We extract stylist profiles, service menus, pricing, availability calendars, and client reviews from StyleSeat. 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 Stylist Profiles objects from styleseat.com. All fields typed and schema-versioned.
"professional_id": "pro_892147x", "name": "Sarah Jenkins", "business_name": "Sarah Styles Studio", "category": "Hair Stylist", "rating": 4.9, "review_count": 412, "city": "Atlanta", "is_mobile": false
| # | professional_id | name | business_name | category | address | city |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Services & Pricing objects from styleseat.com. All fields typed and schema-versioned.
"service_id": "srv_10492", "professional_id": "pro_892147x", "service_name": "Silk Press & Trim", "price": 85.0, "currency": "USD", "duration_minutes": 120, "is_popular": true, "requires_deposit": true
| # | service_id | professional_id | service_name | category | price | currency |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Reviews & Ratings objects from styleseat.com. All fields typed and schema-versioned.
"review_id": "rev_99421", "professional_id": "pro_892147x", "reviewer_name": "Jessica M.", "rating": 5, "review_text": "Always leaves my hair flawless. Highly recommend.", "date": "2023-11-14", "service_received": "Silk Press & Trim"
| # | review_id | professional_id | reviewer_name | rating | review_text | date |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Availability Calendars objects from styleseat.com. All fields typed and schema-versioned.
"professional_id": "pro_892147x", "date": "2023-12-01", "available_slots": 3, "is_fully_booked": false, "timezone": "America/New_York", "slot_times": "['09:00', '13:30', '15:00']", "scraped_at": "2023-11-28T08:14:00Z"
| # | professional_id | date | available_slots | timezone | is_fully_booked | next_available_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Search Rankings objects from styleseat.com. All fields typed and schema-versioned.
"keyword": "braids", "city": "Houston", "position": 4, "professional_id": "pro_55123", "is_sponsored": false, "rating": 4.8, "review_count": 892
| # | keyword | city | position | professional_id | business_name | is_sponsored |
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Our StyleSeat pipeline extracts every layer of the platform: professional profiles, service menus, dynamic pricing, and availability calendars, with JavaScript rendering and rate limit circumvention built in.
Extract names, business names, bios, addresses, contact details, and overall ratings for every professional in a target city or category.
Capture individual services, pricing tiers, duration, deposit requirements, and descriptions directly from the stylist's booking page.
Monitor open booking slots, fully booked days, and next available dates to analyse supply and demand in real time.
Extract full review text, star ratings, service received, and provider responses across paginated review histories.
Capture image URLs, tags, and upload dates from professional portfolios to build visual datasets.
Track organic visibility for specific keywords across major cities, identifying top-performing professionals.
Extract cancellation policies, no-show fees, and late policies to understand professional business practices.
Run parallel pipelines across hundreds of US cities to build a national dataset of beauty professionals.
Run continuous pipelines at daily or weekly cadences to track price changes, new reviews, and shifting availability.
Brief in. Clean data out.
Provide a list of cities, zip codes, or specific professional URLs. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and calendar widget parsing logic for styleseat.com.
Schema validation, null-rate checks, and data normalisation routines run before full pipeline launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on an agreed cadence.
Directory scraping requires navigating complex frontend frameworks and aggressive rate limits. Here is how we maintain data flow.
StyleSeat relies heavily on client-side rendering for its availability calendars and service menus. We run full Playwright browser sessions to hydrate the React components and trigger the necessary API calls to render booking slots.
Directory sites use strict rate limiting to prevent bulk extraction. Our crawlers use US-based residential ISP proxies with realistic browser fingerprints and randomised request timing to distribute the load and avoid IP bans.
Frontend structures change frequently. Our extraction logic uses multiple fallback chains per field, targeting both DOM elements and internal JSON state objects to ensure the pipeline survives UI updates.
For large city-wide tracking, we maintain a hash index of last-seen values per professional. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, missing fields, and coverage drops, fixing issues before you notice.
Beauty tech companies and product distributors extract professional contact details and salon locations to build targeted outreach lists.
Analysts aggregate service prices across different cities and categories to establish market benchmarks and inflation trends.
Booking platforms and salon franchises monitor StyleSeat to track independent professional growth, review velocity, and platform adoption.
By tracking availability calendars and fully booked days, researchers measure consumer demand for specific beauty services by region.
Brands mine the review corpus to understand client preferences, complaints, and emerging trends in hair and skin care.
Commercial real estate and retail brands map salon density and professional ratings to identify optimal locations for new stores.
"StyleSeat holds the definitive dataset on independent beauty professionals, their service pricing, and their actual availability calendars."
Extracting this directory requires navigating complex single-page application hydration, dynamic calendar widgets, and aggressive rate limits. DataFlirt handles the JavaScript rendering and residential proxy rotation so your engineering team receives clean, normalised data ready for immediate query.
Everything supported by our styleseat.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, calendar hydration, and interaction flows.
We maintain pools of US residential ISP proxies. Rotation happens per-request with sticky sessions where required to prevent IP bans.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About styleseat.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available directory information is generally permissible under applicable law in the US. DataFlirt targets only public, non-authenticated professional profiles, pricing, and reviews. We do not extract private client data or circumvent authentication walls. Clients should review platform ToS and consult legal counsel for specific use cases.
We use US residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for rate limit spikes in real time and trigger pool rotation automatically.
Yes. Every pipeline run produces timestamped snapshots of the professional's calendar. We maintain a time-series record of open slots, booked days, and availability changes.
Full city or category refreshes typically complete within a 12-24 hour window depending on size. Targeted pipelines for specific professionals can run at hourly cadences.
Our smallest packages start at a defined list of cities or professionals with weekly delivery. For national coverage or custom schema requirements, we price based on volume and delivery frequency.
Yes, including full pagination across all historical reviews. Each record includes rating, text, date, service received, and provider responses.
Absolutely. We provide a sample run of up to 500 professional profiles as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off directory export or a continuous tracking feed across major cities, we scope, build, and operate the pipeline. Tell us what you need.
