Open data · Google reviews · 2026
International patient reviews of Turkish clinics
We aggregated the newest public Google reviews from 100 businesses in hair transplant, dental and aesthetic care. Explore language, rating and owner-response patterns, then download the same comparisons as CSV.
9,297
reviews
100
businesses
42.8%
Non-Turkish reviews
$0.713
collection cost
Last updated: September 23, 2026 · Next scheduled review: 23 October 2026 · CC BY 4.0
Download aggregate CSVUTF-8 CSV for Excel and Google Sheets. Each row is one clearly labelled aggregate.
What the sample shows
Reviews with an unknown source language are not counted as international. Non-Turkish reviews make up 48.8% of reviews with known language and 42.8% of the full sample.
Businesses replied to 38.7% of reviews overall: 50.2% for hair transplant listings, 33.3% for dental and 31.6% for aesthetic listings.
Of 9,297 reviews, 8,678 had five stars (93.3%). The sample favours businesses with many public Maps ratings, so this does not represent all of Turkey.
Four more breakdowns
Reply gap · rating
- One-star reviews
- 34.6%
- Five-star reviews
- 39.1%
Businesses replied to 34.6% of one-star reviews and 39.1% of five-star reviews.
Reply gap · language
- Turkish
- 41.6%
- English
- 38.7%
- German
- 34.9%
- French
- 29.3%
The same businesses answer Turkish reviews more often than reviews in the languages international patients write in.
Rating distribution
- Five-star
- 93.3%
- One-star
- 4.9%
- Two to four stars
- 1.7%
Two-, three- and four-star reviews add up to just 1.7%. The average rating barely separates businesses; the signal is in the one-star share and how it is answered.
City
- Istanbul
- 83.3%
- Antalya
- 48.7%
- Mugla
- 26.8%
- Izmir
- 25.9%
- Aydin
- 0.5%
Non-Turkish share among reviews with a known language. The Aydin sample contains dental businesses only; city cuts are not market rankings.
Open data · Google reviews · 2026
Explore the breakdowns
| Breakdown | Value | Reviews | Non-Turkish reviews | 1-star | 5-star | Owner replied |
|---|---|---|---|---|---|---|
| Specialty | Hair transplant | 3,223 | 1,344 (41.7%) | 87 (2.7%) | 3,087 (95.8%) | 1,618 (50.2%) |
| Specialty | Dental | 3,744 | 1,266 (33.8%) | 233 (6.2%) | 3,444 (92%) | 1,245 (33.3%) |
| Specialty | Aesthetic | 2,330 | 1,366 (58.6%) | 137 (5.9%) | 2,147 (92.1%) | 736 (31.6%) |
What it means for clinics
Four practical directions the data points to. These are recommendations: we did not measure causation between reply rates and quality or conversion.
01
Answer negative reviews first, in the patient’s language
In the sample, one-star reviews were answered less often (34.6%) than five-star reviews (39.1%), and foreign-language reviews less often than Turkish ones. A calm, concrete reply in the reviewer’s own language is the first exchange the next patient sees. Do not discuss health details in public; move the conversation to a private channel.
02
Benchmark against your specialty and city, not the average rating
When 93.3% of reviews carry five stars, the average rating does not separate businesses. Compare your own one-star share, reply rate and language mix with the specialty and city rows in the CSV.
03
Turn the language mix into staffing and content plans
After English, the largest review languages are German, French, Spanish, Arabic, Russian and Polish. A language that stands out in your own reviews is an early signal for a coordinator and content in that language. Review language does not indicate nationality.
04
Measure the effect with your own data
This study does not measure how reviews affect conversion. To see it in your clinic, track Google Business Profile clicks by source, make “How did you find us?” a required CRM field, and compare enquiry → consultation → booking rates by source.
Method and limitations
Public Google Maps business reviews were collected through the DataForSEO Business Data API. On 23 September 2026, the newest 100 reviews were requested for 100 businesses; all 100 tasks completed and returned 9,297 reviews. Newest-first order was verified on 13 sample tasks covering 1,238 timestamps.
Candidates came from 15 Google Maps searches. The purposive sample has quotas across hair transplant, dental and aesthetic businesses and five cities. It is not a random national sample; city and specialty cuts are not market rankings.
Only aggregate review language, star rating, owner-response and coarse timing counts were retained. Review text, names, profiles, photos, individual review rows and clinic names are not published. No topic or sentiment analysis was performed, so we make no claims about why patients are satisfied or dissatisfied.
Google reviews do not represent a random sample of patients or procedures. High-rating listing selection, unknown source language and platform behaviour affect the results. Reply rates do not measure causation or care quality.
Source and capture date: DataForSEO Business Data Google Reviews API · Task retrieval endpoint · September 23, 2026
Read the full studyCite and reuse
Avangard Reklam — International Patient Reviews of Turkish Clinics. 23 September 2026. https://avangardreklam.com/tools/turkey-clinic-review-study/ · CC BY 4.0
Frequently asked questions
Does review language identify nationality?
No. Language cannot be treated as nationality, residence or patient identity. Unknown-language records remain a separate group.
Do these rates represent all clinics in Turkey?
No. Businesses were selected purposively, with preference for listings that had many public Google Maps ratings. The findings describe this collected sample only.
Why were review topics not classified?
Review text can contain personal or sensitive health details. We do not publish topic rates without a validated method that protects privacy.
Can the aggregate CSV be imported into a CRM?
No; there is no personal data to import. Each CSV row summarises one group (specialty, city, language or star rating) and contains no names, review text or individual records. Use it to benchmark a clinic’s own reply rate, language mix and one-star share against these averages, and to set targets in a CRM dashboard.
Do Google reviews increase international patient conversion?
This study does not measure conversion, and we found no open dataset linking reviews directly to conversion for Turkish clinics. To see the effect, track enquiry, consultation and booking rates by source in the clinic’s own CRM.
What does the split between one- and five-star reviews show?
In the sample, 93.3% of reviews have five stars and 4.9% have one star; everything in between is just 1.7%. The average rating therefore barely separates businesses; the one-star share and how it is answered say more. Because we did not analyse review topics, the reasons have to come from each clinic’s own reviews.
How do you run a competitor analysis with open data in healthcare?
Build a competitor list from the Google Maps searches a patient would make; collect public signals such as review count, rating distribution, review languages and owner replies; summarise them at specialty and city level without storing personal data; and compare them with your own figures. Stating how the sample was chosen and what it does not measure is what makes the result credible.