How do I connect Hotmart to BigQuery without coding?

Kondado provides a no-code interface where you authenticate your Hotmart account and select BigQuery as your destination. The platform handles the schema mapping and data type conversion automatically, creating optimized datasets in your Google Cloud project without requiring SQL knowledge or API configuration.

What Hotmart data can I replicate to BigQuery?

You can replicate 11 distinct pipelines including Subscribers, Sales Commissions, Subscription Transactions, and Hotmart Club data covering students, modules, and progress tracking to BigQuery . This encompasses 202 fields across subscription records, transaction histories, product catalogs, and educational content engagement metrics.

How often does Hotmart data update in BigQuery?

Kondado updates your BigQuery datasets on a configurable schedule ranging from every 5 minutes to daily intervals, depending on your analytics requirements. You can set different frequencies for different pipelines, such as near-real-time updates for Sales Commissions and daily refreshes for historical Student Progress data.

Can I combine Hotmart data with other marketing platforms in BigQuery?

Yes, BigQuery serves as a central warehouse where Hotmart sales data can join with advertising spend from Facebook Ads, Google Ads, or email campaign metrics from other sources. This enables unified reporting across your entire funnel, from ad impression to Hotmart subscription conversion.

What format does Hotmart data arrive in BigQuery?

Data arrives as structured tables with preserved relationships between subscribers, transactions, and products, maintaining data types for currency values, dates, and status codes. Kondado automatically handles nested JSON structures from the Hotmart API, flattening them into query-ready schemas optimized for Looker Studio connectivity.

Do I need a Hotmart API key to set up the pipeline?

Yes, you will need to generate API credentials from your Hotmart account settings to establish the initial connection. Kondado guides you through this one-time authentication process, after which the platform manages token refresh and data extraction automatically.

Can I track Hotmart Club student progress in BigQuery?

Yes, the Hotmart Club: Student Progress pipeline replicates completion percentages, module IDs, and subscriber codes, allowing you to analyze learning velocity and course abandonment points. Combine this with the Hotmart Club: Modules pipeline to correlate specific content difficulty with student retention rates.

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Send Hotmart Data to BigQuery

Hotmart creators and digital entrepreneurs need centralized data to track subscription performance and sales commissions across their entire product portfolio. Replicating your Hotmart data to BigQuery enables comprehensive analytics on student progress, transaction history, and revenue breakdowns without manual CSV exports or spreadsheet maintenance. Kondado automates this data flow directly, allowing you to focus on optimizing your digital courses and membership content rather than managing fragmented data sources.

Kondado replicates data from Hotmart to BigQuery on a configurable schedule, offering 11 pipelines including Subscribers, Sales Commissions, and Hotmart Club progress data, enabling automated analytics without coding.

Once your data arrives in BigQuery, you can combine Hotmart sales records with marketing data from advertising platforms to calculate precise customer acquisition costs and lifetime value metrics. The automated updates ensure your financial reports, affiliate commission dashboards, and student engagement trackers always reflect current subscription statuses and completion rates. You can then visualize this unified data in Looker Studio or Power BI to share insights with your team.

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The Subscribers pipeline delivers detailed subscription records including subscriber codes and status changes directly into your BigQuery warehouse, enabling cohort analysis of churn patterns and retention rates across your digital courses. Meanwhile, the Sales Commissions pipeline captures transaction-level commission data with user identifiers, allowing you to calculate affiliate payouts and revenue shares automatically within your SQL queries.

For educators using Hotmart Club, the Student Progress pipeline tracks completion percentages and module engagement, giving you granular visibility into learning outcomes. By combining these datasets in BigQuery, you can correlate subscription longevity with course completion rates, identify high-value student segments, and build custom dashboards in Looker Studio or Power BI that update automatically as new data flows in.

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Hotmart data available for BigQuery

available pipelines

202

extractable fields

Available integrations

Integration	Description
Subscribers	Records of subscriptions include subscriber_code, subscriber_name, and status, allowing detailed analysis of active and canceled subscriptions.
Sales Commissions	Commission details include transaction, commission_value, and user_name, providing a clear view of commissions generated by each transaction.
Subscriber Purchases	Data on purchases includes subscriber_code, product_id, and price_value, allowing tracking of acquisitions made by subscribers.
Sales Price Breakdown	Detailed pricing information includes product_id, price_value, and price_currency_code, facilitating analysis of sales prices.
Sales History	Sales records include purchase_transaction, product_id, and request_date, allowing analysis of transaction history.
Hotmart Club: Students	Information about students includes subscriber_name, product_id, and status, allowing tracking of students' progress in the club.
Hotmart Club: Modules	Data on modules includes product_id, module_name, and completion_status, allowing analysis of students' progress in each module.
Hotmart Club: Student Progress	Progress records include subscriber_code, module_id, and completion_percentage, facilitating monitoring of students' performance.
Hotmart Club: Pages	Information about pages includes page_id, access_count, and last_access_date, allowing analysis of student engagement.
Products	Product data includes product_id, product_name, and price_value, allowing detailed analysis of the available product portfolio.
Subscription Transactions	Records of subscription transactions, including fields such as transaction code, product ID, and commission value.

Subscribers

Records of subscriptions include subscriber_code, subscriber_name, and status, allowing detailed analysis of active and canceled subscriptions.

Sales Commissions

Commission details include transaction, commission_value, and user_name, providing a clear view of commissions generated by each transaction.

Subscriber Purchases

Data on purchases includes subscriber_code, product_id, and price_value, allowing tracking of acquisitions made by subscribers.

Sales Price Breakdown

Detailed pricing information includes product_id, price_value, and price_currency_code, facilitating analysis of sales prices.

Sales History

Sales records include purchase_transaction, product_id, and request_date, allowing analysis of transaction history.

Hotmart Club: Students

Information about students includes subscriber_name, product_id, and status, allowing tracking of students' progress in the club.

Hotmart Club: Modules

Data on modules includes product_id, module_name, and completion_status, allowing analysis of students' progress in each module.

Hotmart Club: Student Progress

Progress records include subscriber_code, module_id, and completion_percentage, facilitating monitoring of students' performance.

Hotmart Club: Pages

Information about pages includes page_id, access_count, and last_access_date, allowing analysis of student engagement.

Products

Product data includes product_id, product_name, and price_value, allowing detailed analysis of the available product portfolio.

Subscription Transactions

Records of subscription transactions, including fields such as transaction code, product ID, and commission value.

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How to send Hotmart data to BigQuery

Sync data automatically — no code, no manual exports.

Connect your Hotmart account

Authenticate your Hotmart data source by entering your API credentials in Kondado's connection interface, granting access to your subscription and sales data.

Configure BigQuery destination

Select BigQuery as your warehouse and specify your Google Cloud project ID and dataset location where the Hotmart pipelines will be stored.

Select pipelines and schedule

Choose from the 11 available Hotmart pipelines such as Subscribers and Sales Commissions, then set your preferred update frequency ranging from 5 minutes to daily intervals.

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