
Hightouch in Polar: the pipes are built, the metrics are not.
Hightouch moves the data. What it does not do is decide what net revenue means, or what counts as a new customer, so every team that receives the data defines it again on the way out. Polar puts a governed semantic layer on top, so the pipeline ends in metrics rather than in tables.
/ ⏎ The pipeline ends in a metric, not a table.
How to Connect Hightouch to Polar.
A Polar account with Shopify
A Polar account with Shopify connected. Hightouch data only means something read against the orders behind it.
Connect your data →
Your Hightouch workspace
Access to the Hightouch workspace and the destinations or syncs you want Polar to sit alongside.
Open Hightouch →Polar's AI Data Engineer
No native Hightouch connector yet? Describe what you need in plain language and the AI Data Engineer reads the Hightouch API, writes the connector and pipes it into your warehouse, in minutes.
Ask for the connector ~ minutes
Modelled into the layer automatic
One definition everywhere the payoff
End the pipeline in a metric, not a table.
Bring Hightouch in and let Polar's semantic layer define the numbers once, for every tool downstream.
Hightouch moves the data. Polar decides what it means.

Hightouch on its ownon its own
+Hightouch with Polarblended
The connector is only half of it.

Hightouch
Polar
Ask Polar
Polar MCP
Scheduled reports
One definition, everywhere.
Defined once
GovernedA pipeline delivers columns. A semantic layer delivers a number that means the same thing in a dashboard, in a prompt and in a board deck.
Reachable by anyone
No SQLNobody needs to know the schema to ask what happened, which is the difference between data being available and data being used.
