Analytics FAQ

Knowing your metrics is very important 📈 With our Analytics you are able to gain insight on some important stats that will help you forecast your sales or give you ideas on the improvement areas that you'll need to work on. Please review this article for a more detailed information on how we're calculating each one of these stats. 

Monthly Recurring Revenue (MRR)

Best possible way of understanding this one is by showing a simple example. Let's say that you have 10 customers each paying $10/mo on a recurring basis. MRR will than be:

10 x $10 = $100

At present, we're not taking any possibly applied coupons into account when calculating the MRR and any deductions from coupons are excluded from the calculation at present ❗
Want to know more about MRR? Go here!


Revenue metric is calculated as: 

Sum of orders total for the date/date range - sum of refunded amount for the selected date/date range


Churn Analytics include by default the early churn that, like shown below, will help you get more accurate calculations to have a clear reading on what to improve.

Formula used:

SUM((Number of active subscribers at the start of the day) - (Number of active subscribers at the end of the day) / (Number of active customers at the start of the day))

Note that new customer gained that day are excluded from the calculation, as well as customers who churn and then reactivate on the same day.

Let's imagine that: At the beginning of the day on Monday, we had 100 active subscribers. We lost 5 subscribers on Monday. Gained 10 and lost 5 subscribers on Tuesday. This leaves us with 100 subscribers at the end of Tuesday. As the new customers gained on Tuesday are excluded from the calculation, the customers at the end of the day are counted to be 90.
If we wanted to see the churn rate for the period of Monday - Tuesday, we would do this calculation:
Monday: (100 - 95) / 100 x 100 = 5%
Tuesday: (95-90) / 95 x 100 = 5.26%
SUM(Monday churn rate + Tuesday churn rate) = 10.26% customer churn rate

Accumulative Churn  

This one can be enabled by turning on the toggle on top of the churn graphic and doesn't take into account the early churn:

It is calculated as follows 👇

(Sum of cancelled subscriptions in the last 30 days / How much active subscriptions were active on the store 30 days ago) x 100

For example, let's say that you're trying to calculate your churn % on the 1st of August. We calculate that metric taking into account all cancelled subscriptions in the last 30 days (1st of July - 1st of August) and dividing that with the number of active subscribers at the start of this period (number of active subscribers you had on the 1st of July). 

New Cancellations 

Simple sum of all cancelled subscriptions on the selected date/date range. 

Active Subscriptions

Sum of all active subscriptions on the selected date/date range.

New Customers

Count of all new customers (both subscription and one times taken into account here ❗) within the selected time period (number of customers at the end of the time frame - number of customers at the beginning of the selected time frame).


Number of pageviews within the selected time period. 

Only unique IP visits counted. Visits on both Subbly subdomain and your custom domain (if connected) included and taken into account ❗

Abandoned Carts

Count of all carts that were abandoned and were not revisited within the certain date range.

Cart is considered abandoned if customer/visitor starts the checkout and bounces off of it at any point, and doesn't revisit the checkout within the next 2 hours This is also not the same prerequisite for the abandoned cart to become part of the cart abandonment sequence. 

New Subscriptions 

Count of all new subscriptions within the selected time period (number of active subscriptions at the end of the time frame - number of active subscriptions at the beginning of the selected time frame). 

Lifetime Value of Customer (LTV)

LTV is a very important metric that is used for projecting the growth of the business based on average MRR and average churn. Put in simple words, LTV actually shows how much money a customer is going to give to your business before he/she ultimately unsubscribes and churn 😊

As the LTV is affected by churn metrics, you'll also see the changes explained in the churn section above.

Formula would be:

Average MRR per customer / Average Churn

Formula with the early churn analytics (not accumulative):

Average MRR per customer / Average Churn (using the updated formula explained above)

Both average MRR and churn are calculated in regards to the selected time period and based on the calculations presented above in the article ☝

Based on this, LTV can be boosted by either increasing the MRR per customer/user or by reducing churn of your business.  


How do you calculate churn on the customers who are skipping the payment? 

These are not taken into consideration when calculating churn 😊

If you want to deep dive into these and other important metrics, read here our dedicated blog post. 

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