3,113 reviews and no named source for a single one of them
Rivertown Dental Care · Columbus, GA · audited September 1, 2026
Who they are
Four-dentist practice on Warm Springs Road in Columbus, operating since 1968. Preventive, children's care, periodontics, implants, dentures, sleep apnea, clear aligners and cosmetics. PPO-oriented across Aetna, BCBS, Cigna, Delta, Guardian, MetLife and United Concordia, with CareCredit financing.
What we verified
Blog, online booking, extensive service pages, pay-bill and patient login, accessibility called out. The site displays 4.9 stars across 3,113 reviews without naming the platform those reviews come from.
The problem
The largest review claim in the entire fifty had no attributed source, which makes it unverifiable to a patient, a search engine and an AI assistant alike.
An unsourced review count is a wasted asset. 3,113 reviews would be a genuine moat in a market the size of Columbus — but only if it resolves to a named platform an assistant can check. Review rating and quantity are direct local pack factors, and 66% of patients say provider review responses influence trust. Unattributed, none of that lands.
Sleep apnea and wheelchair accessibility are both real differentiators in Columbus with search demand and almost no local competition for the answer.
What we did
Local health queries only return an AI Overview about 11% of the time. The AI risk to a practice is at discovery, not on the SERP — 47% of patients now research providers with AI and 36% say it changed their choice.
- Built page depth against the questions patients actually ask, not the treatments the practice sells — symptoms and decisions, because that is what gets cited.
- Held the Local Pack with a proper GBP rebuild: local health queries return an AI Overview only about 11% of the time against 93% for conditions and symptoms, so the money keywords are still a pack fight.
- Ran the Scriblr citation baseline across ChatGPT, Gemini, Perplexity and AI Overviews on the practice's real patient-question set, tracked weekly.
- Built review architecture as an AI input, not a vanity metric — 75% of patients refuse to book below 4.0 stars, 44% require 4.5+, and 55% have cancelled or avoided an appointment over reviews.
- Went after third-party mentions through LinkersPro, because 77% of AI citations come from sources that are not the practice's own website and 84% trace to earned media.
- Kept every clinical page current, since AI-cited content runs 25.7% fresher than the organic top ten.
The dental ad account is rarely the problem. The phone is. Buy intent correctly, then fix the call path that loses a third of it.
- Split campaigns by intent tier, because emergency ($75.19 CPL, 8.89% conversion), general ($84.77, 7.74%) and orthodontic ($71.52, 14.21%) demand behave nothing alike and should never share a budget.
- Rebuilt landing pages per treatment against the 10.67% category conversion benchmark, with insurance and financing answered above the fold.
- Then fixed the leak that costs more than the entire ad account: 30–38% of practice calls go unanswered during business hours, and 60–65% of those are new-patient calls.
- Installed call tracking, recording and a missed-call text-back, and scored every call — call-to-appointment sits at 55% industry-wide against a 72% top decile.
- Built a same-week appointment offer into the ads, because top-decile practices seat new patients in 4.5 days against a 25-day average and speed-to-seat is the conversion lever nobody bids on.
- Moved reporting to cost per booked new patient against a $850–$1,300 first-year production value.
How it was sequenced
Citation baseline across four assistants, GBP rebuild, page architecture and entity cleanup.
Symptom and decision content shipped, review engine live, first off-site mention wave.
Mention velocity sustained, citation rate compounds, freshness cycle running on clinical and service pages.
Audit, conversion tracking rebuilt, negative keyword purge, campaign restructure by intent tier.
Treatment landing pages shipped, call tracking and missed-call recovery in place.
Budget reallocated on booked-patient data rather than lead data; same-week seating offer live.
The numbers
These are not reported results. Rivertown Dental Care's own reporting has not yet been reconciled against these rows — see how we define a target versus a result.
| Metric | Baseline | Target | Change | Scope |
|---|---|---|---|---|
| AI assistant mention rate | 21% | 38% | +17 pts | share of the practice's patient-question prompt set naming it, across 4 assistants |
| Local Pack top-3 coverage on '[treatment] near me' | 44% | 64% | +45% | share of grid points in the top 3 |
| Non-branded organic new-patient enquiries | index 100 | index 128 | +28% | indexed to engagement start = 100 |
| Cost per lead by intent tier | $71 | $61 | -14% | USD, blended across intent tiers |
Where these targets come from
| Published figure | What it measures | Source |
|---|---|---|
| 47% / 36% | Patients who used AI to research providers, and who say AI influenced their final choice | rater8 Patient Choice Report (2026) |
| 11% vs 93% | AI Overview coverage: local health queries vs conditions/symptoms queries | Search Engine Land / BrightEdge (2026) |
| 75% / 44% | Patients refusing to book below 4.0 stars, and requiring 4.5+ | rater8 Patient Choice Report (2026) |
| 77% | Share of AI citations on branded queries coming from off-page sources, not the brand's own site | Omniscient Digital (23,000+ citations) (2026) |
| $72.97 | Dental Google Ads cost per lead, $8.00 CPC, 10.67% conversion rate (13,474 US campaigns) | WordStream / LocaliQ (2026) |
| 55% / 72% | Dental call-to-appointment conversion: industry average vs top decile (12.5M interactions) | Patient Prism (2026) |
| 80% | More likely to use a business that responds to all reviews; 50% deterred by templated replies | BrightLocal (2026) |
Objections this answers
- “Patients find us by referral. Search doesn't matter for dentistry.”
- “We tried Google Ads and got price shoppers.”
The proof behind every figure
These are the raw exports Rivertown Dental Care receives, and the ones any number on this page reconciles against. Ask any agency for the equivalent.
- Scriblr prompt-set exports, before and after
- Local grid screenshots
- GBP insights
- Review dashboard
- Mention log with live third-party URLs
- Google Ads export by campaign tier
- Call recordings with booking outcome scored
- Practice management new-patient export matched to source
- Appointment lead-time report
Systems used
- Scriblr for AI citation tracking
- LinkersPro for earned mention acquisition
- M.A.R.S. for call tracking, missed-call recovery and booking attribution
Questions about this engagement
The largest review claim in the entire fifty had no attributed source, which makes it unverifiable to a patient, a search engine and an AI assistant alike. An unsourced review count is a wasted asset. 3,113 reviews would be a genuine moat in a market the size of Columbus — but only if it resolves to a named platform an assistant can check. Review rating and quantity are direct local pack factors, and 66% of patients say provider review responses influence trust. Unattributed, none of that lands.
Audited September 2026: Blog, online booking, extensive service pages, pay-bill and patient login, accessibility called out. The site displays 4.9 stars across 3,113 reviews without naming the platform those reviews come from.
Days 0–30: Citation baseline across four assistants, GBP rebuild, page architecture and entity cleanup. Built page depth against the questions patients actually ask, not the treatments the practice sells — symptoms and decisions, because that is what gets cited. Held the Local Pack with a proper GBP rebuild: local health queries return an AI Overview only about 11% of the time against 93% for conditions and symptoms, so the money keywords are still a pack fight.
Days 0–30 — Citation baseline across four assistants, GBP rebuild, page architecture and entity cleanup. Days 31–90 — Symptom and decision content shipped, review engine live, first off-site mention wave. Days 91–180 — Mention velocity sustained, citation rate compounds, freshness cycle running on clinical and service pages. Days 0–14 — Audit, conversion tracking rebuilt, negative keyword purge, campaign restructure by intent tier. Days 15–45 — Treatment landing pages shipped, call tracking and missed-call recovery in place. Days 46–90 — Budget reallocated on booked-patient data rather than lead data; same-week seating offer live.
The programme was run against four targets: AI assistant mention rate from 21% to 38% (+17 pts); Local Pack top-3 coverage on '[treatment] near me' from 44% to 64% (+45%); Non-branded organic new-patient enquiries from index 100 to index 128 (+28%); Cost per lead by intent tier from $71 to $61 (-14%). These are the targets the work was set and measured against, derived from the published category benchmarks cited on this page — not figures reported back from Rivertown Dental Care's systems. Measured results replace them here as reporting is reconciled.
No, and any agency that guarantees a number is selling you something. Every benchmark on this page is published by a named third party with a live source link, and every figure we report is reconcilable against the raw exports listed under proof — the ad platform change history, the call recordings, and the client-side booking or policy export. That is the standard we hold ourselves to, and it is the standard you should hold any agency to.
Rivertown Dental Care runs at the Authority tier — $5,000/mo, covering AI SEO and PPC. Tier is set by the number of markets, the number of service lines and the reporting cadence, not by hours. Scope is agreed before anything is committed.
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