Yelp uses automated recommendation software to surface trusted, first-hand doctor reviews and downrank suspicious or solicited posts.
Patients rely on star ratings when picking a physician. Yelp doesn’t show every post the same way, though. Its system studies each review and reviewer, then decides whether that content helps readers make a safe choice. The result is a mix of “recommended” reviews that feed the star average and a separate pool that sits behind a small link. Understanding how that works helps clinics set fair expectations and keeps their profile healthy without risky tactics.
How Yelp Screens Doctor Feedback: What Gets Shown
Yelp’s software looks at behavioral signals around the account and the content itself. It checks whether the reviewer appears to be a real, active person, whether the text reads like a first-hand visit, and whether anything hints at bias or coordination. The software updates over time, which means a review can move between states. Ads don’t change that decision, and staff can’t flip a switch to override it.
Signals The System Weighs
Think of the model as a trust gate. Reviews and accounts with solid, natural activity flow through. Items with red flags get parked in the “not currently recommended” section. That section is public, but those posts don’t impact the visible star average.
Common Patterns And Outcomes (Quick Reference)
| Signal | Likely Outcome | Notes |
|---|---|---|
| Reviewer with a history of detailed, diverse posts | Recommended | Account looks authentic and active over time. |
| Brand-new profile with one review and no photo | Not currently recommended | Low account history limits trust. |
| Reviews linked by timing or wording from many patients at once | Not currently recommended | Pattern can suggest a request campaign. |
| Review from staff, family, or vendors | Removed or not recommended | Conflict of interest flags bias. |
| Detailed, first-hand visit write-up with specifics | Recommended | Reads like a real appointment story. |
| “Drive-by” one-liners with few facts | Not currently recommended | Thin content can limit value. |
What “Recommended” Versus “Not Currently Recommended” Means
Recommended reviews shape the visible star rating and appear in the main feed. Posts that aren’t recommended sit behind a link on the profile. They’re still viewable, and the business can respond, but they don’t count toward the average or default sort. The pool can change. As the system learns more about a reviewer, a post may move into the main feed later, and the reverse can happen too.
Does Pay Change The Filter?
No. Yelp states that ads don’t impact whether a review shows up in the main feed. Recommendation decisions apply across advertisers and non-advertisers the same way. That separation exists to keep the marketplace fair and reduce pressure to “buy stars.”
Content Rules That Matter In Healthcare
Beyond the recommendation gate, content rules still apply. Posts can be removed if they break site policies. In healthcare, two areas come up often: conflicts of interest and privacy.
Conflicts And Solicitation
Yelp bars review requests. Asking patients to post—by email blast, QR code at checkout, or a gift card offer—can backfire. The platform calls this out plainly and treats organized campaigns as a bias signal. That signal makes posts less likely to land in the main feed. Read the policy here: Don’t ask for reviews.
Healthcare Privacy When You Reply
Patients can share their own details. Providers can’t share protected health information in public replies. The American Medical Association explains that acknowledging a patient relationship or discussing care risks a privacy breach. A safe path is a general, policy-based reply and an invitation to move the chat offline. See guidance from the AMA: Responding without violating HIPAA.
How The Recommendation Software Works In Plain Terms
Yelp describes a model that studies hundreds of signals. It looks at the reviewer’s footprint, the quality of the text, and signs of bias or coordination. The model learns over time, and decisions can change. Reviews that look reliable tend to be recommended; items that look risky tend to sit out. A short explainer from Yelp lives here: Recommendation software overview.
Why Reviews Move In Or Out
As the system gathers more data about a reviewer’s activity, it can re-score past content. A dormant account that starts posting consistently may see older posts shift to the main feed. The reverse can happen if new signals reduce trust. Yelp notes this movement happens regularly.
Doctor-Specific Edge Cases
Medical offices sometimes run into patterns that look odd to an algorithm. Staff send a portal message asking every discharged patient to leave feedback. A surge lands the same day. Wording lines up. The model sees coordination and parks many of those posts. It isn’t judging the care, only the pattern.
Procedures And Complex Visits
Long treatment plans can spark glowing notes that read similar across patients. When phrasing clusters, the system may treat them as connected. Patients writing in their own words and on their own timeline tends to fare better.
Follow-Up Visits And Family Accounts
Family members sometimes write on behalf of a patient. That can count as a third-party account and miss the “first-hand” bar. If the patient wants to post, a separate account in their name is safer.
What Not To Do If You Want More Recommended Reviews
Shortcuts usually trip the filter. Below is a clean list of moves to avoid and better habits that raise trust.
Risky Moves Versus Durable Habits
- Don’t hand patients a QR code that opens Yelp right after discharge. Let feedback arrive on its own schedule.
- Don’t offer perks or gifts for a rating. That counts as a conflict.
- Don’t coach wording or ask for a specific star count.
- Do keep your business info current, add clear hours, services, and photos that match the patient experience.
- Do reply with calm, policy-based language and invite a private channel when care issues arise.
Mid-Feed Snapshot: What The Model Says It Looks For
To recap in a single view, here are the factors Yelp says the model weighs. The terms below come from the platform’s own description and help set expectations for medical offices.
| Factor | How It Affects Visibility | Clinic Takeaway |
|---|---|---|
| Reviewer quality and activity | Active, real-looking accounts tend to be featured | Don’t engineer activity; let genuine patients post in their own time. |
| Potential bias or conflicts | Biased content gets downranked or removed | No staff or family reviews; no perks. |
| Learning over time | Reviews can move between states | Expect shifts in the feed now and then. |
Replying To Patients Without Creating Risk
A calm, brief reply shows patients you care and signals to readers that you’re engaged. Keep it high-level, avoid any details about care, and point to a private channel. Many clinics pre-approve a few templates so staff can respond quickly without naming conditions, visit dates, or any PHI. The AMA’s guidance above lays out the limits in plain terms.
Sample, HIPAA-Safe Reply Templates
When Someone Praises Care
“Thanks for sharing this experience. We aim for prompt, attentive visits for every patient. If you’d like to talk directly, call our office and ask for the practice manager.”
When Someone Reports A Wait Or Billing Issue
“We’re sorry for the frustration. We review scheduling and billing feedback each week. Please reach us at the number on our profile so we can look into your case offline.”
When The Reviewer Is Hard To Identify
“We’d like to help. Please contact the office with your visit date and initials so our team can follow up by phone.”
Ethics, Law, And Platform Enforcement
Most clinics want more patient feedback. Pushing for it can cross lines. Yelp runs active enforcement against “review gating” and vendors that claim they can bury comments. A recent court filing shows the platform pressing a case against a company that marketed removal services tied to its logo. The message is clear: paid tricks around star ratings are a dead end.
Clinic Playbook: Build Real Signals The Model Trusts
Here’s a practical plan any medical office can run without stepping on a policy landmine. It grows reviews in a slow, steady way that aligns with the filter.
Before The Visit
- Keep your profile consistent with your website: address, phones, services, insurances.
- Add clear photos that match reality: front desk, waiting area, entrances, parking notes.
- List service areas and specialties with plain wording patients use.
During The Visit
- Reduce surprises: signage for parking, forms, and wait estimates.
- Give patients a real contact point for concerns before they leave.
After The Visit
- Send a thank-you or satisfaction note that doesn’t ask for a rating or link to a review site.
- If a patient mentions they shared feedback online, say thanks. Don’t steer or script future posts.
What To Do When Good Reviews Sit “Not Currently Recommended”
It’s common to see glowing comments parked off the main feed, especially from new accounts. Coaching that person to edit or repost can make things worse. A better path is to grow overall trust on your page through steady, authentic activity. As the model learns more about those accounts and your profile, some posts may move into the main feed later. Yelp notes that movement happens as part of normal operations.
Clear Answers To Common Clinic Questions
Can A Business Ask Patients To Write Reviews?
No. The platform says not to do it, and signals of outreach can push posts out of the main feed.
Can Staff Or Family Rate The Office?
No. That’s a conflict, and those ratings can be removed or hidden.
Do “Not Currently Recommended” Posts Count Toward Stars?
No. They live in a separate pool and don’t affect the average.
Checklist For A Healthy Profile
- Keep NAP info (name, address, phone) consistent across your site and directories.
- Upload clear, current photos of the office and team.
- Reply to feedback with policy-based language; no PHI.
- Avoid any request or perk tied to reviews.
- Train front-desk staff on safe responses and escalation paths.
- Audit your profile monthly for hours, services, and insurance changes.
Why This Matters For Patients And Clinics
Readers want a feed that reflects real visits and avoids campaigns. Clinics want fair visibility. The recommendation layer tries to deliver both by leaning on trust signals. Work with it, not against it: remove friction in care, share accurate office details, and keep replies respectful and private when medical specifics pop up.