How does Kondado replicate Hotmart data to PostgreSQL ?

Kondado uses a direct integration to extract data from your Hotmart account and load it into your PostgreSQL database on a configurable schedule. The platform handles API authentication, data transformation, and schema management automatically, delivering structured data to your PostgreSQL instance without requiring manual CSV exports or custom scripts.

What specific Hotmart data can I replicate to PostgreSQL ?

You can replicate 11 different pipelines including Subscribers, Sales Commissions, Subscription Transactions, and Hotmart Club data covering students, modules, and progress tracking. Each pipeline delivers specific fields such as subscriber codes, transaction values, completion percentages, and product details directly into your PostgreSQL tables.

How frequently does Hotmart data update in PostgreSQL ?

You can configure update schedules to run as frequently as every five minutes or extend intervals to hourly or daily depending on your analytics needs. This automated scheduling ensures your PostgreSQL database stays current with your latest Hotmart sales and subscription activities without manual refreshes.

What format does Hotmart data take when it arrives in PostgreSQL ?

Hotmart data arrives as structured relational tables within your PostgreSQL database, with each pipeline creating dedicated tables containing normalized fields like subscriber_code, transaction_id, and product_name. This format allows you to write standard SQL queries, create views, and join Hotmart data with information from other sources stored in your PostgreSQL warehouse.

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

Yes, once Hotmart data resides in PostgreSQL, you can join it with data from additional sources, creating unified customer views and comprehensive revenue analytics. Many users combine Hotmart subscription data with advertising spend information to calculate true customer acquisition costs and lifetime value metrics within their PostgreSQL environment.

Which Hotmart pipelines track student engagement and course progress?

The Hotmart Club section includes four specific pipelines: Students, Modules, Student Progress, and Pages, which track enrollment status, module completion rates, progress percentages, and page access counts. These pipelines enable you to analyze learning outcomes, identify at-risk students, and correlate educational engagement with subscription retention in your PostgreSQL analytics environment.

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Send Hotmart Data to PostgreSQL Automatically

Sending Hotmart data to PostgreSQL requires a direct integration that automates the extraction and loading of your digital commerce information. Kondado provides a no-code solution that connects your Hotmart account to PostgreSQL, allowing you to replicate sales, subscription, and student progress data without manual exports or complex API configurations. Simply authenticate your Hotmart credentials, select the pipelines you need, and configure your destination database to start automated data flows that keep your analytics current.

Kondado replicates Hotmart data to PostgreSQL on a configurable schedule, offering 11 different pipelines including Subscribers, Sales Commissions, and Hotmart Club progress data, enabling automated analysis of your digital product business within your PostgreSQL environment.

Once your data arrives in PostgreSQL, you can build custom reports, combine Hotmart information with other business data sources, and create analytics workflows that track subscription revenue, student engagement, and sales performance across your digital products. The platform supports automated updates with intervals as frequent as every five minutes, ensuring your PostgreSQL database reflects the latest transactions and subscriber activities from your Hotmart store without manual intervention.

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The Subscribers and Subscription Transactions pipelines deliver comprehensive subscription data to your PostgreSQL database, enabling you to analyze recurring revenue patterns, churn rates, and subscriber lifetime value using SQL queries. Combine this with the Hotmart Club: Student Progress pipeline to correlate subscription payments with actual course completion rates, identifying which content drives retention and revenue.

With Sales Commissions and Sales History pipelines in PostgreSQL, you can calculate net profitability per transaction, track affiliate performance over time, and build financial dashboards that update automatically as new sales occur. This data foundation supports advanced analytics when connected to visualization tools like Power BI or Looker Studio, or when merged with marketing data from other platforms in your PostgreSQL warehouse.

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Hotmart data available for PostgreSQL

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 PostgreSQL

Sync data automatically — no code, no manual exports.

Connect Hotmart to Kondado

Authenticate your Hotmart credentials in Kondado to establish the data source connection, granting access to your sales, subscription, and student data without writing API code.

Configure PostgreSQL Destination

Enter your PostgreSQL connection details including host, database name, and credentials to establish the target location where your Hotmart data will replicate.

Select Pipelines and Schedule

Choose from 11 available Hotmart pipelines such as Subscribers or Sales Commissions, then set your preferred update frequency from five minutes to daily intervals to automate data replication to PostgreSQL.

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