ARR is short for Annual Recurring Revenue, a common metric used by SaaS or subscription businesses. Simply, ARR is the value of recurring revenue, normalized to a one year period. ARR excludes one-time and variable payments. It’s the key metric used to track where your business is headed over the next year.
Here’s how we calculate it: ARR = MRR * 12
It is typical for ARR to only be used as a metric for businesses that have annual contracts, since non standard or non contracted agreements can cause heavy fluctuation and inaccuracy.
However, we feel ARR is a vital metric for a business to track, so we developed a proprietary algorithm that normalizes month and term agreements, and accounts for things such as number of days in a month.
ARR is a great indicator of the momentum of your business, specifically when used as part of a cohort analysis:
- ARR from new customers during a certain time period
- ARR from existing customer renewals
- How upgrades and add ons increases in ARR
You can learn more about how to do this type of cohort analysis here.
Since ARR is calculated using MRR, you may find this post helpful: What is MRR?
GAAP revenue is typically computed using a daily recognition model, which means revenue is recognized pro rata each day between the start and end date of a plan. We do not currently calculate GAAP revenue, do to the specific reporting requirements of different types of organizations. Your account can help you with this one.
MRR is short for Monthly Recurring Revenue, which is calculated using subscriptions or a predictable revenue stream (plans for this post). It excludes one time payments, discounts, refunds or non contracted revenue. Since MRR reports revenue across dissimilar plan terms, reporting can challenging. We automatically account for these challenges with our a proprietary algorithm that normalizes the contributing elements used to calculate MRR. Also, since we integrate directly with payment providers and can calculate MRR in real time, we report REAL MRR, not theoretical (link) Since this is a key metric on the current performance of your business, we want it to be as accurate as possible.
Here’s how we calculate it: MRR = (ARR(Normalized)) + (Plans(Normalized))
It is important to note that MRR is not GAAP Revenue. The difference tends to cause confusion for many organization and their finance departments.
To ensure clear business discussions, we’d suggest using the term “GAAP Revenue” for discussions relating to accounting and income performance, and “MRR” for subscription metrics and analytics.
CLV is short for Customer Lifetime Value; an estimate of the projected total value of a customer to your business. To be as accurate as possible, we use a proprietary algorithm to derive the present value of a customer using actual historic values and predictive modeling. This is far more accurate than most calculations that merely account for averages against churn.
Here’s how we calculate it: CLV = ARPU (Historical + Predictive) / Churn
Why is this so important?
Understanding CLV will help you determine how much you can spend to acquire a customer, how much support you can/should offer that customer, and ultimately how sustainable your business model is over time.
Here are two examples:
Your SaaS business has an ARPU (Average Revenue Per User) of $125, and churn is 3%, your CLV is $4,166. Your cost per acquisition will basically tell you if this is a great customer or not. If you acquired the customer for less than $1,000, this should be a profitable customer. Go get more of them right now.
Your SaaS business has an ARPU of $650, and churn is 16%, your CLV is $4,062.50. Compared to the above example, the CLV is pretty close even though the ARPU is much higher. However, you can see how high churn can really hurt the overall value a business obtains from its customers.
ARPU is short for Average Revenue Per User. Basically ARPU is the average revenue you make from a user over a particular month. This is a simple, yet powerful metric that can inform many different areas of your business.
To be as accurate as possible, we use Active Users to calculate ARPU, and use our Customer Profiles to combine any users who have multiple plans/transactions into 1 Active User.
Here’s how its calculated: ARPU = MRR / Active Users
Why is ARPU important?
Measuring ARPU is important because it’s a key indicator of both revenue source and margin growth, and informs analysis of whether or not you are going to hit your revenue targets. A higher ARPU is also indicative of how successful you are at up-selling/cross-selling additional services to individual customers.
An Active Customer is someone who has transacted with your business during a given period of time. Typically, these are customers that are either under a subscription plan, or who have made a purchase during the Average Purchase Timeline.
Our Customer Profiles and Customer Persona contain a lot of information on your customers, (both individually and on the aggregate), which we use to compute Active Customer. We use a proprietary algorithm to understand what the Average Purchase Timeline is for you customer base, and then identify Active Users as part of a Custom Audience.
Since the number of Active Users is a key part of other metrics such as ARPU, CLV we take extra care to ensure we are delivering the most accurate information.
A Customer Persona is a model of the unique attributes displayed across your entire customer base using Customer Profiles. With Customer Personas, you’ll have a clear understanding of your “typical” customer, and can therefore be more strategic in how you relate to them.
Customer Persona = Aggregate of Customer Profiles
Here are the elements of a Customer Persona:
- Average # Transactions
- Top Sources
- Aggregate LTV
- Average Revenue Per User
- Aggregate CAC
- % Using Social Media
- Average Social Media Followers
- Customer Location Map View
- Top Location by State Breakdown
- Gender Breakdown
- Average HHI
- Average Purchase Frequency
- Top Audiences
- Average Quality Score
LaunchTrack wants to help you understand your customers on a deeper level. So we automatically build rich and insightful profiles combining payment data with demographic information and social media accounts.
Customer Profiles are unified, whereas, transactions are mapped together on multiple data points to create a singular, enhanced view.
Here are the elements of a Customer Profile:
- Transactions; purchase history
- Source; where did they come from?
- LTV: Lifetime Value
- Total Revenue; how much money have you made to date?
- CAC%: Average Acquisition Cost / Total Revenue
- Social Media Info: Account Listings
- Activity; actual streams/posts to social media
- Map; where they live
- Address(es); collected address(es)
- Gender; Male / Female
- HHI; household income
- Timeline; when they have purchased from you
- Purchase Frequency; how often do they purchase from you
- Predictive Purchase Frequency; when will they buy from you again
- Audience Member; lists Custom Audiences they are a member of
- Quality Score; how good a customer are they
Average Charge is the amount your customers spend with you, during a given period of time.
Churn is the measure of attrition or loss over a specific period of time. While you can measure a lot of different things to calculate churn, we focus on customers (lost/won).
Here’s how we calculate it: Churn = Lost Customers @End / Total Customers @Beginning
We express churn as a ratio, which is the inverse of your renewal rate. For example, an 86% renewal rate is equivalent to a 14% churn rate.
Churn can be used in a variety of ways to inform business decisions, such as:
- Assessing the value your customers are attributing to your product (more churn = less value)
- Calculating Customer Lifetime Value calculations
- Projecting revenue and cash flow
Churn is a good measure for optimizing pricing, product, promotions and other decisions that maximize revenues and business performance.
To truly understand the importance of measuring churn, check out this post by Tom Togunz: Why negative churn is such a powerful growth mechanism.