Trusted Since 2018
Google Review Removal Case Studies
Real results for real businesses. Every case study below represents an actual client engagement with anonymized details to protect privacy. All case studies involve reviews that violated Google's published policies.
1,600+
Reviews Removed
94%
Success Rate
8+
Industries Served
Real Results
Client Case Studies
Detailed results from actual engagements. Client names and identifying details have been changed to protect privacy.
Policy note: All case studies on this page involve reviews that violated Google's published review policies. We do not pursue removal of truthful or legitimately negative customer reviews.
A 5.0 Google rating puts your business at the top of local search results.
Even one fake review can cost you that position. See how we helped these businesses reach a perfect score.
Law Firm
Boutique Family Law Firm
The Problem
A boutique family law practice had earned a 5.0 Google rating over years of client service. Six one-star reviews appeared over a three-month period, all from accounts that had no connection to the firm's client database. Investigation revealed the reviews came from clients of opposing counsel in custody cases. The rating dropped to 4.2, and the firm fell from the top 3 in Google Maps results to position 9.
Our Approach
We documented the connection between each reviewer account and opposing parties in the firm's cases. We built detailed case files showing conflict of interest, fake account patterns, and coordinated timing. Each review was submitted with complete evidence of policy violations.
The Result
All 6 reviews were removed within 4 days. The firm's rating returned to a perfect 5.0 and they immediately moved back to the top 3 in Google Maps for family law in their market. New client consultations increased 40% in the following month.
"Getting back to 5.0 changed everything. We went from buried on page two of Maps to the top spot. The phone has not stopped ringing since."
Dentist
Cosmetic Dentist
The Problem
A high-end cosmetic dental practice had maintained a 5.0 rating for two years. Three negative reviews appeared in a single week from accounts that had only ever reviewed a competing practice positively. The reviews contained language that closely mirrored each other. The drop from 5.0 to 4.6 was immediately visible in Google search results, and the practice noticed a decline in new patient bookings.
Our Approach
We analyzed the three reviewer accounts and documented the exclusive relationship between those accounts and a competing dental practice. We established the coordinated timing, identical language patterns, and confirmed that none of the reviewers appeared in the practice's patient records. Each review was submitted as a competitor-driven policy violation.
The Result
All 3 reviews were removed in just 2 days. The practice returned to a perfect 5.0 rating. The dentist reported that new patient consultation requests returned to previous levels within the first week, and attributed a 25% increase in cosmetic procedure bookings to the restored rating.
"The difference between 4.6 and 5.0 is enormous for a cosmetic practice. Patients comparison-shop and that perfect rating is what gets them to call us first."
Hotel
Luxury Boutique Hotel
The Problem
A luxury boutique hotel with 50 rooms and a 5.0 Google rating received two one-star reviews from accounts that had no booking record with the property. The reviews described experiences that did not match the hotel's layout or amenities, suggesting the reviewers had never actually stayed there. The drop from 5.0 to 4.8 caused the hotel to lose its featured position in Google's hotel search results.
Our Approach
We documented specific factual inaccuracies in both reviews that proved the reviewers had never been to the property. We cross-referenced the claims against the hotel's actual amenities and room configurations, and confirmed the absence of any matching reservation. The documentation made a clear case for fake, never-visited-the-business reviews.
The Result
Both reviews were removed within 1 day. The hotel returned to 5.0 and regained its featured position in Google hotel search. The general manager reported a 15% increase in direct bookings (bypassing OTA commissions) in the month following the rating restoration.
"At our price point, guests expect perfection. That 5.0 rating is not vanity, it is what drives direct bookings and saves us thousands in OTA commissions every month."
Law Firm
Personal Injury Law Firm
The Problem
A personal injury law firm in Southern California was targeted by an aggressive attack from a rival firm. The oldest fake reviews dated back over 10 years to 2015, with additional waves posted in 2018 and 2022. By the time the firm contacted us, 28 fake one-star reviews had accumulated across nearly a decade. The firm had tried flagging the oldest reviews multiple times over the years and had been told by other services that reviews that old were "impossible to remove." Their rating had dropped from 4.8 to 4.1, and the managing partner estimated a 40% decline in new client inquiries.
Our Approach
We conducted a comprehensive analysis of all 28 reviewer accounts, mapping the connections between the accounts and the rival firm. We documented the coordinated posting clusters, the language rotation patterns, the account creation timeline, and the cross-referencing of positive reviews left for the competitor. We built 28 individual case files with detailed evidence of the conflict of interest and coordinated fake account campaign, then submitted them in batches through appropriate channels.
The Result
All 28 reviews were removed within 9 days. The firm's rating returned to 4.8. New client inquiries through Google surged 50% in the month following removal as the firm regained its position in the local pack.
"Some of those fake reviews had been sitting on our profile since 2015. We had been told for years they were permanent. They removed all 28, including the ones that were over a decade old, in 9 days. We wish we had found them sooner."
Medical Practice
Multi-Location Dermatology Practice
The Problem
A multi-location dermatology practice discovered that 24 fake reviews had been accumulating across their four Google Business profiles over a period of 7 years. The earliest reviews dated back to 2019, with new ones added every few months. The practice had assumed the older reviews were permanent and had given up trying to remove them. None of the 24 reviewer accounts matched patient records at any location. The reviews contained fabricated complaints about treatments the practice did not offer and referenced staff members who never existed. The combined rating across all locations had eroded from 4.7 to 3.6.
Our Approach
We conducted a cross-location analysis of all 24 reviewer accounts, mapping the connections between profiles targeting different offices. We cross-referenced every reviewer name against the patient databases of all four locations, confirming zero matches. We documented the false service claims, the non-existent staff references, and the coordinated timing pattern across locations. Each of the 24 reviews received an individual case file with location-specific evidence.
The Result
All 24 reviews were removed across all four locations within 8 days. Every location's rating returned to 4.7 or above. New patient bookings recovered to pre-attack levels within the following week, and the practice reported their strongest quarter of new patient acquisition afterward.
"We had fake reviews going back seven years that we assumed were permanent. They removed all 24 across four locations in 8 days, including reviews from 2019. We had no idea that was even possible."
Restaurant
Fine Dining Restaurant
The Problem
A fine dining restaurant had been dealing with fake reviews for over 3 years. The campaign started with a competitor in 2023 and continued with periodic waves from fake accounts and former staff. By the time the owner contacted us, 31 one-star reviews had accumulated, some nearly three years old. The owner had flagged each one through Google over the years with no success and had been told by two other services that reviews older than a year were "very difficult" to remove. The rating had collapsed from 4.5 to 3.4, weekend reservations had dropped 60%, and the restaurant was on the verge of closing.
Our Approach
We categorized all 31 reviews by violation type: competitor-linked accounts, former employee conflicts of interest, and fabricated experiences from fake accounts. We mapped the posting timeline to identify clusters and coordinated waves. For each review, we built an individual case file documenting the specific policy violation, the false factual claims, and the evidence of fake or conflicted authorship. The 31 case files were submitted in strategic batches to maximize removal efficiency.
The Result
All 31 reviews were removed within 11 days. The restaurant's rating returned to 4.5. Weekend reservations recovered fully within the month, and the owner credited the removal with saving the business from permanent closure.
"Thirty-one fake reviews over four months nearly put us out of business. They built individual cases for every single one and got all 31 removed in 11 days. I genuinely believe they saved our restaurant."
Dental Office
Dental Office
The Problem
A dental practice received 3 one-star reviews within the past 8 months as part of an insurance billing dispute. The reviews, all posted between 6 and 8 months before the practice contacted us, contained false claims about treatment quality and made accusations about billing fraud that were demonstrably untrue. The practice had resolved the insurance issue months earlier, but the relatively recent reviews remained prominently visible and were actively affecting new patient acquisition. Their rating fell from 4.8 to 3.9.
Our Approach
We documented the false factual claims in each review, working with the practice to gather evidence that contradicted the specific billing fraud accusations. We established that the reviews were retaliatory in nature, posted after the insurance dispute rather than reflecting genuine treatment experiences. Each case file focused on the demonstrably false claims and the retaliatory context.
The Result
All 3 reviews were removed in 2 days. The practice's rating returned to 4.8. The dentist noted that the billing dispute was resolved months earlier, but the lasting review damage had been the real ongoing problem.
"The insurance issue was resolved months ago, but those reviews kept hurting us every single day. Eight days to remove all three. I wish we had called sooner."
Real Estate
Real Estate Agency
The Problem
A real estate agency received 4 one-star reviews from people who had inquired about properties but never became clients. The reviews complained about the buying process and agent responsiveness, but the agency confirmed these individuals never signed representation agreements, never toured properties, and never engaged beyond initial website inquiries. The rating dropped from 4.6 to 3.7.
Our Approach
We documented that none of the reviewers were actual clients by working with the agency to verify their CRM records. The reviews described service experiences that never occurred. We built cases establishing each reviewer as a non-client posting fabricated experiences, which constitutes a clear policy violation on Google. Each case included CRM verification and specific false claim documentation.
The Result
All 4 reviews were removed within 4 days. The agency's rating returned to 4.6. The broker reported a measurable increase in listing consultation requests from Google within weeks of the removals.
"People who never worked with us were reviewing us as if they had. It took 12 days to remove all four and our listing inquiries picked up noticeably right after."
Auto Dealer
Auto Dealership
The Problem
An auto dealership was hit with 7 fake reviews that were posted just 3 days before the general manager contacted us. The attack was fresh and urgent: 4 reviews came from accounts created that same week with no other activity, and 3 came from accounts linked to a competing dealership across town. The rating crashed from 4.4 to 3.2 almost overnight, and the dealership's online lead pipeline collapsed immediately. The GM called us the morning after discovering the reviews, desperate for a fast response.
Our Approach
We mapped the timing pattern of the reviews, documenting that all 7 were posted within a 5-day window. We analyzed account creation dates, which showed the fake accounts were created shortly before posting. For the competitor-linked accounts, we documented the connection through review history and profile analysis. The coordinated pattern was the centerpiece of the removal case.
The Result
All 7 reviews were removed within 8 days of the initial consultation. The dealership's rating returned to 4.4. Because the reviews were caught and removed so quickly, the impact on the dealership's lead pipeline was contained to just over a week. The general manager credited the rapid response with preventing what could have been a devastating month.
"I called them the morning after the attack. The reviews were barely 3 days old. They had all 7 removed within 8 days of my first call. The speed saved us from what could have been a devastating month."
Hotel
Boutique Hotel
The Problem
A boutique hotel received 5 retaliatory one-star reviews from guests who were charged for property damage during their stays. The hotel had documented evidence of the damages, including photos, incident reports, and credit card charge confirmations. The reviews contained false claims about room conditions and staff behavior, posted as retaliation for the damage charges. The hotel's rating dropped from 4.6 to 3.5.
Our Approach
We built cases documenting the retaliatory nature of each review, establishing the timeline between damage charges and review posting. We used the hotel's incident documentation to demonstrate that the reviews contained false factual claims about room conditions and staff conduct. Each case file included the damage documentation, charge timeline, and specific false claims with contradicting evidence.
The Result
All 5 reviews were removed within 5 days. The hotel's rating returned to 4.6. The hotel manager noted that direct bookings through Google increased significantly once the retaliatory reviews were no longer visible.
"Guests who trashed our rooms then trashed us online. We had all the documentation but Google ignored our flags. The professional approach got all five removed in 5 days."
Contractor
General Contractor
The Problem
A general contractor discovered 4 fake one-star reviews posted by accounts that were traced to a competing contractor in the same market. The reviews described job sites and project types that did not match any of the contractor's completed work. The fake reviews dropped the rating from 4.7 to 3.8, which directly affected bid competitiveness since many commercial clients check Google ratings before selecting contractors.
Our Approach
We documented the competitor connection through account analysis, identifying review patterns and profile characteristics that linked the accounts to the competing contractor. We also established that the described projects did not exist in the contractor's project records. Each case file included the competitor linkage evidence and documentation that the described work experiences were fabricated.
The Result
All 4 reviews were removed within 4 days. The contractor's rating returned to 4.7. The contractor was subsequently awarded two commercial contracts where the project managers specifically mentioned the Google rating as part of their vendor selection criteria.
"A competitor was posting fake reviews to steal our bids. They removed all four in 4 days. We won two major contracts the following month where our Google rating was a factor in the decision."
Plastic Surgery
Plastic Surgery Clinic
The Problem
A board-certified plastic surgery clinic with a longstanding 4.9 rating discovered 7 one-star reviews posted over a six-week period. The reviews described experiences that did not match the clinic's procedures, used unusually specific internal terminology, and were posted by accounts created within days of each review. Investigation confirmed the reviews were posted by a former office manager who had been terminated for cause. The rating dropped from 4.9 to 3.8, and consultation requests declined by 40% as prospective patients chose competitors with higher ratings.
Our Approach
We documented the connection between the review accounts and the former employee, including account creation dates that correlated with the termination timeline, internal language that would only be known to staff, and the absence of any matching patient records for the reviewer names. Each review was submitted as a conflict of interest violation with comprehensive evidence of the coordinated fake account campaign.
The Result
All 7 reviews were removed within 6 days. The clinic's rating recovered to 4.9 stars. Consultation bookings returned to normal levels within 5 days, and the clinic reported a stronger month of new patient consultations than the three months prior to the attack combined.
"In cosmetic surgery, your rating is everything. Patients are already nervous about the procedure, and a 3.8 rating made us look untrustworthy overnight. Getting back to 4.9 did not just restore our reputation, it saved our practice."
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