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Connect Pinterest Ads to PostgreSQL

Connect Pinterest Ads to PostgreSQL and export selected accounts, metrics, and dimensions to your PostgreSQL project.

Configure the historical window, destination table, and recurring schedule without maintaining a Pinterest Ads API pipeline.

Used by the world's leading companies

Export Pinterest Ads data to PostgreSQL

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Pinterest Ads data in PostgreSQL

Bring all your Pinterest Ads data into your warehouse and make it available for analytics, machine learning, and internal applications.

Data freshness

Keep your PostgreSQL tables up to date

Automatically sync new data from Pinterest Ads so every dashboard, model, and report works with fresh information.

Analysis

Unify Pinterest Ads with the rest of your business data

Join marketing, finance, CRM, and product data inside the same warehouse.

Pinterest Ads metrics and dimensions available in PostgreSQL

Access 538 metrics and 126 dimensions from Pinterest Ads connectors including ROAS (Checkout), Web ROAS (Checkout), CPC, CPM, Paid CTR, Click-through conversions (Checkout), Campaign name, Ad Group Name, Ad Name, Ad Creative Type, Keyword, Placement, Day of the month and many more...

538

Metrics availables

126

Dimensions availables

Connect Pinterest Ads to PostgreSQL in minutes

Move your data from Pinterest Ads to PostgreSQL with a simple setup. Once connected, Catchr handles the ingestion automatically so your warehouse stays up to date without manual work.

Step one

Connect your Pinterest Ads account

Authenticate your Pinterest Ads account securely in Catchr. No custom scripts, API maintenance, or engineering work required.

Client A · Connected sources
5 sources ready
Pinterest Ads 3 advertising accounts Connected
Google Ads 2 advertising accounts Connected
Google Analytics 4 1 web property Connected
HubSpot 1 CRM portal Connected
Step two

Choose the PostgreSQL destination

Add the database host and credentials once. Catchr checks the connection so your exports start with a reachable destination.

Destination / PostgreSQL Required fields
Host Required
warehouse.company.net
Username Required
catchr_writer
Password Required
••••••••••••
Database Required
marketing
Step three

Keep your PostgreSQL tables updated

Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your PostgreSQL table.

Export job / PostgreSQL Example
Schema Destination
marketing_raw
Table Per job
linkedin_ads_daily
Recurring schedule Choose a cadence
Every 6 hours
Daily · 07:00
Weekly · Mon
First sync scheduledSelected fields · configured history
07:00 UTC

Review 30-day Pinterest Ads campaign delivery in SQL.

This example summarizes spend, impressions, clicks, and click-through rate by campaign.

Pinterest Ads.sql
BigQuery SQL
30-day window
SELECT
  campaign_name,
  SUM(spend) AS spend,
  SUM(impressions) AS impressions,
  SUM(clicks) AS clicks,
  SAFE_DIVIDE(
    SUM(clicks),
    SUM(impressions)
  ) AS ctr
FROM `your_project.marketing_raw.pinterest_ads_daily`
WHERE date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY campaign_name
ORDER BY spend DESC;
Illustrative SQL — adapt it to the fields and schema selected in your export. Standard SQL

Choose what to load into PostgreSQL.

Each connector has its own entities, fields, historical limits, and reporting uses. Open a source page for the details that belong to that platform.

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Before you schedule the job.

Answers about PostgreSQL setup, available source data, schedules, table updates, and SQL use cases.

How do I route Pinterest Ads data into PostgreSQL tables?

Connect Pinterest Ads and add PostgreSQL as the stored destination. Create a datastream, then save a job that sends the required records to the "accounts" table.

Which Pinterest Ads fields can I store in PostgreSQL?

Select concrete Pinterest Ads fields such as Add To Cart, ROAS (Checkout), Paid Pin clicks, and Day of the month. You can rename the chosen columns, preview the result, and write them to PostgreSQL tables such as accounts, advertisers, and campaigns.

Can I backfill Pinterest Ads data before scheduling PostgreSQL updates?

Choose how far back the first Pinterest Ads load should go and how much recent data each "accounts" run should refresh. Catchr splits large backfills into smaller intervals.

What happens if no partition field is chosen for Pinterest Ads?

For recurring Pinterest Ads loads, assign an eligible partition field to "accounts". Otherwise Catchr cannot match the refresh window and will append the returned records.

How does Pinterest Ads data in PostgreSQL support deeper analysis?

With Pinterest Ads data, a PostgreSQL query can summarize spend, impressions, clicks, and click-through rate by campaign. Join Add To Cart and ROAS (Checkout) with shared account or date keys to build a reusable performance model in PostgreSQL.

Does my PostgreSQL database need to exist before I connect it?

Yes. Connect an existing PostgreSQL database first. The Catchr job creates and populates the destination table you configure inside that database.

Can I load several marketing sources into the same Postgres database?

Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.

Still have a question ? 

Our teams is always here to responds to any question you could have about our data connector. 

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