ChartMogul connector

Set up the ChartMogul connector in Kaivo: authentication, configuration, the 6 BigQuery tables it syncs, and answers to common questions.

Written By Lauri Raivio

Last updated About 1 hour ago

Kaivo is a fully managed data platform that syncs your ChartMogul data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your payment and finance data instead of moving it.

What is the ChartMogul connector

Sync your ChartMogul subscription metrics into BigQuery with Kaivo to analyse MRR, churn, and customer movements alongside the rest of your data.

CategoryFinance & Payments
StatusGenerally available
AuthenticationAPI key
SetupSelf-service

Getting started with the ChartMogul connector

  1. Sign up for Kaivo and create a workspace.
  2. Connect your ChartMogul account.
  3. Choose which tables to sync.
  4. Wait for the initial sync to finish.
  5. Query your data in BigQuery or your favourite AI or BI tool.

Authenticating ChartMogul

Authenticate with your API key.

FieldDescription
API key

Your ChartMogul API key. See the docs for info on how to obtain this.

Configuring the ChartMogul connector

When you set up the connector, you provide:

FieldDescription
Start date

Any data before this date will not be fetched.

Tables and columns synced from ChartMogul

Kaivo syncs 6 tables from ChartMogul into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.

How the ChartMogul sync works

After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where ChartMogul supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.

Frequently asked questions

How long does the initial sync take for ChartMogul?

It depends on how much history is in your ChartMogul account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.

Can I sync only some tables or columns?

Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.

What happens when ChartMogul's schema changes?

New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in ChartMogul, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.

How do I handle GDPR or data deletion requests?

Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in ChartMogul instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the ChartMogul connector in Kaivo and all of its synced data is deleted with it.

Common use cases for ChartMogul data

MRR movements

Use the activities data to break MRR into new, expansion, contraction, and churn.

Customer counts

Track customer_daily_count and the weekly and monthly counts to monitor growth over time.

Cohort retention

Analyse customers and activities to measure retention by signup cohort.

Metrics and product together

Combine ChartMogul metrics with product usage in BigQuery to connect engagement to revenue.

Use ChartMogul data in your AI and BI tools

Once ChartMogul data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with ChartMogul data.

Claude

Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →

Power BI

Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →

Data Studio

Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →

Tableau

The premium analytics standard, with native BigQuery integration. Setup guide →

Google Sheets

Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →

Excel

Connect via Power Query's BigQuery connector. Setup guide →

Metabase

Open-source BI tool with strong BigQuery support. Setup guide →

See our pricing page for ChartMogul connector pricing and plan details.