We extract salon profiles, service menus, pricing, staff lists, and reviews from Fresha. 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 Venue Profiles objects from fresha.com. All fields typed and schema-versioned.
"venue_id": "849201", "name": "Lumiere Beauty Lounge", "type": "Beauty Salon", "city": "London", "rating": 4.9, "review_count": 842, "latitude": 51.5074, "longitude": -0.1278
| # | venue_id | name | type | address | city | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Service Menus objects from fresha.com. All fields typed and schema-versioned.
"service_id": "svc_94812", "venue_id": "849201", "category": "Hair Styling", "service_name": "Balayage & Blow Dry", "duration_minutes": 180, "price": 145.0, "currency": "GBP", "discount_price": "None"
| # | service_id | venue_id | category | service_name | description | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Staff Directories objects from fresha.com. All fields typed and schema-versioned.
"staff_id": "stf_4920", "venue_id": "849201", "name": "Sarah Jenkins", "role": "Senior Stylist", "rating": 5.0, "review_count": 156, "services_offered": "['Hair Styling', 'Colouring']"
| # | staff_id | venue_id | name | role | rating | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from fresha.com. All fields typed and schema-versioned.
"review_id": "rev_849201a", "venue_id": "849201", "reviewer_name": "Emma W.", "rating": 5, "review_text": "Best balayage in the city. Sarah was brilliant.", "date_posted": "2026-03-14", "service_received": "Balayage & Blow Dry", "staff_member": "Sarah Jenkins"
| # | review_id | venue_id | reviewer_name | rating | review_text | date_posted |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from fresha.com. All fields typed and schema-versioned.
"keyword": "hair salon", "location": "Manchester", "position": 3, "venue_id": "92810", "name": "Northern Quarter Cuts", "rating": 4.8, "top_rated_badge": true, "scraped_at": "2026-05-18T10:22:00Z"
| # | keyword | location | position | venue_id | name | type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Fresha scraper targets deep directory layers: venue profiles, granular service menus, staff listings, and customer reviews — handling dynamic pagination and map-based search results automatically.
Capture business name, address, coordinates, aggregate ratings, about text, and operating hours across multiple cities and categories.
Extract complete treatment menus including service names, descriptions, duration, standard pricing, and discounted rates.
Compile lists of practitioners, their roles, individual ratings, and the specific services they are qualified to perform.
Extract full text reviews, star ratings, service context, staff attribution, and venue replies across all historical data.
Iterate through geographic coordinates and bounding boxes to ensure complete coverage of venues in a target region.
Normalise venue classifications (e.g., Hair Salon, Spa, Nail Bar) and extract specific amenities or tags.
Identify 'Top Rated' venues and sponsored listings within search results to analyse platform visibility.
Scrape directories across the UK, US, Australia, and Europe with accurate currency and timezone mapping.
Run continuous pipelines that only emit records when a venue changes its pricing, adds new services, or receives new reviews.
Brief in. Clean data out.
Provide target cities, categories, or specific venue URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and geographic bounding box iteration for Fresha.
Schema validation, null-rate checks, and location deduplication before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Directory scraping requires bypassing location-based rate limits and rendering single-page applications. Here is how we maintain pipeline stability.
Fresha's interface relies heavily on client-side rendering. We run full Playwright browser sessions to hydrate service menus, trigger lazy-loaded reviews, and expose complete staff directories that static requests miss.
Standard search pagination limits results to top venues. We use programmatic coordinate grids (bounding boxes) to systematically scan cities block by block, ensuring 100% extraction of smaller, unranked salons.
Frequent requests to directory endpoints trigger rate limits. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to distribute load across target regions.
Platform updates frequently alter DOM structures. Our selector strategy uses multiple fallback chains — CSS selectors, XPath, and JSON payload interception — so layout changes do not break your data pipeline.
For large directory catalogues, we maintain a hash index of last-seen values. Subsequent runs only push diffs — reducing compute cost and downstream processing load when tracking price changes.
Software vendors and suppliers extract verified salon contact details, operating status, and staff counts to build targeted sales lists.
Franchises and independent salons track competitor service menus to optimise their own pricing strategies and treatment durations.
Brands analyse the frequency of specific treatments (e.g., balayage vs highlights) across regions to predict product demand.
Local discovery apps ingest venue profiles, ratings, and operating hours to enrich their own directory offerings.
Agencies monitor review velocity and aggregate ratings across thousands of venues to report on client performance vs competitors.
PE firms evaluate regional market saturation, average service prices, and review sentiment before acquiring salon chains.
"Fresha contains the most comprehensive pricing and service menu dataset for the global beauty and wellness industry — but accessing it requires navigating heavy map-based pagination and dynamic rendering."
Extracting local business directories at scale requires bypassing location-based rate limits and rendering single-page applications. DataFlirt handles the proxy rotation, JavaScript execution, and schema maintenance so your data engineering team receives normalised, query-ready records.
Everything supported by our fresha.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, geographic grid iteration, and retry logic. Playwright handles JavaScript rendering for single-page application hydration.
We maintain pools of residential ISP proxies across target regions. Rotation happens per-request to bypass location-based rate limits and 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 fresha.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available directory information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated venue profiles, service menus, and reviews. We do not extract personal user data or circumvent authentication walls.
Standard search results often cap at a certain number of venues. We use coordinate bounding boxes to divide a city into smaller grids, querying each sector individually to guarantee 100% extraction of all listed salons.
Yes. We extract the complete hierarchy of service categories, individual treatments, durations, standard prices, and any listed discounts or staff-specific pricing variations.
Yes. We capture staff names, roles, aggregate ratings, and the specific services each practitioner is qualified to perform, as listed on the venue profile.
Full city or regional directory refreshes typically complete within a 12-24 hour window depending on scale. We can configure delta pipelines to run weekly or monthly to capture new venues and price changes.
Yes. Every pipeline run produces timestamped records. We maintain a history of service prices, allowing you to track inflation or promotional pricing trends across specific venues or regions.
Our smallest packages start at a defined regional extraction (e.g., all venues in London or New York) with monthly delivery. For national or global coverage, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off directory export for a specific city or a continuous price-monitoring feed across national chains — we scope, build, and operate the pipeline. Tell us what you need.
