We extract course metadata, instructor profiles, lesson structures, pricing signals, and student reviews from CreativeLive. 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 Course Catalogues objects from creativelive.com. All fields typed and schema-versioned.
"course_id": "cl-ph-102", "title": "Fundamentals of Photography", "category": "Photo & Video", "instructor_name": "John Greengo", "price": 99.0, "duration_minutes": 1440, "student_count": 145201, "rating": 4.9, "release_date": "2023-04-12"
| # | course_id | title | category | sub_category | instructor_name | instructor_id |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Instructor Profiles objects from creativelive.com. All fields typed and schema-versioned.
"instructor_id": "jg-992", "name": "John Greengo", "total_students": 380492, "course_count": 14, "average_rating": 4.9, "areas_of_expertise": "['Photography', 'Camera Gear', 'Lighting']", "website_url": "https://johngreengo.com", "social_links": "['instagram.com/johngreengo']"
| # | instructor_id | name | bio | profile_image_url | website_url | social_links |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Lesson Syllabi objects from creativelive.com. All fields typed and schema-versioned.
"lesson_id": "ls-8419", "course_id": "cl-ph-102", "module_name": "Camera Basics", "lesson_title": "Understanding Shutter Speed", "duration_seconds": 1245, "is_free_preview": true, "sequence_number": 3, "resource_links": "['shutter_speed_cheat_sheet.pdf']"
| # | lesson_id | course_id | module_name | lesson_title | duration_seconds | is_free_preview |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Subscriptions objects from creativelive.com. All fields typed and schema-versioned.
"course_id": "cl-ph-102", "single_class_price": 99.0, "creator_pass_eligible": true, "discount_active": true, "discount_expiry": "2026-11-30T23:59:59Z", "currency": "USD", "bundle_options": "['Photography Starter Kit']", "bundle_price": 149.0
| # | course_id | single_class_price | creator_pass_eligible | discount_active | discount_expiry | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from creativelive.com. All fields typed and schema-versioned.
"review_id": "rv-91823", "course_id": "cl-ph-102", "student_name": "Sarah Jenkins", "rating": 5, "review_text": "The most comprehensive breakdown of exposure I have seen.", "date_posted": "2026-02-14", "helpful_votes": 42, "verified_purchase": true
| # | review_id | course_id | student_name | rating | review_text | date_posted |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline captures course hierarchies, instructor metadata, deep lesson structures, and dynamic pricing models — bypassing frontend rendering layers to deliver structured data.
Title, description, student counts, aggregate ratings, release dates, and skill levels extracted for every course.
Scrape instructor bios, social handles, total student reach, course portfolios, and aggregate ratings.
Map module hierarchies, individual lesson titles, duration in seconds, and free-preview eligibility flags.
Track single-class pricing, discount events, bundle offers, and Creator Pass subscription eligibility.
Extract paginated student reviews, star ratings, helpful votes, and verified purchase indicators.
Reconstruct CreativeLive's internal category trees, sub-categories, and specific skill tags.
Capture video lengths, resolution availability, and closed-caption language support flags.
Extract localised pricing structures across different geographic regions using targeted proxy nodes.
Run one-off bulk exports or configure continuous pipelines at weekly or daily cadences.
Brief in. Clean data out.
Provide target categories, instructor lists, or full catalogue requirements. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for creativelive.com.
Schema validation, null-rate checks, and data type normalisation before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
CreativeLive relies on modern JavaScript frameworks. Here is how we extract structured data reliably without brittle DOM parsing.
Rather than relying on fragile CSS selectors, our crawlers intercept the underlying JSON state payloads used to hydrate the frontend application. This yields cleaner data, captures hidden metadata fields, and survives cosmetic UI updates.
We utilise residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass rate limits and automated scraping defences.
When state extraction is insufficient, we deploy multiple fallback chains per field — CSS selectors, XPath, and structured data extraction (LD+JSON) — ensuring continuous data flow.
We maintain a hash index of last-seen values per field. 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, schema drift, and coverage drops before data reaches your warehouse.
Platform operators track course release velocity, pricing models, and category expansion to benchmark against CreativeLive.
Course creators and production studios analyse student counts and review volumes to identify high-demand, low-supply educational niches.
Competing platforms identify top-performing instructors based on aggregate ratings and student enrolments for recruitment.
Analysts track single-class price points versus Creator Pass adoption indicators to optimise their own subscription pricing tiers.
Investors monitor review velocity across specific categories (e.g., Photography vs Audio) to gauge shifts in creative industry demand.
Enterprise L&D platforms ingest course syllabi and metadata to index external learning resources for internal employee portals.
"CreativeLive holds a premium catalogue of creative education metadata. Accessing its taxonomy, pricing history, and instructor metrics requires dedicated extraction infrastructure."
Extracting structured data from modern single-page applications requires more than basic HTTP requests. It demands state-hydration interception, proxy rotation, and continuous schema monitoring. DataFlirt manages the entire extraction lifecycle, delivering clean, warehouse-ready data so your engineering team can focus on product development.
Everything supported by our creativelive.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, state interception, and interaction flows.
We maintain pools of 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. State is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About creativelive.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated course metadata, instructor profiles, and pricing data. We do not extract personal user data or circumvent authentication walls. Clients should review terms of service and consult legal counsel for specific use cases.
No. DataFlirt extracts structured metadata (titles, durations, descriptions, pricing). We do not download, host, or distribute proprietary video content or copyright-protected media files.
We monitor application state structures and deploy multi-layer fallback chains in our selectors. We monitor for null-rate spikes in real time and patch extraction logic automatically when the frontend application updates.
Full catalogue refreshes at weekly or daily cadences complete within a 2-6 hour window depending on scale. Incremental runs for pricing changes operate faster via targeted category crawling.
We capture the current price and any active discount logic during the crawl. By running the pipeline continuously, you build a proprietary time-series database of price fluctuations over time.
Our minimum engagement typically starts with a full catalogue extraction with weekly updates. Contact us with your specific data requirements for a scoped quote.
Yes. We provide a sample run of up to 100 courses or specific instructor profiles during the pre-engagement scoping process to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue export or a continuous competitor tracking feed — we scope, build, and operate the pipeline. Tell us what you need.
