We extract course listings, digital download pricing, creator profiles, and curriculum structures from Podia storefronts. 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 Creator Profiles objects from podia.com. All fields typed and schema-versioned.
"creator_id": "podia_cr_84921", "name": "Jane Doe Design", "bio": "UI/UX Designer and educator.", "storefront_url": "https://design.janedoe.com", "custom_domain": true, "total_products": 12, "scraped_at": "2026-05-12T09:14:00Z"
| # | creator_id | name | bio | storefront_url | custom_domain | avatar_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Course Listings objects from podia.com. All fields typed and schema-versioned.
"course_id": "crs_99214A", "title": "Advanced Figma Prototyping", "creator_id": "podia_cr_84921", "price": 149.0, "currency": "USD", "module_count": 8, "lesson_count": 42
| # | course_id | title | creator_id | price | currency | payment_plans |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Digital Downloads objects from podia.com. All fields typed and schema-versioned.
"download_id": "dl_48192X", "title": "Wireframe UI Kit 2.0", "creator_id": "podia_cr_84921", "price": 29.0, "currency": "USD", "file_type": "Figma File", "included_files": 3
| # | download_id | title | creator_id | price | currency | file_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Memberships objects from podia.com. All fields typed and schema-versioned.
"community_id": "com_11294", "title": "Design Innovators Club", "tier_name": "Pro Member", "monthly_price": 15.0, "annual_price": 150.0, "currency": "USD", "features": "['Weekly Q&A', 'Resource Library']"
| # | community_id | title | creator_id | tier_name | monthly_price | annual_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Curriculum Structure objects from podia.com. All fields typed and schema-versioned.
"module_id": "mod_8841", "course_id": "crs_99214A", "module_title": "Introduction to Variables", "lesson_title": "Setting up your first variable", "is_preview_available": true, "content_type": "video", "order_index": 1
| # | module_id | course_id | module_title | lesson_title | is_preview_available | content_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Podia scraper navigates custom creator domains, complex product bundles, and varied payment structures to deliver uniform data across thousands of independent storefronts.
Capture creator names, bios, social links, and total product counts across the platform or targeted storefront lists.
Extract full course structures including module names, lesson titles, preview availability, and content types.
Map complex pricing structures including one-time payments, monthly installments, and subscription tiers in local currencies.
Catalogue digital products, eBooks, templates, and software files with their associated pricing and descriptions.
Extract public community tiers, monthly vs annual pricing options, and listed membership benefits.
Resolve product bundles to their individual component courses and downloads to calculate implied discounts.
Podia allows creators to use custom domains. We trace and extract data seamlessly across standard podia.com subdomains and custom URLs.
Track upcoming and past webinars, including scheduled dates, registration prices, and embedded promotional content.
Monitor competitor storefronts continuously. Receive updates only when new courses are launched or prices change.
Brief in. Clean data out.
Provide lists of Podia subdomains, custom creator URLs, or specific product categories. We design the extraction schema.
We configure crawlers to handle Podia's dynamic rendering, custom domain routing, and varied storefront layouts.
Schema validation ensures complex payment plans and curriculum structures map correctly to your database.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting data from an all-in-one creator platform requires navigating varied user-generated structures and custom domains. Here is how we ensure data quality.
Many Podia creators use custom domains rather than podia.com subdomains. Our pipeline identifies the underlying Podia platform structure and applies the correct extraction logic regardless of the top-level domain.
Creators offer one-time payments, multi-month installments, and recurring subscriptions. We normalise these varied pricing models into a structured, queryable format across all currencies.
Podia storefronts rely heavily on JavaScript for checkout modals, curriculum expansion, and dynamic pricing toggles. We use Playwright to fully render pages and trigger necessary DOM events.
Creator descriptions and course structures vary wildly. Our parsers clean HTML, strip inline styling, and normalise text blocks to ensure your database receives clean, uniform records.
We maintain state on previously scraped storefronts. When a creator launches a new product or updates pricing, our diffing engine flags the exact changes, reducing your processing overhead.
Analysts aggregate course structures and pricing models to understand trends in the independent education market.
EdTech platforms monitor independent creator pricing strategies, payment plans, and bundle discounts.
SaaS companies building tools for creators identify high-volume sellers and active community managers.
Marketplaces aggregate public metadata for digital downloads and courses to build comprehensive learning directories.
PE firms evaluate the growth of the creator economy by tracking the proliferation of new storefronts and product launches.
Researchers map the taxonomy of digital products, comparing the volume of design assets versus coding tutorials.
"Podia hosts a massive repository of independent creator knowledge and pricing strategies — but extracting it requires navigating dynamic storefronts and complex product bundles."
Most teams underestimate the investment required: reliable Podia scraping requires rendering creator-customised storefronts, handling varied payment plan structures, and maintaining selectors across custom domains. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our podia.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, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across IN/US/UK/DE regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 podia.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 storefront, pricing, and curriculum data. We do not extract personal data of students, circumvent authentication walls, or download paid course content. Clients should review Podia's ToS and consult legal counsel for specific use cases.
Yes. Our pipeline identifies Podia's underlying platform structure, allowing us to extract data uniformly regardless of whether the creator uses a podia.com subdomain or a completely custom URL.
No. We only extract publicly visible metadata — such as course titles, curriculum outlines, pricing, and public community tier descriptions. We do not bypass paywalls or login screens to access gated video content or private discussions.
Our schema is designed to capture multiple pricing arrays per product. We extract one-time fees, multi-month installment plans, and recurring subscriptions separately, and we map bundled products to their individual component IDs.
For targeted competitor monitoring, we can configure daily or weekly pipeline runs to detect new product launches or price adjustments. Full historical snapshots are available from the day your pipeline is commissioned.
Absolutely. We provide a sample run of up to 100 creator storefronts as part of the pre-engagement scoping process — so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off extraction of course curriculums or continuous monitoring of creator pricing strategies — we scope, build, and operate the pipeline. Tell us what you need.
