1,544 times between May 12 and July 7, and the shape of the curve is the point. It ran at 6.4 citations/day in the first two weeks and 41.6/day in the last two — a 6.5× climb — peaking at 121 in a single day. Citation volume was sparse through mid-May and ramped hard across June as the content got indexed. This is the leading indicator the manual citation runs above confirm from the demand side.

Area chart of Bing AI citations per day from May 12 to July 7, 2026, totalling 1,544. The daily count runs near 6.4 per day for the first two weeks, then ramps 6.5 times to 41.6 per day in the last two weeks, peaking at 121 citations on June 10.

  • Which crawlers arrived (Silo CDP, matched 61-day windows; ubid was retired mid-run, so counts use anonymous ID): the bot surge charted at the top of this post is a Googlebot re-crawl (5 → 379 hits) plus the first appearances of AI fetchers — ClaudeBot, Bytespider, Meta’s external agent, and Google NotebookLM — none of which touched the site in the prior 61 days. Over the full windows, unique human visitors rose 409 → 1,282 (+213%) and unique bot agents 62 → 865 (~14×).

  • Indexed-page count (Google Search Console): 35 → 60 indexed pages (+71%) from the day-0 baseline (May 8) to day 60, while “not indexed” fell from 109 to 81. Google both discovered the new topic archives and pagination and indexed more of what it had already crawled — the router-derived sitemap doing its job.

Before-and-after bar chart of pages Google indexed: 35 indexed pages on day 0 rising to 60 on day 60, a 71% increase.

  • Core Web Vitals (GSC, Chrome UX field data, mobile): 51 of 51 URLs rated “good,” zero poor, zero needs-improvement as of July 7. Field data only crossed Google’s CrUX reporting threshold in mid-June — before that the site had too little real-user traffic to be scored at all — so the result reads as “enough traffic to finally be measured, and every measured URL passes.” Desktop still shows insufficient field data; PageSpeed Insights lab data covers that gap.
  • Rich-result eligibility (Google’s Rich Results Test): the homepage validates as LocalBusiness, Organization, and Review Snippet — all eligible for rich results — and the blog posts validate as Article and Breadcrumb. The FAQPage markup is present but no longer surfaces as a Google rich result — Google retired FAQ rich results for most sites — so it now earns its keep by handing AI engines a clean question-and-answer structure to lift from rather than by rendering a SERP dropdown.

Methodology

7 queries × 3 engines × 2 dates = 42 manual UI captures. Queries were grounded in real Google Search Console data — top impressions, blog-slug matches, and /pricing.md content — not plausible-sounding guesses. We measured in the consumer UIs rather than the provider APIs on purpose: the API’s web-search tool is a different surface (different backend, no consumer system prompt, no personalisation), so its citation rate is not a reliable proxy for what a real user sees. Screenshots and the per-query rationale live in the agency repo.

Sources

Related

Keep reading

Case Studies

Making a vet clinic citable by ChatGPT, Perplexity, and Claude

What we shipped on sixteenmilevet.com to make the site eligible for citation by AI answer engines: robots policy, llms.txt, reviewer-aware E-E-A-T, schema hygiene, and Core Web Vitals.

·6 min

AI & Tech

Claude Design produces AI slop unless you tell it not to

Anthropic's new design tool ships with anti-slop guardrails. They don't fire on their own. The DESIGN.md, system prompt, named aesthetic, and reference-mix that actually do.

·10 min

AI & Tech

A working playbook for Claude Code Skills on Opus 4.7

Skills are markdown files Claude reads when relevant. The description field decides whether one ever triggers. What changed in Opus 4.7, and the trap that silently disables half your skills.

·10 min

AI & Tech

Two Google image models, two jobs: a working prompt guide for Nano Banana Pro and Nano Banana 2

Google ships two image models on Gemini 3 now: Pro for hero shots, NB2 for everything else. The original Nano Banana's prompting habits actively hurt; here's the working stack.

·10 min

AI & Tech

Brand-fidelity mockups in Claude Code and Google Stitch: what actually steers them off the AI default

Both tools default to the same generic AI aesthetic: Inter, purple-on-white, three-up icon cards. A practitioner playbook for steering each off it, and the cross-tool file doing most of the work.

·10 min

AI & Tech

How to get Claude Opus 4.7 to write copy that doesn't sound like AI

A working playbook for stopping Claude from defaulting to LinkedIn-thinkpiece prose: the leverage points, the banned-words block, the three-pass workflow, and the before/after.

·10 min
© 2026 The Adpharm. All rights reserved.