Data Overview

ChartMogul exposes subscription analytics data across six entities: individual customer records, subscription activity events, and customer count aggregations at four time granularities. Together, these give you everything you need to track revenue growth, churn patterns, and customer lifecycle changes.

Entities

Entity	Best used for
Customers	CRM-style analysis, segmentation, cohort building
Activities	Event-level revenue tracking, churn and expansion analysis
Customer daily counts	High-resolution growth tracking
Customer weekly counts	Weekly business reviews
Customer monthly counts	MRR reporting, board decks
Customer quarterly counts	QBRs, investor reporting

Customers

Key fields

Field	Description
uuid	Unique ChartMogul customer identifier
external_id	ID from the connected billing system (e.g., Stripe)
name	Customer name
email	Customer email address
status	Subscription status: Active, Past Due, Cancelled
customer-since	Date the customer first subscribed
mrr	Current MRR contribution (in cents)
arr	Annualized revenue (in cents)
ltv	Lifetime value (in cents)
plan	Name of the current subscription plan
country	Customer country
city	Customer city
lead_created_at	When the lead was first created in ChartMogul
free_trial_started_at	Trial start date, if applicable

Activities

Key fields

Field	Description
uuid	Unique activity identifier
customer_uuid	Links the activity to a customer record
type	Activity type: new_biz, expansion, contraction, churn, reactivation
date	Date the activity occurred
mrr	MRR value associated with the activity (in cents)
mrr-movement	Change in MRR caused by this activity
currency	Currency code
plan	Plan associated with the activity
description	Human-readable description of the event

Customer count cadences

All four count entities (daily, weekly, monthly, quarterly) share the same structure:

Key fields

Field	Description
date	Period start date
customers	Number of active customers in that period

The only difference is the time granularity. Use daily counts for operational monitoring, monthly or quarterly counts for reporting and trend analysis.

Common metric combinations

• Activities + Customers (Join on customer_uuid) — Enrich each activity event with customer metadata like plan, country, or LTV for deeper segmentation

• Customer monthly counts over time — Plot as a time series to visualize net customer growth trends

• Activities filtered by type = churn — Isolate churn events to calculate churn rate or identify at-risk segments

• MRR from Customers + MRR movement from Activities — Cross-reference current MRR with historical movements to reconcile revenue changes

Use cases by role

Finance

• Export monthly customer counts to Google Sheets or Excel for board-ready MRR and growth reports

• Use Activities data to reconcile MRR movements (new, expansion, churn) with billing system records

• Send ChartMogul data to BigQuery and combine with invoicing data for full revenue recognition workflows

• Use Aggregate transformations to sum MRR by plan or country for revenue mix analysis

Growth & Marketing

Product & Leadership

Platform-specific notes

• MRR and LTV values are returned in cents — divide by 100 for display in reports

• The start_date parameter applies to all entities; set it far enough back to capture the history you need

• ChartMogul aggregates data from connected billing sources (Stripe, Recurly, etc.) — discrepancies usually trace back to the source system, not ChartMogul

• The external_id field is useful for joining ChartMogul customer records with records in your CRM or billing platform