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Connect Piano Analytics to PostgreSQL

Connect Piano Analytics 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 Piano Analytics API pipeline.

Used by the world's leading companies

Export Piano Analytics data to PostgreSQL

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Piano Analytics data in PostgreSQL

Bring all your Piano Analytics 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 Piano Analytics so every dashboard, model, and report works with fresh information.

Analysis

Unify Piano Analytics with the rest of your business data

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

Piano Analytics metrics and dimensions available in PostgreSQL

Access 90 metrics and 228 dimensions from Piano Analytics connectors including Users, Sessions, Conversions, Sales, Time Spent, Page To Purchase Rate, Date, Source Campaign, Source Medium, Source, Country, Page and many more...

90

Metrics availables

228

Dimensions availables

Connect Piano Analytics to PostgreSQL in minutes

Move your data from Piano Analytics 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 Piano Analytics account

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

Client A · Connected sources
5 sources ready
Piano Analytics 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 Piano Analytics traffic and conversion performance in SQL.

This example summarizes users, sessions, conversions, and conversion rate by traffic source.

Piano Analytics.sql
BigQuery SQL
30-day window
SELECT
  traffic_source,
  SUM(active_users) AS active_users,
  SUM(sessions) AS sessions,
  SUM(conversions) AS conversions,
  SAFE_DIVIDE(
    SUM(conversions),
    SUM(sessions)
  ) AS conversion_rate
FROM `your_project.marketing_raw.piano_analytics_events_daily`
WHERE date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY traffic_source
ORDER BY sessions 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.

What do I need to export Piano Analytics data to PostgreSQL?

Register Piano Analytics, save the PostgreSQL connection details, and pair both systems in a datastream. The associated job previews and writes the selected columns to "sessions".

What does a Piano Analytics table in PostgreSQL contain?

Select concrete Piano Analytics fields such as Action Clicks, Ad Clicks, Ads Skip, and Day of the month. You can rename the chosen columns, preview the result, and write them to PostgreSQL tables such as properties, sessions, and users.

How do scheduled PostgreSQL jobs keep Piano Analytics data current?

The "sessions" job can begin with a historical Piano Analytics fetch and continue on a recurring schedule. Available history and frequency depend on the source API and your plan.

What controls row replacement in a Piano Analytics PostgreSQL table?

Select a valid date field when configuring the Piano Analytics job for "sessions". Catchr deletes and rewrites the scheduled window, limiting duplicate rows across overlapping runs.

How can I model Piano Analytics performance with PostgreSQL?

With Piano Analytics data, a PostgreSQL query can summarize users, sessions, conversions, and conversion rate by traffic source. Turn Action Clicks and Ad Clicks into a stable PostgreSQL view that analysts and reporting tools can query repeatedly.

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 ? 

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