We extract provider profiles, patient reviews, Worth It ratings, treatment costs, and Q&A forums from RealSelf. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Provider Profiles objects from realself.com. All fields typed and schema-versioned.
"provider_id": "P849201", "name": "Dr. Sarah Jenkins", "specialty": "Plastic Surgeon", "rating": 4.8, "review_count": 342, "board_certified": true
| # | provider_id | name | specialty | location | rating | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Patient Reviews objects from realself.com. All fields typed and schema-versioned.
"review_id": "R99382", "treatment_id": "T45", "rating": 5.0, "worth_it_status": "Worth It", "cost_paid": 8500.0, "date_posted": "2026-03-14"
| # | review_id | provider_id | treatment_id | author | rating | worth_it_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Treatment Costs objects from realself.com. All fields typed and schema-versioned.
"treatment_name": "Rhinoplasty", "average_cost": 7800.0, "min_cost": 3000.0, "max_cost": 15000.0, "total_reviews": 12450, "worth_it_pct": 91
| # | treatment_id | treatment_name | category | average_cost | min_cost | max_cost |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Q&A Forums objects from realself.com. All fields typed and schema-versioned.
"question_id": "Q49281", "treatment_id": "T12", "question_title": "How long does swelling last?", "answer_count": 4, "date_asked": "2026-04-02", "view_count": 1403
| # | question_id | treatment_id | author_details | question_title | question_body | date_asked |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Before & After Metadata objects from realself.com. All fields typed and schema-versioned.
"photo_id": "PH8392", "provider_id": "P849201", "patient_age": 34, "procedure_details": "Primary Rhinoplasty", "upload_date": "2026-01-15", "view_count": 892
| # | photo_id | provider_id | treatment_id | patient_age | patient_gender | procedure_details |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our RealSelf scraper handles every layer of the platform: provider directories, dynamic cost data, patient reviews, and the Q&A corpus, with JavaScript rendering and anti-bot circumvention built in.
Extract names, specialties, board certifications, locations, and contact metadata across the entire provider catalogue.
Capture full review text, star ratings, Worth It status, and reported costs paid by patients.
Track average, minimum, and maximum costs for specific procedures based on aggregated patient reports.
Extract patient questions and verified provider answers to build comprehensive medical NLP datasets.
Capture photo metadata, patient demographics, and procedure tags associated with visual evidence.
Target specific cities, states, or postal codes to build regional competitive intelligence reports.
Run continuous pipelines that only emit records when a provider updates their profile or receives a new review.
Bypass rate limits and CAPTCHAs using residential proxies and realistic browser fingerprints.
Navigate deep review histories and extensive Q&A threads without dropping records or triggering blocks.
Brief in. Clean data out.
Provide provider URLs, treatment categories, or geographic regions. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for realself.com.
Schema validation, null-rate checks, and data normalisation tests before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
RealSelf invests heavily in scraping detection. Here is how we stay resilient, and why teams choose managed infrastructure over DIY.
RealSelf blocks data centre IPs aggressively. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management trained on real user behaviour patterns.
Provider pages and review feeds rely on JavaScript for lazy loading. We run full Playwright browser sessions with JavaScript execution to trigger pagination and hydrate data that headless HTTP clients miss entirely.
RealSelf frequently tests new UI layouts. Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and JSON-LD extraction, ensuring layout changes do not break your data pipeline.
For large provider directories, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost, storage bloat, and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, coverage drops, and schema drift, responding before you notice any data degradation.
Healthcare analysts track treatment popularity, average costs, and patient satisfaction trends across different geographic regions.
Clinics monitor local competitors to optimise their pricing strategies and identify service gaps in their market.
Medical device manufacturers and pharmaceutical companies identify high-volume providers for targeted sales outreach.
Data science teams analyse review text and Q&A forums to understand patient concerns, recovery experiences, and overall satisfaction.
Practices aggregate cost data for specific treatments to ensure their consultation fees and procedure prices remain competitive.
Machine learning teams use structured Q&A data to train medical chatbots and patient advisory algorithms.
"RealSelf holds the definitive dataset on cosmetic procedure pricing and patient sentiment, but accessing it requires navigating aggressive bot mitigation."
Extracting aesthetic medicine data at scale requires bypassing sophisticated TLS fingerprinting and handling heavily JavaScript-rendered provider pages. DataFlirt manages the proxy rotation, session state, and DOM parsing so your engineering team can focus on analysis rather than pipeline maintenance.
Everything supported by our realself.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across targeted regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda for burst workloads and ECS for sustained extraction. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About realself.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from RealSelf is generally permissible under applicable law. DataFlirt targets only public, non-authenticated provider profiles, reviews, and Q&A data. We do not extract private messages, circumvent authentication walls, or violate GDPR. Clients should review RealSelf Terms of Service and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains so DOM changes do not break the pipeline. We monitor for rate spikes in real time and trigger pool rotation automatically.
Yes. We can scope the pipeline to extract data exclusively for specific procedures, such as rhinoplasty or breast augmentation, targeting relevant providers, reviews, and cost aggregates.
Full catalogue refreshes at a weekly or daily cadence complete within a 6 to 12 hour window depending on scale. Delta runs can be configured to capture new reviews or profile updates on an hourly basis.
Our smallest packages start at a defined provider list or specific geographic region with weekly delivery. For full national directory extraction, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
Absolutely. We provide a sample run of up to 500 provider profiles or 1,000 reviews as part of the pre-engagement scoping process so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off provider catalogue dump or a continuous review monitoring feed across 50,000 clinics, we scope, build, and operate the pipeline. Tell us what you need.
