From ChatGPT Ads to PostgreSQL: managed, scheduled, no code.
Creating a pipeline that sends data from ChatGPT Ads to PostgreSQL databases takes only a few minutes with Kondado. And the whole integration from ChatGPT Ads to PostgreSQL is managed and executed by our platform. With Kondado, you can focus on extracting value from ChatGPT Ads data and combining it with other data in your PostgreSQL database
How to send ChatGPT Ads data to PostgreSQL? Kondado provides a direct integration that replicates advertising metrics from OpenAI’s platform into your open-source database without requiring extraction scripts or manual CSV uploads. You select the exact pipelines you need, define an update interval that matches your operational rhythm, and let the platform handle the structured delivery of campaign data into your existing schema. Whether your team needs near-real-time refreshes for intraday spend pacing or daily batches for consolidated reporting, Kondado moves your ChatGPT Ads metrics on a configurable schedule so analysts can focus on insight generation rather than data preparation.
Kondado replicates 8 ChatGPT Ads pipelines covering 144 fields, including ad registries, campaign settings, ad group targeting, performance metrics, conversion events, account details, ad previews, and custom audiences, directly into PostgreSQL on a configurable schedule.
With the Ad performance pipeline in PostgreSQL, analysts can build custom SQL models that join daily spend and conversion data across campaigns to calculate true ROAS by product or country. The Campaigns and Ad groups pipelines deliver targeting parameters, bidding strategies, and budget limits that let finance teams audit pacing against planned flight dates directly inside the database. By keeping these datasets together in PostgreSQL, you can cross-reference creative status from the Ads pipeline with click-through rates to quickly identify which headlines, body copy, or destination URLs drive the most efficient traffic.
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Replicated to PostgreSQL
ChatGPT Ads data available for PostgreSQL
Tables Kondado writes into your PostgreSQL, on a schedule you control.
8
available pipelines
144
extractable fields
PostgreSQL
Destination
Available integrations
Ads
Registry of the account's ads, with the parent ad group and campaign, status and review outcome, creative format and copy (headline, body, price and destination URL with tracking parameters), and the reasons an ad is not serving.
Campaigns
Registry of campaigns, with objective, bidding strategy, billed event, start and end windows, daily and lifetime spend limits in the account currency, product catalog, and countries included in targeting.
Conversion event settings
Conversion events configured on the account, with type, the sources that feed them (pixels or integrations), associated campaigns, and the click-through and view-through attribution windows.
Ad account
Details of the connected ad account: name, main website, status and review, the time zone that defines how report days are cut, and the currency every monetary value in this connector is expressed in.
Ad groups
Registry of ad groups, with the parent campaign, status, context signals used for targeting, associated product feed, bidding strategy, billed event, and maximum bid in the account currency.
Ad performance
Performance report grouped by hour, day or month at account, campaign, ad group or ad level, with impressions, clicks, spend, CTR, CPC, CPM, conversions, CPA, ROAS and attributed sales, plus breakdowns by product, country, device or platform.
Ad preview
Renderable preview of each ad: an HTML snippet with the creative's iframe and the moment the preview was generated — the address inside the iframe expires 24 hours later.
Custom audiences
Registry of custom audiences, with status, hash specification version, and the ranges of uploaded, matched and invalid identifiers — for privacy the API returns text ranges, never the exact count.
Sync data automatically — no code, no manual exports.
1
Authenticate ChatGPT Ads on Kondado
Log in to Kondado and add ChatGPT Ads as a new data source by entering your API credentials, then grant the permissions needed to read campaign registries and performance metrics.
2
Configure PostgreSQL Destination
Enter your PostgreSQL host, database name, and credentials in the destination settings so Kondado knows exactly where to deliver the replicated datasets.
3
Select Pipelines and Schedule
Choose the ChatGPT Ads pipelines you want to replicate, such as Ad performance or Campaigns, and set your preferred update interval to keep PostgreSQL current on a configurable schedule.
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Answers about sending ChatGPT Ads data to PostgreSQL automatically
How does Kondado send ChatGPT Ads data into PostgreSQL?▼
Kondado uses a direct integration with the ChatGPT Ads API to extract the pipelines you select and load them into your PostgreSQL destination. The platform handles schema creation and data type mapping automatically, so metrics like impressions, spend, and conversions arrive as properly typed columns ready for querying. You control which pipelines run and how frequently they update without managing any extraction code yourself.
What specific ChatGPT Ads metrics and registries can I pull into PostgreSQL?▼
You can pull time-series metrics from the ChatGPT Ads Ad performance pipeline broken down by hour, day, or month with dimensions like country, device, and platform. The Campaigns and Ad groups pipelines include budget limits, bidding strategies, and targeting contexts, while the Ads pipeline stores creative copy, review status, and destination URLs for full-funnel analysis.
How frequently does ChatGPT Ads data update in PostgreSQL?▼
Kondado runs updates on a configurable schedule that you define, with intervals ranging from every 5 minutes up to daily or longer depending on your reporting needs. This lets marketing teams maintain near-real-time spend visibility for active pacing while keeping historical conversion metrics synchronized without manual intervention.
How is ChatGPT Ads data structured inside PostgreSQL?▼
Each activated pipeline becomes its own relational dataset within PostgreSQL, with columns mapped to the original API fields such as impressions, clicks, CTR, CPC, and ROAS. Monetary values use the account currency defined in the Ad account pipeline, and date columns respect the time zone configured in the source, making it simple to build consistent SQL reports.
Can I merge ChatGPT Ads PostgreSQL data with other advertising platforms?▼
Yes, Kondado connects 80+ sources, so you can replicate data from multiple advertising platforms into the same PostgreSQL instance and join them with standard SQL. Teams often blend ChatGPT Ads spend with other channel data before connecting the unified dataset to Power BI or Looker Studio for cross-channel reporting.
Do I need engineering resources to connect ChatGPT Ads to PostgreSQL?▼
No code is required to establish the connection, you simply authenticate your ChatGPT Ads account and provide your PostgreSQL credentials within the Kondado interface. The platform exposes each available pipeline as a selectable item, so analysts can choose exactly which registries and reports to load without writing extraction logic or handling API pagination manually.
What is the difference between the Ad performance and Ads pipelines in PostgreSQL?▼
The Ad performance pipeline contains time-series metrics such as impressions, clicks, conversions, and attributed sales grouped by hour, day, or month, while the Ads pipeline is a registry of creative assets that includes headline, body copy, price, and review status. In PostgreSQL, you can join these two datasets on ad identifiers to analyze which creative variations actually deliver the strongest CTR and ROAS over specific date ranges.
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