# Connect Chargify to ChartMogul

> Automate billing data flow from Chargify into ChartMogul so your SaaS metrics stay accurate, timely, and ready to act on.

**Canonical page:** https://tray.ai/connectors/chargify-chartmogul-integrations/
**Chargify connector:** https://tray.ai/connectors/chargify-integrations/
**Chargify documentation:** https://tray.ai/documentation/connectors/service/chargify
**ChartMogul connector:** https://tray.ai/connectors/chartmogul-integrations/
**ChartMogul documentation:** https://tray.ai/documentation/connectors/service/chartmogul

## Overview

Chargify is a subscription billing and revenue management platform built for B2B SaaS companies. ChartMogul is a subscription analytics platform that turns raw billing data into MRR, churn, LRR, and cohort insights. Together, they're the backbone of a data-driven subscription business. Connecting them means every subscription event — new signups, upgrades, downgrades, cancellations, reactivations — shows up in your analytics dashboards immediately, with no manual exports and no data lag.

For SaaS finance, growth, and revenue operations teams, the gap between billing data and analytics is a constant source of friction. When Chargify and ChartMogul aren't connected in real time, teams fall back on manual CSV exports, error-prone data entry, or delayed batch syncs that produce stale metrics. Leadership ends up making pricing, retention, and expansion decisions from outdated MRR figures and inaccurate churn rates. By integrating Chargify with ChartMogul through tray.ai, every subscription lifecycle event is automatically captured and pushed into ChartMogul the moment it happens, giving you a single source of truth for subscription revenue. Board reporting gets faster, investor metrics get more accurate, and your revenue team spends time on analysis instead of data wrangling.

## Use cases

### Real-Time MRR Tracking Across the Full Subscription Lifecycle

Whenever a subscription is created, upgraded, downgraded, or cancelled in Chargify, tray.ai syncs that event to ChartMogul so your MRR charts reflect the true state of your business at all times. No lag between billing activity and analytics reporting. Finance and leadership always have an accurate, up-to-the-minute picture of recurring revenue.

- Eliminate stale MRR figures caused by delayed manual syncs
- Capture every subscription event including trials, upgrades, and mid-cycle changes
- Enable daily or intra-day revenue reporting without manual intervention

### Automated Customer Import and Profile Enrichment

When a new customer is created in Chargify, tray.ai provisions a matching customer profile in ChartMogul, pre-populated with company name, email, and subscription plan. Your analytics platform always has a complete customer roster, and richer profiles make cohort analysis and segmentation far more useful.

- Ensure ChartMogul customer profiles are created the moment a subscription is activated
- Reduce manual data entry and the risk of duplicate or missing customer records
- Enable accurate customer-level LTV and cohort tracking from day one

### Churn and Cancellation Event Synchronization

When a subscription is cancelled or expires in Chargify, tray.ai immediately updates ChartMogul to record the churn event with the correct date and plan details. Accurate churn timestamps matter for calculating monthly churn rate and understanding retention cohorts. Your churn data in ChartMogul is never delayed or approximated.

- Log churn events in ChartMogul with precise timestamps from Chargify
- Distinguish between voluntary cancellations, failed payments, and trial expirations
- Improve the accuracy of cohort-level churn and retention analysis

### Plan Upgrade and Expansion Revenue Capture

Expansion revenue from plan upgrades and add-ons in Chargify is automatically reflected as MRR expansion events in ChartMogul, giving you a clear view of Net Revenue Retention. Without this connection, expansion events are frequently missed or miscategorized. tray.ai makes sure every upsell is counted and attributed correctly.

- Capture expansion MRR from plan upgrades and add-on purchases automatically
- Improve Net Revenue Retention reporting accuracy for investor and board decks
- Identify high-expansion customer segments using reliable ChartMogul data

### Reactivation and Win-Back Tracking

When a previously churned customer reactivates in Chargify, tray.ai sends the reactivation event to ChartMogul so the customer is correctly reclassified and their MRR contribution is restored. Tracking win-backs accurately is how you measure whether re-engagement campaigns are actually working — and this workflow means reactivations are never lost in the data.

- Accurately record reactivation events to avoid double-counting churn
- Measure the MRR impact of win-back campaigns in ChartMogul
- Support accurate Net New MRR calculations that account for reactivations

### Subscription Plan and Pricing Change Propagation

When you update pricing plans or product configurations in Chargify, tray.ai can sync the updated plan metadata to ChartMogul so your analytics segments and MRR calculations stay aligned with your current pricing structure. This is especially useful during pricing migrations or annual plan launches, where stale plan data quietly breaks segmentation in your revenue reporting.

- Keep plan names, pricing tiers, and intervals consistent across both platforms
- Avoid MRR miscalculations caused by stale plan data in ChartMogul
- Support accurate plan-level segmentation for retention and expansion analysis

### Failed Payment and Dunning Event Logging

tray.ai can listen for failed payment and dunning events in Chargify and log them in ChartMogul as contraction or at-risk signals, giving your customer success team early warning of potential involuntary churn. Correlating payment failures with churn cohorts tells you how much revenue is lost to billing issues versus genuine cancellations — and makes churn analysis a lot more honest.

- Distinguish involuntary churn from voluntary cancellations in ChartMogul reporting
- Trigger customer success alerts when high-value accounts enter dunning
- Quantify the revenue impact of payment failures to prioritize dunning improvements

## Templates

### Sync New Chargify Subscriptions to ChartMogul in Real Time

This template listens for new subscription created events in Chargify via webhook and automatically creates or updates the corresponding customer and subscription record in ChartMogul, so your analytics platform is always current.

Connectors used: Chargify, ChartMogul

### Push Chargify Cancellation Events to ChartMogul as Churn

When a subscription is cancelled in Chargify, this template sends a cancellation event to ChartMogul with the correct date, so churn metrics are recorded precisely and without delay.

Connectors used: Chargify, ChartMogul

### Sync Chargify Plan Upgrades and Downgrades to ChartMogul

This template detects subscription component or plan change events in Chargify and updates the corresponding subscription in ChartMogul to reflect the new MRR value, correctly categorizing the event as expansion or contraction revenue.

Connectors used: Chargify, ChartMogul

### Daily Chargify to ChartMogul Full Reconciliation Sync

This template runs on a daily schedule to compare active subscriptions in Chargify with records in ChartMogul, identifying and correcting discrepancies to keep data consistent across both platforms.

Connectors used: Chargify, ChartMogul

### Auto-Log Chargify Reactivations in ChartMogul

This template detects subscription reactivation events in Chargify and posts the reactivation event to ChartMogul, so previously churned customers are correctly reclassified and their MRR is restored in your analytics.

Connectors used: Chargify, ChartMogul

### Chargify Failed Payment Alert and ChartMogul At-Risk Tagging

When Chargify fires a payment failure or dunning event, this template tags the matching ChartMogul customer as at-risk and optionally notifies the customer success team, so you can intervene before the account churns.

Connectors used: Chargify, ChartMogul

## Challenges Tray.ai solves

### Mapping Chargify Subscription States to ChartMogul Event Types

Chargify uses its own subscription states — active, past_due, canceled, expired, on_hold — that don't map one-to-one to ChartMogul's event model of new business, expansion, contraction, churn, and reactivation. Mapping them incorrectly means miscalculated MRR and inaccurate churn rates.

**How Tray.ai helps:** tray.ai's workflow logic layer lets you build conditional branching that inspects each Chargify event type and maps it to the correct ChartMogul event, including edge cases like mid-cycle plan changes and component-based billing adjustments, without writing custom code.

### Handling Chargify's Component-Based and Metered Billing in ChartMogul

Chargify supports components, metered usage, and quantity-based pricing that make MRR calculation non-trivial. Pushing raw billing data to ChartMogul without aggregating components first produces overstated or understated MRR figures.

**How Tray.ai helps:** tray.ai lets you build calculation steps within the workflow that aggregate all active components and quantities for a given subscription before posting the final MRR value to ChartMogul, so your analytics reflect true recurring revenue regardless of billing complexity.

### Avoiding Duplicate Customer Records in ChartMogul

When the same customer appears multiple times in Chargify — due to test subscriptions, migrations, or multiple products — naive integrations often create duplicate customer profiles in ChartMogul, polluting analytics with inflated customer counts and fragmented LTV data.

**How Tray.ai helps:** tray.ai workflows can include a deduplication step that checks for an existing ChartMogul customer using the Chargify customer ID or email before creating a new record, and merges subscription data into the correct profile when a match is found.

### Maintaining Historical Data Integrity During Initial Migration

When you first connect Chargify to ChartMogul, you need to backfill historical subscription events — not just current active subscriptions — so ChartMogul's MRR history, cohort charts, and churn trends are accurate from the start. Doing this manually is slow and error-prone.

**How Tray.ai helps:** tray.ai supports paginated bulk data workflows that can iterate through Chargify's historical subscription records and feed them into ChartMogul in chronological order with correct event dates, enabling a clean historical backfill without manual CSV manipulation.

### Keeping ChartMogul in Sync During Chargify Webhook Failures or Delays

Relying solely on Chargify webhooks means any webhook failure, retry storm, or delivery delay can leave ChartMogul out of sync with the actual billing state, resulting in temporarily wrong MRR figures and missed churn events.

**How Tray.ai helps:** tray.ai has built-in error handling, automatic retries, and support for scheduled reconciliation workflows that cross-check Chargify API data against ChartMogul records, catching and correcting any events missed due to webhook failures.

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