Rank OS Scoring Methodology — GMB for Clinics (Angryturtle)
What Rank OS actually measures
Rank OS grades a Google Business Profile across 47 distinct signals grouped into six categories. Each signal has a maximum score. Each score is weighted by the estimated correlation with local-pack rank for the clinic's top three query patterns. The total rolls up to a 0-to-1000 Rank OS score that is comparable across clinics, across specialties, and across time.
| Category | Signals | Weight |
|---|---|---|
| Completeness | 8 (name, categories, hours, services, attributes, description, cover photo, primary category match) | 14% |
| Activity | 7 (post cadence, Q&A responsiveness, offer freshness, event usage, product listings, post variety, message response rate) | 18% |
| Reviews | 9 (velocity, response rate, response latency, keyword mention density, star distribution, review length, photo-attached reviews, owner-response quality, review depth trend) | 26% |
| Photos | 7 (recency, exterior/interior/team split, geo-tagging, resolution, upload consistency, doctor headshots, before-and-after excluded) | 14% |
| Categories & services | 8 (primary category match, secondary category count, service list depth, service description length, procedure-specific services, price ranges present, service photos, service updates) | 16% |
| NAP consistency | 8 (name variations across 40 directories, address exact match, phone match, website match, hours match, structured data on website, GBP-website URL match, sameAs graph) | 12% |
The weights are not fixed forever. They update quarterly as our data on Google's local ranker shifts. When Google increases the weight of review-response latency (as it did in Q1 2026), Rank OS reweights and re-ranks the action list within the next Monday cycle.
How the score translates into an action list
A Rank OS score of 640 is not by itself useful. What is useful is the ranked list of the seven fixes that move the score fastest, per hour of clinic time. That list is what Angryturtle surfaces every Monday. The methodology behind the ranking:
- For each signal below its maximum, the estimated point-lift from closing the gap is calculated.
- The estimated clinic-hours to close the gap are applied — a photo upload takes 10 minutes, a category audit takes 3 hours.
- Signals are ranked by point-lift-per-hour.
- The top 7 become the week's action list. Anything below the top 7 waits for next week's cycle to avoid overwhelm.
This is what turns Rank OS from a diagnostic into an operating system. The clinic manager does not decide what to work on. They execute the top 7. The next Monday, the next 7. And so on.
Category weights — why reviews earn 26 percent
Review signals carry the single heaviest weight in Rank OS because Google's local ranker weighs them heavily and because reviews are the fastest-refreshing signal a clinic controls. A clinic that shifts its review-response latency from 6 days to 12 hours typically moves its Rank OS score by 40 to 70 points within two weeks. No other single lever produces comparable movement.
The nine review sub-signals inside the category also carry unequal weight. Response rate and response latency are heaviest. Star distribution matters less than most consultants believe. Keyword mention density in reviews — which the clinic can nudge through post-visit conversation, not through incentives — matters more than most consultants realise.
Category weights — why NAP is 12 percent and still non-negotiable
NAP consistency looks like a low-weight category, but the weight is misleading. NAP inconsistency does not just cost you the 12 percent — it caps every other category's contribution because Google's local ranker treats an inconsistent NAP as evidence that the profile is not reliably about a single real business. A clinic with a Rank OS of 890 across everything else but NAP consistency at 40 percent typically ranks worse than a clinic at 720 across everything with NAP at 100.
This is why Angryturtle's onboarding sequence begins with a 40-directory NAP audit and correction workflow. The rest of the score means little until the NAP floor is intact.
What a 90-day Rank OS trajectory looks like
- Day 0 — Baseline scan. Typical clinic score: 540 to 680. Category primary mismatch on 30 to 40 percent of clinics. NAP fragmented across 8 to 22 directories.
- Day 14 — NAP corrected. Category primary aligned. Score typically at 640 to 720. First local-pack rank changes visible in geo-grid tracking.
- Day 30 — Reviews cadence lifted. Response latency under 12 hours. Photos refreshed. Score at 720 to 800.
- Day 60 — Post cadence weekly. Q&A populated. Services list expanded. Score at 800 to 880.
- Day 90 — Score stabilised at 850 to 940. Top-3 local-pack rank on the clinic's primary specialty query in the primary neighbourhood.
What Rank OS deliberately does not measure
Rank OS excludes three categories of activity that some GMB tools include:
- Review incentives. Google's guidelines prohibit incentivising reviews. Any tool that ranks "reviews per week" as an independent goal is pushing clinics toward policy risk. Rank OS measures response quality and latency, not volume in isolation.
- Fake or bought reviews. These skew the review category short-term and destroy the score long-term when Google detects them. Rank OS treats sudden velocity spikes without engagement pattern as a warning signal, not a score booster.
- Bulk post automation. Automated posts that do not reflect real events at the clinic are algorithmic noise. Rank OS penalises post variety scores that read as boilerplate.
Get a Rank OS scan of your clinic's GBP
Angryturtle scans your Google Business Profile against the 47 Rank OS signals, produces a category-by-category score, and hands you the ranked action list for the first four weeks. Solo clinics can run it themselves; multi-location groups run it inside our Managed track.
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