Gorgias integration

Gorgias in Polar: support load, read against revenue.

Connect Gorgias and ticket volume flows into Polar, created, opened and closed, sliced by agent, channel and tag. Polar sits it next to Shopify orders, returns and refunds, so support load stops being a number in a helpdesk and becomes a metric you can read against revenue.

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Connect Gorgias See the setup
Google Sheets → Polar

What you can bring in

Ticket volume
"How many tickets, really?"
Tickets created, opened and closed, one line per ticket, refreshed on every sync.
created · opened · closed
By agent
"Who's carrying the load?"
Ticket volume sliced by agent, so you see where support effort concentrates.
by agent
By channel & tag
"What are people writing in about?"
Volume sliced by channel and tag, so you see the drivers behind the load.
by channel · tag
Tickets per 1k orders
"Is support load rising with growth?"
Ticket volume read against Shopify orders as tickets per thousand orders, with the trend.
per 1,000 orders
Against returns
"Is support tied to returns?"
Sit ticket volume next to returns and refunds to see where operational issues show up as support.
tickets vs returns
Focused by design
"What does the connector cover?"
A focused ticket-volume connector, created, opened, closed, not a full helpdesk mirror.
ticket-volume, honest scope

Gorgias measures support. Polar measures support against the business.

Your helpdesk reports tickets in isolation, volume, agents, tags, but it cannot see orders, returns or revenue. So you never really know whether support load is healthy for the size of the business. Polar reads Gorgias against the numbers that give it meaning.

Gorgias on its own

  • Ticket volume lives in the helpdesk, revenue lives elsewhere.
  • No sense of whether load is high or low for your order volume.
  • Support trends and revenue trends never sit on the same chart.
  • Nothing ties support effort to returns or refunds.

Gorgias with Polar

  • Ticket volume read against orders as tickets per thousand orders.
  • Load in context: rising, flat or falling relative to growth.
  • Support and revenue on one view, on the same timeline.
  • Ticket volume sits next to returns and refunds, so drivers are visible.
Setup Guide

Connect Gorgias.

01 · What you need
Polar

A Polar account with Shopify

A Polar account with Shopify connected. This connector plugs in right next to your stack.

Connect your data →

Your Gorgias account

Your Gorgias domain and account email, and one REST API key from Gorgias settings. Your account needs to already hold data before you connect.

Open Gorgias →

Shopify already connected

Support only means something against orders, so Polar reads Gorgias next to your Shopify orders, returns and refunds.

02 · Connect Gorgias
1

Connect with an API key ~2 min

Domain, email, one REST key.
Add Gorgias with your domain, account email and a REST API key from Gorgias settings. Your account needs to already hold data before you connect.
2

Ticket volume, aggregated automatic

Created, opened, closed.
Polar pulls ticket volume, created, opened and closed, one line per ticket, into an aggregated view sliced by agent, channel and tag.
Scope, honestly: Gorgias is a focused, ticket-volume connector, not a full helpdesk mirror. If you need more metrics, ask and Polar can request them.
3

Read it against revenue the payoff

Support as a metric.
Sit ticket volume next to Shopify orders, returns and refunds, so support load reads against revenue as tickets per thousand orders, not a standalone helpdesk number.
Get started

Turn support load into a business metric.

Connect Gorgias with a REST API key and read ticket volume against orders, returns and refunds.

Book a demo Connect your data ↗
The Gap

The connector is only half of it.

Once your Gorgias ticket volume are clean and attributed inside Polar, you can use them wherever you already work. Ask Polar in plain language, pull them live through the Polar MCP, or schedule a snapshot into the report your team reads every morning.

Gorgias

tickets created, opened, closed
Polar

Polar

support load vs revenue

Ask Polar

Polar MCP

Scheduled reports

Featured Use Case

Support, finally in proportion.

Support, in proportion

A thousand tickets is a crisis for one brand and a quiet week for another, the number only means something against how many orders you shipped. In Gorgias, that context does not exist: you see volume, agents and tags, but not the orders, returns and refunds that make the load meaningful. Polar pulls ticket volume, created, opened and closed, and sits it next to your Shopify orders, so support becomes tickets per thousand orders, a metric you can actually trend and reason about. When it spikes, you can look at returns and refunds on the same view and see whether it is an operational issue, not just a busy inbox. It is a focused, honest connector, ticket volume, not a full helpdesk mirror, but it puts support where it belongs: next to the business.

What makes it real

Tickets per 1,000 orders. Volume read against Shopify orders, so load is in proportion to the business, not an absolute number.

Sliced where it matters. Created, opened and closed by agent, channel and tag, next to returns and refunds.

Ask Polar, in plain language. “Show tickets per thousand orders this week and how it tracks with returns.” No SQL, no export.

See how support reads against revenue
Other Use Cases

Other use cases

Use case 01

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Placeholder. The use case skill fills this. (rung: see it)

See the use case › Use case 02

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Placeholder. The use case skill fills this. (rung: report it)

See the use case › Use case 03

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Placeholder. The use case skill fills this. (rung: analyze it)

See the use case › Use case 04

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Placeholder. The use case skill fills this. (rung: decide from it)

See the use case › Use case 05

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Placeholder. The use case skill fills this. (rung: act on it)

See the use case ›
Your Prompt Library

Gorgias in plain language

A scannable wall of sample prompts for your Gorgias data inside Polar. Ask Polar, or Claude with the Polar MCP connected.
See it
Show tickets created, opened and closed this week.
Break down Gorgias tickets by agent and channel.
Show ticket volume by tag this month.
Analyze it
Show tickets per 1,000 orders and the week-over-week trend.
Compare support load to returns and refunds this month.
Which tags are driving the most tickets relative to orders?
Decide from it
Is support load healthy for our current order volume?
Where should we invest in self-serve based on ticket drivers?
Summarize how support load changed since last month and why.
Get started · connect once · support in context

Support load, against the business.

Connect Gorgias with a REST API key and read ticket volume against orders, returns and refunds, so support load finally has context.

Get started by booking a demo Connect your data in Polar
Phase 1 ~2 minConnect GorgiasAdd your domain, email and a REST API key.
Phase 2 automaticTicket volume inCreated, opened, closed, sliced by agent, channel and tag.
Phase 3 the payoffRead against revenueTickets per thousand orders, next to returns and refunds.