Auditing your subscription data

As a subscription data platform, ChartMogul uses data it obtains from your billing system(s) to calculate the subscription revenue metrics that can inform your business decisions. ChartMogul uses primarily invoice data to achieve this, and the calculations may differ to those provided by the specific billing systems themselves. Some of the reasons are explored in more detail here. This article instead focuses on how to better audit and explore your data.

First, we will cover how changes in MRR are treated in ChartMogul.

Activities: showing and classifying MRR changes in ChartMogul

How fluctuations in MRR are represented in ChartMogul are dependent on changes to individual subscriptions and the status of the customer. We represent these changes as separate activities for each change done to each subscription. The exceptions to this are changes in MRR due to fluctuations in currency exchange rates, or if the change to a subscription did not change its total MRR.

Our chart breakdowns show the number of activities rather than the number of individual customers, so if your customers buys or cancels multiple subscriptions, they may contribute to the different types of MRR more than once. This is elaborated on below.

New business MRR: An activity contributes to this when it belongs to a brand new customer who buys their first subscription. If smart grouping is enabled, then when a new customer buys multiple subscriptions within a set time frame, then all the resulting activities will be included in the new business MRR.

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In the above example, 27 is the number of new business activities, not necessarily the number of new customers.

Expansion MRR: This includes activities where an existing customers has either upgraded their existing subscription or bought an additional one.

Contraction MRR: Similar to the above, but instead related to whether a customer has downgraded an existing subscription, or removed one (but not all) of their subscriptions.

Reactivation MRR: This is similar to new business MRR, with the exception that the customer used to have a now-cancelled subscription at some previous point in time.

Churn MRR: These are activities tied to a customer who is cancelling all their current subscriptions (see again smart grouping).

Bear in mind that these activities are tied to changes for a subscription. This means that if a customer cancels their only subscription, and then purchases a new one, this will be reflected in ChartMogul as a churn and a reactivation, rather than just reporting the net difference between the two subscriptions. However you can obtain this effect by connecting these two subscriptions.

Comparing the data with your billing system

When auditing your data, a good place to get started is to check how the high-level numbers align, such as:

  • Total MRR (assuming this is provided by your billing system)
  • Total cash flow
  • Number of customers

Seeing differences between some of these numbers but not others can give you an indication as to where any differences may come from. For instance, if you have fewer active customers in ChartMogul, then this might explain why your MRR might be lower than expected. Perhaps your cash flow is still aligned, which might indicate that some customers' subscriptions are not yet contributing to the MRR in ChartMogul. An example of this is Stripe, which requires a successful payment for a subscription to star contributing to MRR. As stated earlier, some reasons for discrepancies can be found in this article here.

ChartMogul also offers a few options on how your subscription analytics are derived, so it is a good idea to try these as you are setting up your account. Changing some of these settings will reprocess your data which, depending on the size of the account, may take some time.

Using Data platform to identify issues in the import process

Some discrepancies can be accounted for by issues in the data being imported. For instance, the data format may be invalid or be otherwise unsupported. This may be at the level of the customer data, invoices, invoice line items or even transactions. If you are an Admin you can find such issues in the *Data platform* section of the application, and selecting the option to only view rows with errors in them. You can also see items that are still in a processing stage. This is available for all of our integrations with the exception of Stripe, Chargify, Recurly, PayPal, and Braintree.

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Looking at an individual customer within ChartMogul

ChartMogul offers you the option to really drill into the data that makes up the aggregate metrics. You can see which customers are contributing to your charts, and then drill down to the individual customer. An individual customer can be a great way to understand how their data is represented in ChartMogul, especially if you compare with how they are represented in your billing system.

Mapping MRR with the underlying transactions

Once you are on a customer's page, two important things you can see here are their MRR throughout their life cycle, and how this ties to the history of transactions they have had.

It is important to note that MRR is not the same as a monthly transaction, and by looking at how ChartMogul is interpreting the payments of invoices can give a lot of clarity on how the MRR was calculated. Below you can see the breakdown of a transaction that took place.

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The transaction is correctly identified as resulting in that customer's MRR being $133, as the line item is correctly identified as a subscription event (as opposed to a non-recurring line item), the service period determines it is for a monthly payment, and the taxes have been excluded from the MRR:

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John Smith's MRR is derived by taking into account the transaction type, service period, and excluding any taxes.

By looking at the information in the transaction you can see how we calculate the MRR value, as well as what information we are receiving from the billing systems themselves. For instance, if you expected a payment to contribute to MRR and it did not, then this could be accounted for if it being categorised as being a 'non-recurring' payment, and it may be worth checking your settings in your billing system.

Seeing a customer's behaviour across the application

Once you have looked into a customer in detail, a useful way to see how they contribute to your metrics is to tag them within the customer's page with a tag that only they have (e.g. "Audit"). This allows you to then see how customers with said plan are represented across our application. For instance in the MRR chart you will be able to see how they have contributed to your MRR over time, whereas the cash flow charts will allow you to see an aggregation of their payments, refunds and taxes.

You can remove any tags you create by using our tags manager.

Using filters for auditing your metrics

Using filters can be useful in auditing your aggregate numbers, as they will help understand how a specific selection of your customers are treated in ChartMogul. Remember also that any applied filter will persist as you change between the charts.

Below are some filtering suggestions, but remember that you can create several filter combinations to drill in to your data.

Filtering by subscription status: This allows you to filter for customers who are active, past due, cancelled, or leads. Out of these, customers who are active or past due will contribute to your current MRR.

Filtering by data source: If you have multiple billing systems, then using our data source filter can help focus on how the analytics are derived for each one. The billing systems may vary among themselves in how they treat customers, and ChartMogul may also vary in how it interprets customers from each one.

Filtering by 'Subscriber since': By using this filter you can focus on just on specific cohorts of customers, including selecting date ranges.

Filtering by tags or custom attributes: You can enrich your customers by using both tags and customer attributes, which can be a good way to focus on a pre-determined group of users. Additionally, you can identify through tags customers who have been churned via our setting for delinquent subscription handling, or have been merged. They can be identified via the tags 'auto-churned-delinquent-subscription' and 'merged customer' respectively.

 

We provide several pages with links to how our metrics are calculated, such as MRR, customer lifetime value (CLV) and different churn rates. These and other pages can be found within our Help Center's Guide-section.