We extract course structures, practice questions, pricing updates, and study schedules from Magoosh. 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 Catalog objects from magoosh.com. All fields typed and schema-versioned.
"course_id": "mg-gre-premium", "exam_type": "GRE", "title": "GRE Premium", "price_6_month": 179.0, "guarantee_score": "+5 Total", "video_count": 1200, "practice_question_count": 1700, "rating": 4.8
| # | course_id | exam_type | title | description | price_1_month | price_6_month |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Practice Questions objects from magoosh.com. All fields typed and schema-versioned.
"question_id": "q-gre-math-492", "exam_type": "GRE", "subject": "Quantitative", "difficulty": "Hard", "question_text": "If x + y = 14 and x - y = 4, what is the value of x * y?", "correct_answer": "45", "explanation_text": "Solve the system of equations. Add them to get 2x = 18, so x = 9. Then y = 5. 9 * 5 = 45."
| # | question_id | exam_type | subject | difficulty | question_text | options |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Study Schedules objects from magoosh.com. All fields typed and schema-versioned.
"schedule_id": "gmat-1-month-daily", "exam_type": "GMAT", "duration_weeks": 4, "target_audience": "Working professionals", "total_hours": 80, "author": "Mike McGarry", "last_updated": "2023-08-14"
| # | schedule_id | exam_type | duration_weeks | target_audience | daily_tasks | total_hours |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Plans objects from magoosh.com. All fields typed and schema-versioned.
"plan_id": "toefl-6-month", "exam_type": "TOEFL", "plan_name": "Premium 6-Month", "billing_cycle": "One-time", "price": 129.0, "discount_pct": 20, "score_guarantee": "+4 points", "scraped_at": "2023-11-02T14:32:00Z"
| # | plan_id | exam_type | plan_name | billing_cycle | price | discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Blog & SEO Content objects from magoosh.com. All fields typed and schema-versioned.
"post_id": "blog-gre-vocab-flashcards", "url": "https://magoosh.com/gre/gre-vocabulary-flashcards/", "title": "Top 1000 GRE Vocabulary Words", "author": "Chris Lele", "publish_date": "2023-01-15", "category": "GRE Vocabulary", "word_count": 2450
| # | post_id | url | title | author | publish_date | category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Magoosh pipeline captures course structures, pricing variations, and public study materials. We handle the dynamic React components and pagination logic so you receive clean, structured records.
Extract comprehensive metadata for every exam type including GRE, GMAT, LSAT, and MCAT. Capture video counts, practice question volumes, and score guarantees.
Monitor subscription costs, billing cycles, discount percentages, and promotional offers across all test prep categories.
Parse public practice questions, multiple-choice options, difficulty ratings, correct answers, and text explanations.
Extract structured daily and weekly study plans, including recommended hours, target audiences, and required materials.
Capture full text, author metadata, publish dates, and categorisation from the Magoosh blog for SEO and content analysis.
Collect data on course authors, their credentials, test scores, and associated subject specialisations.
Extract public student testimonials, reported score improvements, and star ratings from course landing pages.
Identify updates to course syllabi, new blog posts, or pricing adjustments with hash-based diffing on subsequent runs.
Track localised pricing and currency variations by routing requests through specific regional proxy pools.
Brief in. Clean data out.
Provide the specific exams, blog categories, or pricing pages you need. We design the extraction schema to match your requirements.
We configure Playwright crawlers, proxy rotation, and session management to navigate Magoosh's React-based frontend.
We test the schema against multiple exam categories to ensure field consistency and low null rates before full execution.
JSON, CSV, or Parquet files pushed to your AWS S3 bucket, BigQuery dataset, or Snowflake stage on your defined cadence.
Educational platforms use aggressive caching and dynamic rendering. We manage the extraction infrastructure so you get reliable data.
Magoosh relies on React for rendering course details, pricing toggles, and practice question interfaces. We use full browser automation to execute JavaScript and capture the final DOM state.
EdTech sites frequently run A/B tests on pricing and landing page layouts. Our proxy rotation and session management ensure we capture baseline data while flagging experimental UI variants.
The Magoosh blog contains thousands of posts across complex category structures. Our crawlers systematically traverse pagination and tag archives to ensure total content coverage.
The layout for GRE prep often differs entirely from LSAT or MCAT pages. We maintain specific selector chains for each exam category to prevent data loss when templates diverge.
We route requests through ISP-grade residential proxies with realistic browser fingerprints to bypass basic rate limiting and WAF blocks.
EdTech companies monitor Magoosh subscription tiers, discount frequencies, and billing models to adjust their own pricing strategies.
Marketing teams analyse Magoosh blog output, keyword targeting, and publication velocity to inform their own test prep content calendars.
Analysts track the addition of new exam categories and course features to measure market expansion and product development trends.
Course comparison websites ingest Magoosh syllabi, pricing, and review data to populate their directories automatically.
Researchers extract public practice questions and study schedules to analyse pedagogical approaches in standardised test preparation.
Machine learning teams use structured explanations and question formats to fine-tune educational language models.
"Magoosh holds a massive repository of structured test prep metadata and pricing signals, but extracting it requires a system built for dynamic educational platforms."
EdTech platforms deploy aggressive caching and varied DOM structures across different exam categories. DataFlirt manages the residential proxies, JavaScript rendering, and schema normalisation so your data engineering team receives clean, query-ready records without maintaining brittle scrapers.
Everything supported by our magoosh.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 manages the crawl orchestration and deduplication. Playwright handles the React component rendering and dynamic interaction required by modern EdTech platforms.
We utilise ISP-grade residential proxies to prevent IP bans and access geographically specific pricing data without triggering bot detection.
Pipelines execute on AWS Lambda and ECS. Apache Airflow manages scheduling and dependencies, ensuring reliable data delivery on your specified cadence.
Data delivered to where your team already works — no new tooling required.
About magoosh.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information, such as course pricing, public blog posts, and free practice questions, is generally permissible. DataFlirt extracts only unauthenticated data and does not bypass login walls to access proprietary video content or user data.
We use Playwright to execute JavaScript and render the full DOM before extraction. This ensures we capture data that relies on client-side hydration, such as dynamic pricing toggles and interactive question components.
We can extract data across all Magoosh verticals, including GRE, GMAT, TOEFL, SAT, ACT, LSAT, MCAT, and IELTS. We maintain specific selector schemas for each category.
No. We extract metadata about the videos (titles, durations, descriptions) available on public course pages. We do not extract or download proprietary video files gated behind user authentication.
Pipelines can be configured for daily, weekly, or monthly runs depending on your requirements. Pricing and course catalog updates are typically captured within 24 hours of execution.
Our minimum engagement typically starts with a defined extraction scope, such as the complete pricing matrix or the entire blog archive, delivered on a weekly or monthly cadence.
Yes. We offer a sample extraction of specific course pages or blog categories to validate the schema and data quality before finalising the pipeline configuration.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need competitive pricing intelligence or a complete extraction of public study materials, we build and manage the infrastructure. Tell us your requirements.
