We extract course structures, pricing models, creator profiles, and landing page copy from Kajabi sites. 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 Listings objects from kajabi.com. All fields typed and schema-versioned.
"course_id": "KJB-9921", "title": "Advanced Python Mastery", "creator_name": "TechEdu Pro", "total_lessons": 42, "difficulty_level": "Intermediate", "category": "Programming"
| # | course_id | title | creator_name | category | description | syllabus_modules |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Offers objects from kajabi.com. All fields typed and schema-versioned.
"offer_id": "OFF-331", "price": 199.0, "currency": "USD", "billing_frequency": "monthly", "trial_days": 14, "is_bundle": false
| # | offer_id | course_id | price | currency | billing_frequency | trial_days |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Creator Profiles objects from kajabi.com. All fields typed and schema-versioned.
"creator_id": "CR-554", "name": "Jane Doe", "total_courses": 5, "active_students_estimate": 12000, "website_url": "https://janedoe.com", "bio": "Expert in digital marketing."
| # | creator_id | name | bio | social_links | total_courses | active_students_estimate |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Syllabus & Modules objects from kajabi.com. All fields typed and schema-versioned.
"module_id": "MOD-12", "module_title": "Introduction to APIs", "module_order": 1, "lesson_count": 5, "total_duration_minutes": 45, "preview_available": true
| # | module_id | course_id | module_title | module_order | lesson_count | total_duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Testimonials & Reviews objects from kajabi.com. All fields typed and schema-versioned.
"review_id": "REV-998", "reviewer_name": "Alex Smith", "rating": 5, "review_text": "Life changing course.", "review_date": "2023-10-12", "verified_student": true
| # | review_id | course_id | reviewer_name | rating | review_text | review_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Kajabi scraper targets creator domains and subdomains to extract course metadata, pricing configurations, syllabus structures, and marketing copy. Built with proxy rotation and dynamic rendering to handle custom themes.
Extract titles, descriptions, categories, and thumbnail images across Kajabi creator storefronts.
Capture one-time payments, subscriptions, payment plans, trial periods, and bundle structures.
Scrape module titles, lesson counts, duration estimates, and preview availability without logging in.
Gather creator bios, social media links, aggregate course counts, and contact information.
Extract structured text from custom Kajabi landing pages for marketing analysis and SEO research.
Parse RSS feeds, episode descriptions, and blog posts hosted on the Kajabi platform.
Extract featured reviews, student names, and ratings displayed on course sales pages.
Automatically identify and scrape Kajabi instances hosted on custom creator domains.
Configure daily or weekly runs to track pricing changes and new course launches across target creators.
Brief in. Clean data out.
Provide target Kajabi domains or creator names. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, handle custom theme variations, and manage routing.
Schema validation, null-rate checks, and data normalisation across different creator layouts.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage.
Kajabi allows creators to heavily customise their storefront themes. Here is how we maintain schema stability across thousands of unique layouts.
Kajabi creators use varied templates (Encore, Premier). Our selector strategy abstracts layout differences, mapping custom DOM structures into a unified relational schema.
Pricing toggles and dynamic syllabus accordions require JavaScript execution. We run headless Playwright sessions to trigger state changes and extract hidden payload data.
Many creators use white-labelled domains instead of mykajabi.com. We identify underlying Kajabi infrastructure via header analysis and apply the correct extraction logic.
Aggressive crawling of a single creator site triggers WAF blocks. We distribute requests across ISP proxies and enforce domain-specific concurrency limits.
We hash course and pricing records. Subsequent pipeline runs only emit data when a creator alters a price, adds a module, or updates landing page copy.
Analyse pricing strategies, popular course topics, and curriculum structures across the creator economy.
Creators and agencies monitor rival course launches, bundle offers, and syllabus updates.
B2B service providers identify successful course creators for targeted outreach and tool upselling.
Marketing teams analyse high-converting landing page copy and module structures to inform their own launches.
Track the distribution of one-time payments versus subscription models within specific educational niches.
Investment firms track platform adoption, creator growth metrics, and course proliferation.
"Kajabi powers the creator economy, but its data is fragmented across thousands of custom domains. We unify it into a single queryable dataset."
Extracting data from Kajabi requires navigating hundreds of custom themes, dynamic pricing toggles, and white-labelled domains. DataFlirt normalises this fragmentation. We handle the DOM variations, JavaScript rendering, and proxy management so your team receives clean, structured records ready for immediate analysis.
Everything supported by our kajabi.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.
We build abstract selector layers that map varied Kajabi storefront themes into a strict relational schema, preventing pipeline breakage when creators update their sites.
Playwright instances execute JavaScript to trigger pricing toggles and expand syllabus accordions, ensuring no hidden data is missed during the crawl.
Requests are distributed across residential proxy pools to respect per-domain rate limits while maintaining high aggregate throughput across thousands of creator sites.
Data delivered to where your team already works — no new tooling required.
About kajabi.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We automatically detect underlying Kajabi infrastructure via HTTP headers and DOM signatures, applying the correct extraction logic regardless of the domain name.
Kajabi offers multiple themes and heavy customisation. Our pipelines use abstract selector strategies and fallback chains to normalise data across different layouts into a single, predictable schema.
No. Course videos, private community discussions, and student progress metrics are gated behind authentication and paywalls. We only extract publicly accessible storefront, pricing, and syllabus data.
Yes. We extract all available offers, including one-time payments, monthly subscriptions, multi-pay plans, and bundle configurations.
We use Playwright to render the page and simulate user interactions, expanding all syllabus modules to extract complete lesson lists and duration estimates.
We do not maintain a global directory of all Kajabi sites. You must provide the target URLs, domains, or search parameters to define the extraction scope.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you are tracking competitor pricing or building an EdTech market map, we deliver the structured data you need. Scope your pipeline with us.
