SaaS Metrics 2.0 – Detailed Definitions


This page is a supplement to the the SaaS Metrics 2.0 blog post. It provides detailed definitions for each of the key metrics used in that post.


Calculating LTV and CAC for a SaaS startup

Unit Economics is a very powerful way to analyze the long term profitability of a SaaS business.

I am often asked for the details of how to compute the various elements, such as CAC and LTV. This post gives the formulae.

CAC – Cost to Acquire a Customer

CAC is defined as follows:
There is a problem with using this formula in the early days, as you may several expensive people in the team that should scale to handle a far number of customers as you grow. In that case, your CAC will be too high. I suggest doing a very simple adjustment to the Sales & Marketing expenses to take only a portion of those salaries and expenses in the early days. That will give a better indication of how CAC will look in the future when you are at scale.

Customer Lifetime

If you start with a cohort of 100 customers and apply a constant churn rate every month, you’ll get an exponential decay, as shown in the following graph (which uses a 3% monthly churn rate):

Mathematically this can be simplified to the following formula to find the average Customer Lifetime:

Note that if the Customer Churn rate is a monthly % or yearly %, then the Customer Lifetime will be for the same time period. Here is a monthly and annual example to illustrate the point:

a) If the Monthly customer churn rate is 3%, then the Customer Lifetime will be 1/0.03 which is 33 months.

b) if the Annual customer churn rate is 20%, then the Customer Lifetime will be 1/0.20 which is 5 years.

Lifetime Value of Customer

In the situation where there is no expansion revenue expected over the lifetime of a customer, you can use this simple formula:

which can also be expressed as follows:
Once again if ARPA is monthly, the churn rate should be monthly.

To truly get an accurate picture of LTV, you should take into consideration Gross Margin. i.e.


However in most SaaS businesses, the gross margin % is high (above 80%), and it’s quite common to use the simpler version of the formula that is not Gross Margin adjusted.

Ron Gill, NetSuite: I’m surprised at how often I see a SaaS product architected in a way that means they’ll never clear a decent gross margin. Including GM in the calc is a great way for you to see there is a big lever on LTV/CAC that is worth focusing on.

For NetSuite, we’ve not only calculated LTV/COCA, but also calculated r-squared of each of the components (to see what has driven improvement) and sensitivity analysis on them (to see what might drive it in the future). GM is an important component.

More complex case
In the specific situation where you expect ARPA to change over the lifespan of the customer due to expansion revenue, this simple version of the formula will not work. We ran into this situation with ZenDesk, where there is a pretty reliable increase in revenue over the life of a customer.

Here’s a graph showing what would happen if you had a cohort of 100 customers that initially started paying you $100 a month, but increased their payment by $5 every month. The monthly Customer Churn Rate is 3%:


As you can see the expansion revenue initially is greater than the losses from churn, but over time the churn takes over and brings down the value of that cohort.

I asked my partner, Stan Reiss, to help with the math to calculate LTV in this more complex situation. Here is what he came up with:

a = initial ARPA per month ( x GM %, if you prefer)
m = monthly growth in ARPA per account
c = Customer Churn Rate (in months)


(This formula makes an assumption that revenue increases at a roughly fixed rate every month for the entire lifetime of the customer. That probably doesn’t hold true for many SaaS businesses, but the goal is to get a rough idea, not to have the absolute perfect answer.)

LTV : CAC Ratio


Our guideline for a successful SaaS business is that this number should be higher than 3.

Ron Gill, NetSuite: It is most important to track this metric over time to make sure you’re driving improvement. And, look at investment and how it will impact.

(The guideline assumes you are using the simpler LTV formula that does not include a Gross Margin adjustment, and that you have a Gross Margin of 80% or higher.)


Months to recover CAC

To be perfectly accurate, this should include a Gross Margin adjustment as follows:
However in our guideline which states that Months to Recover CAC should be less than 12, we are assuming that you are using the simpler formula, and have a Gross Margin of 80% or higher.

The Metrics to help understand Bookings

MRR The Monthly Recurring Revenue at the end of each month. Computed by taking the MRR from the previous month and adding Net New MRR.
ARR Annualized Run Rate = MRR x 12ARR is annual run-rate of recurring revenue from the current installed base. This is annual recurring revenue for the coming twelve months if you don’t add or churn anything.
ACV Annual Contract Value of a subscription agreement.
New MRR/ACV The increase in MRR from new customers in the current month.
Churned MRR/ACV The lost MRR from churning customers in the current month.
Expansion MRR/ACV The increase in MRR from expansion in your installed base in the current month.
Net New MRR/ACV Net New MRR = New MRR + Expansion MRR – Churned MRRThis is the sum of the three different components that will change MRR during each month.
Bookings The total dollar value of all new contracts signed. Usually taken as an annualized number even if the contract period is longer than one year.Since the bookings number might have a mix of different durations (e.g. month-to-month;  6 months; 12 months) this number is not very helpful for understanding the business.To really understand what is going on in your SaaS Business, you should look at the following components:a) What happened with new customers:

  • New MRR/ACV from new customer contracts

b) What happened in your installed base:

  • Renewals
  • Churned MRR/ACV
  • Expansion bookings

The sum of all of the above:

  • Net New MRR/ACV
Billings Billings is the amount that you have invoiced that is due for payment shortly.
Revenue Revenue is amount of money that can be recognized according to accounting policy. Even if it is paid for upfront, usually subscription revenue can only be recognized ratably over time as the service is delivered.If more money has been paid than can be recognized, the difference goes into a balance sheet item called Deferred Revenue.
Average Contract Length Assuming a mix of different contract lengths, this gives you the average duration in months or years.
Months up front Average of months (or years) of payment received in-advance with new bookings. Getting paid in advance has a big positive impact on cash flow. This metric has been used at both HubSpot and NetSuite in the past as a way to incent sales people to get more paid up front when a new customer is signed. However asking for more money up front may turn off certain customers, and result in fewer new customers, so be careful how you balance these two conflicting goals.
ARPA – Average monthly recurring Revenue per Account This number is tells you the average monthly revenue per customer. It is useful to look at this for just the new customers booked in the month. Plot a trend line to show you the average price point that your new customers have chosen.

Bookings, Billings and Revenue – An example

Since there can be some confusion around the difference between bookings, billings and revenue, here is a simple example to help clarify them: Imagine you signed a new contract with a customer with a one year term, specifying that you provide your service to them for $1,000 per month, with an upfront payment of six months:

  • Your bookings would be $12,000 (the entire contract value)
  • You would bill $6,000 in the first month, then $1,000 per month from the seventh month onwards.
  • You would recognized $1,000 in revenue for each month of the contract. (This is dictated by GAAP accounting policy.)

For the example above, the balance sheet and income statement impact of these items is as follows:

  • Bookings do not affect either the balance sheet or the income statement.
  • When you bill $6,000 in the first month, but can only recognize $1,000 in revenue (income statement), and the other $5,000 goes into deferred revenue on the balance sheet (a liability).
  • Each month thereafter until another $1,000 can be recognized as revenue (income statement), and that reduces the deferred revenue liability on the balance sheet.

The Metrics for Churn

The following shows the metrics to understand Churn:

# of new Customers The number of new customers added this month
# of churned Customers The number of customers lost due to churn this month
Net New Customers Net New Customers = # of new Customers – # of churned CustomersThis is the net number of new customers added once lost customers due to churn has been taken into account.
% Customer Churn image
% MRR Churn Defined as lost revenue due to churned customers as a percentage of total recurring revenue.image(See below for a description of why this is different to % Customer Churn.)
% MRR Expansion Defined as the expansion revenue from existing customers as a percentage of total revenue.image
% Net MRR Churn imageThis is the number that will go negative if the Expansion revenue from existing customers starts to outstrip the lost revenue from churn.Getting to negative Net MRR Churn is a great goal for a SaaS company.
% Renewal Rate (Customers) renewal-rate-custs 

It can be confusing to look at both your renewal rate (which should be just 1- Churn) in addition to churn. However in a model where you have yearly contracts being renewed, the two numbers can actually be different. For example, in the early days of a startup, you might have low churn because many of your customers have not yet reached the point where they could drop your service because of the length of their contract. In that situation, your churn number will not accurately predict what is really going to happen when you reach steady state. So a better number to look at is how many of your customers are renewing at the point where their contract expires. That is what this number measures.

When you reach steady state, this number should be equal to 1 – % Customer Churn.

% Renewal Rate ($’s) renewal-rate-dollars
Similar to the number above, but instead of looking at the number of customers, it looks at the dollar value of the renewed contracts. It’s important to look at both, as they each tell an useful part of the story. If you were losing a lot of customers, you’d want to know why. Similarly, if you were only losing a few customers, but they were your biggest $ value customers, you’d also want to know that as well.



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  • David Skok

    That is definitely expansion revenue. It’s a wonderful thing to have, so congratulations. It would also be expansion revenue if you can get them to upgrade. At some point in the future worth asking how you can make that edition more compelling.
    Best, David

  • Nelly

    Hi David,

    These insights are incredibly useful in the company I’m working actually.
    Quick question for you : how do you calculate ACV? we are booking annual and semi-annual contracts and I had the feeling that Bookings new customers = ACV but when I look in your Excel file, I can see it’s different.

    Many thanks for your help

  • David Skok

    ACV is the annualized value of either a single customer, or all customers (depending on which context). So if you have a new customer that signs up with an annual contract valued at $100 per month, or $1,200 per year, ACV for that customer would be $1,200.
    If you currently have 20 customers all signed with at $1,200 per year, but with varying contract start and end times, you would ignore the different start and end times, and compute ACV for the customer base as 20 x $1,200. The churn number provides outsiders/investors with the picture of what is the likely loss of revenue going forward as contracts expire.
    I hope I answered the question you were asking, as I had to guess a bit at what you were looking for.

  • TMT

    I’m new to the SaaS industry as a financial manager and found this extremely helpful in getting a better understanding of the metrics. Thanks!

  • Nelly

    Many thanks David, that’s perfectly clear !!
    As we are also selling 6 months contract (let’s say $600 for such a period), for ACV calculation should I take into account the value of the contract i.e. $600 or the value of 1 year contract ($1,200) even if we don’t know yet if the client will renew its contract for another 6 months?
    In my metrics, should I distinguish semi-annual and annual contracts or not?
    Thanks again

  • David Skok

    You would look at the value of that customer over a full year. However in your situation, if I was talking to investors, I would focus my metrics more around MRR than ACV, as there is potential for that investor to assume that every contract you have is annual, which would be misleading.
    The other thing that I would recommend is looking at the churn rate for the customers on 6 and 12 months contracts separately. I would expect that you might see a higher churn rate for the 6 month contracts than for the 12. It will be useful to know this, as you would also now know the LTV was different.
    If there is a big difference in churn, you might track the amount of revenue that is on 6 month contracts separately from those on 12 months. But I don’t believe you will see that big of a difference in churn rate.
    Beyond that I would not recommend adding more complexity, as I don’t see you getting enough benefit to make it worth the effort.

  • ak

    Hi David,

    Thanks again for these posts. We are planning to present to several VCs this Winter and I was wondering if you might have an guides or suggestions as to the most critical data or best practices for these presentations from a data analytics perspective? Are there certain details to leave out, certain things to make sure to talk about? We want to be as efficient with everyones time as possible, but not leave any stone unturned. We are a 3 year old company at this point.

    Thanks very much -

  • David Skok

    If you send me a copy of your presentation, I will be happy to go through it and provide you with some feedback.
    Most VC’s seem to have read this post, and so will be looking for the following:

    - MRR Churn Rate (and be ready to discuss Customer Churn Rate)
    - CAC

    - LTV

    - LTV:CAC ratio

    - Months to recover CAC

    - MRR Graph

    - Net New MRR Graph (showing the three component parts as well: New MRR, Churned MRR, Expansion MRR)
    These should be posted alongside of your traditional financial elements such as Gross Margin, Expenses, EBITDA, Cash, No of Employees by Dept, etc.

  • ak

    Thanks David! I will run the idea by the others and get back with you. Thanks very much for the offer! I have built out most of the spreadsheets you have on your site, but am confused a little by how to show negative churn. Since we have a lot of expansion customers/revenue in the form of customers recruiting others in their office, shouldn’t we be able to show a negative churn number? How would the formula you present for churn ever show negative churn?

    Would this be the correct formula to take into consideration negative churn? Churn=(Churned-Expansion)/Total customers last month

    Thanks very much,

  • David Skok

    You nearly have the right formula. Your error is dividing by Total Customers Last Month. It’s easy to make this mistake, as there are two ways to look at churn: one is by Customer, and the other is Revenue Churn. Here we are interested in Revenue Churn. You mixed the two types of churn in one forumula which doesn’t work. Instead of dividing by Total Customers Last Month, divide by total MRR Last Month. Here is my formula for Net Revenue Churn:
    Net Revenue Churn = (MRR Revenue Churn – MRR Expansion Revenue) / Total MRR Last Month
    The number will automatically come out as negative if your expansion revenue from your existing customers exceeds your lost revenue from your existing customers.
    I hope that helps.

  • ak

    Great! Thanks very much David.

  • OJ

    My experience is mostly from mobile services where the same type of metrics is commonly used. Here we always take churn at the average customer base – ie. churn over (base start of month + base end of month)/2

  • David Skok

    Interesting. Thanks. I am not sure I like that, as it is unlikely in the SaaS world that someone would join and then leave in less than a month. If I am right, then I think it is correct to use the end of last month’s customer base.

  • GuillermoDV

    Hi David, Thanks for again for your post! For early stage CAC calculation, how should select a portion of S&M initial expenses? In my company’s case, the initial expenses include the hiring of the S&M team, outsourcing a digital media company for website design and content, expensing in SEO and Marketing / PR events. What portion of theses costs should I consider for early CAC? For calculating CAC in future periods, should I take into account the total monthly S&M or only the aggregate amount expensed to capture new customers? Many thanks!

  • David Skok

    I would look at the amount that you believe represents your best guess at what you’d see in a longer term steady state situation. So ignore one time things, but use a portion of things that are likely to be reduced in the future steady state. I hope that helps.

  • fguzman

    Hi David, great post!! I need you help. We provide SaaS for the lending industry. We usually charge a “Setup Fee” for implementation services (typically 2-3 months of work) and when we finish the implementation we start collecting the monthly fee (when the system is in production). In order to implement the dashboard excel file that you are sharing with us, I have the following questions:

    - The CAC is exclusively for sales and marketing, and shouldn’t include the setup fee cost, correct?
    - The setup fee has a different gross margin than the monthly payment, so how can I add this in your dashboard model?
    - The setup fee is established on case by case basis and sometimes we make money from it and sometime we don’t. So, I would say that if we loos money that would be considered as CAC, correct?
    - I think that the setup fee is part of the overall booking, correct?
    - In our business model we provide professional services to our customer during the life of the contract. This item is very important in our bottom line. I saw that your model does not include that… am I right? Can be added? What do you suggest?

    I would love to have a excel file version with this included… can we work on it! I will be happy to help!!

    Thank you so much for your time and support!

  • GuillermoDV

    Got it! Thank you David

  • David Skok

    Thanks for your interest and commentary. I would love to be able to help you work on that specific version of the spreadsheet, but am unfortunately in the position where I just don’t have the time. My goal in providing the spreadsheet was really to show the nature of the P&L trough. Unfortunately to provide a generic model that covers all situations is quite a lot more work. I apologize that I am not able to help you get that done, but I hope you understand and are able to complete that on your own steam.
    Best, David

  • Alun Rafique

    Hi David. First of all, great post and we are currently following it.

    One question: Do you find that the second half of the LTV formula which takes account of expansion can unduly increase the LTV at low rates of C (<10%)?

  • Alun Rafique

    Hi David, did you have any thoughts on my question related to low rate of churn?

  • David Skok

    Sorry for the delayed reply. I didn’t fully understand your first question. Can you explain your situation so I can give you a meaningful answer. Feel free to email me directly if your situation is confidential. Thanks, David

  • Nelly

    Hi David,

    I’ve created all the metrics for my company and I’m actually working on a business plan for the next 3 years. What are your advices to get realistic metrics? How can we make a projection of our MRR and ARR (we are selling both monthly and annually subscriptions)? Do you suggest me to use the growth and churn rate the company triggered in the previous years and adjust depending on the expansion and upgrade planned for our products? Thanks !

  • David Skok

    That sounds like a good plan. You have some historical data which is the best guide to what will happen going forward. If you think that will change, then make it clear to all concerned what your assumptions are, and then test them going forward and modify the plan as you get real data.

  • Alun Rafique

    Hi David. Cheers for the reply, I am building up the metrics for our company and I have found your blog unbelievably helpful. With respect to my question I have produced a graph to show you what I mean.
    With a churn < 10% the LTV can really escalate using the formula a/c+m*(1-c)/c*c. I was wondering if you have experience with the accuracy of this formula and its prediction rates.

  • David Skok

    Hi Alun, many thanks. The graph produced by inputting the data you have in your situation clearly looks wrong. It makes me wonder whether there isn’t a simple error of some kind. Can you send me the values that you are using for the different variables, and we will get to the bottom of it. Thank you.

  • Alun Rafique

    Thanks David. I have sent a mail to the address for your attention. Looking forward to hearing from you and many thanks in advance.

  • David Skok

    Thanks Alun. I got the data. I will get back to you as soon as I have had a chance to take a look.

  • David Skok

    Hi Alun, I took a look at your spreadsheet, and it appears to be working correctly. The reason your graph rises so steeply as churn goes down is because the lifetime of the customer is going up dramatically. The second part of the formula only increases the effect by a small amount to reflect the fact that you have your customers adding another $10 per month to their MRR. To show what I mean, I would recommend that you break down the formula into two parts calculating first a/c, and the the second part that takes into account growth. I think that will make it all clear.
    Let me know if this still does not make sense to you.

  • Alun Rafique

    Many thanks David. This makes perfect sense and brings me back to my original question on the validity of the second half of the formula for low values of c? Would you have any detail on how this formula was created and what are the assumptions behind it? (perhaps Stan Reiss can help)

  • Zach Bulygo

    Hi David,
    In your Net MRR Churn formula you mention that you can achieve negative churn if expansion revenue exceeds MRR churn. Couldn’t you also take into account new customer MRR? For that, the formula would be:

    (Churned – Expansion – New MRR) / Previous Months MRR

    You can also use it percentage churn. If new customer signups exceeds churned customers, you’ve achieved negative churn.

    Am I missing something?

  • David Skok

    Hi Zach, I like to separate what is going on with new customers from what is going on in the installed base. The New New MRR number does take into consideration the new customer bookings. But those would be confusing if added to churn, as they have nothing to do with the existing customers, and churn is all about what is going on in the installed based.
    I hope that makes sense.

  • Alun Rafique

    Hi David. I broke down the graph:

    I can see what you mean the the inverse relationship to c is the main driving factor until c is very low. The key for us is to get as much data as possible to gain the right value of c or it can skew the ratio.

  • Stan Reiss

    Alun, really good to see you take such an interest here! Let me see if I can give you a two part answer. Part 1 is that this is just a formula, and as such it assumes a certain behavior in the world. Its validity will be limited by a) the extent the model it implies mirrors the real world and b) the user’s ability to estimate the variables needed.
    In this case I assumed a very simple world, where organic growth is perfectly linear and churn is completely exponential. It makes for a solvable and explainable formula, but the truth is the real world is never perfectly linear or exponential.

    Part 2 is what’s in the formula and how it therefore behaves.

    Restating the definitions:

    a = initial ARPA per month ( x GM %, if you prefer)
    m = monthly growth in ARPA per account
    c = Customer Churn Rate (in months)

    You can see that revenue at time t, R(t) will equal to the
    initial ARPA a, plus the growth in ARPA since the beginning, which is m*t, adjusted down for the customers that have churned, or multiplied by (1-c)^t.

    So R(t) = (a + mt)(1 – c)^t

    LTV is just the infinite sum of R(t) over all values of t, or

    LTV = Sum from t=0 to infinity of (a + mt)(1 – c)^t.

    If you solve the infinite sum you’ll end up with LTV = a/c + m(1 – c)/c^2.

    Note that you could have written this as two terms:

    The value of the initial ARPA as it decays due to churn,
    R_originalARPA(t) = a(1 – c)^t

    Plus the value of the growth, where
    R_growth(t) = mt(1 – c)^t

    If you solve the infinite sums for each, you’ll end up with two parts of total LTV equation. The familiar a/c for the portion of the LTV derived from the initial sale, or initial ARPA, and m(1-c)/c^2 for the portion derived from the growth.

    Depending on the relative values of A, c, and m, any of the terms can dominate. I encourage you to just play in Excel comparing the results that come out of the equation
    with what you’d get if you just calculated the value at each time t and summed them up (easy to just sum up over 100 periods in Excel, for most values of c that’ll give you the answer).

    The conclusions are quite logical. When churn is high and growth is low, the value of the initial sale dominates, and if you look at the structure of the equation that’s what you’d expect. When growth is high but the initial sale low, the growth in the account will drive LTV for all but the highest values of churn. Likewise, if churn is ultra low – the accounts stay for a really long time, and growth is not tiny, you’d expect the growth to matter much more than the size of the initial sale.

    I hope this is helpful!

  • Alun Rafique

    Hi Stan. Many thanks for the comprehensive post and this managed to side track me for several hours looking at Taylor expansions, series and sums to infinity. I am really not sure that is the best thing for a Saturday night! It actually does make sense and gives me confidence in the results that are being produced. You answer is very much appreciated. Many thanks.

  • Stan Reiss

    Any time, like you I had to dust off a piece of my brain when thinking about simplifying the equation. But it’s fun to do that every now and then to realize all that time in class wasn’t wasted! :-)

  • Alun Rafique

    Absolutely. I knew all those hours in lectures had to end up being useful at some time, its a shame it took 20 years!

  • Zach Bulygo

    I understand – thanks David!

  • Denis Altudov

    Hi David. Shouldn’t you also discount future cash flow when computing LTV? A 5% annual discount rate reduces present value of the cash flow by 20% over 10 years and by 80% over 100 years.
    I feel the best way is to add the discount into churn rate in your formula?

  • David Skok

    You are correct: you should use discounted cash flows to get an accurate value. The problem is that doing a discounted cash flow analysis adds a lot of complexity to the formula. I have found that when things get too complicated, they don’t get used. My goal with these metrics is to keep them simple so that they provide an easy tool for entrepreneurs to use to make decisions. Most people only have a lifetime that is in the 3 to 8 year range, so the impact is not huge. That’s why I went with the simpler formula.

  • Suraj

    Hi David,

    Excellent blog ! We have been building an internal tool to track churn and have closely followed your blog. One of things we currently do to calculate MRR is to simply divide the total contract value by the number of months in the contract term.

    For calculating churned MRR I have been using MRR (i.e just one month’s MRR) for the churned customer. For ex: if the contract amount was $1200 for 1 year term and the customer left at the end of the term then the churned MRR = 1 month’s MRR = $100. Do you think this makes sense as the actual amount lost is $1200 (renewal).

    Appreciate any suggestions.

    Thanks !

  • David Skok

    Hi Suraj,

    From your description of how you calculate MRR, I think there may be a misunderstanding. MRR should be the total of monthly recurring revenue from all current customers. It does not look forward to ask the question of how many months are left in the contract. The assumption is that you will renew most contracts at the end, and those that don’t renew will be accounted for in the Churn number.
    I know this may seem odd, but it is correct to calculate churned MRR as 1/12th of the lost contract value. But if all your contracts are annual, you might want to work with ARR, instead of MRR. ARR is simply 12 times MRR. That will more clearly show the cost of losing a customer contract.
    Best, David

  • Snehal

    Hi David, Thank you for the very helpful post and the formulae.

    I had a question regarding calculating Churn MRR. We have a subscription model, where a customer pays monthly as well as annually. For eg. a customer has signed up for monthly subscription and his billing cycle starts 15th of every month. Now he decides to cancel on 20th of same month. We do charge him until the next billing cycle i.e 15th of next month (expiry). So in this case should I account this customer to be lost in the month he canceled or in the month that it actually expires (next month) while calculating the MRR? Also what would be the case for Annual subscriptions in MRRs if they cancel mid-year? when should I account them for churn?


  • David Skok

    That’s a good question. For Revenue Churn, I would count that customer lost in the month where you no longer are able to bill them. Same answer for both situations. However if you are wanting to get a true feeling for Customer Churn (different to Revenue Churn) you might want to count them as churned in the month after they tell you they are cancelling. That will give you a clearer picture of how long it is taking them to decide to cancel.

  • Guest

    Hi, we’re just starting to figure out how these stats apply to our business.
    Reading the conversation above, most of our cancellations do happen in the month that the customers signed up. We call them “quick cancels” because they changed their mind quickly. With that information, should I use the total customer base from the previous month or from the current month to calculate % customer churn?

  • Ellen Pfeiffer

    Hi, we’re just starting to figure out these figures for our business. Reading the conversation above, most of our cancellations are within the month of subscription. We call them “quick cancels” because they changed their mind quickly. With that in mind, should we calculate % customer churn using the current month’s ending customer base, or the previous month’s ending customer base?

  • Ellen Pfeiffer

    Hi David, we are starting to figure out these figures for the first time and a have a couple questions about how to adapt them to our business model.

    First, on the SaaS Metrics 2.0 Dashboard, there is Starting MRR and Ending MRR, which lead to ARR. I can’t seem to find a definition about these calculations and what they mean. Can you explain them?

    Second, we give some of our customers a “trial period” of 1-3 months where they can use the service before beginning their monthly payments. Should I included them as “new customers” for the month they started the trial, or the month when their trial ended and they began paying monthly payments? Also, which should I use for putting them in a Cohort?

    Third, our customers subscribe to our service indefinitely. There’s no real duration time for the subscriptions. How would I calculate the “Deal Size” or “Contract Length” which are used on the SaaS Metrics dashboard?

    Thank you! We love all these posts, and they’re really helping us understand our business.

  • David Skok

    Hi Ellen, I would take out these quick cancels and deal with them separately. They sound like people who thought this might be applicable, but quickly discovered some issue. They’re worth studying more to find out the reasons why they’re canceling. Some of these might be addressable.
    Best, David

  • David Skok

    Hi Ellen, I hope the following clarifies:

    Starting MRR = MRR (Monthly Recurring Revenue) at the start of the month Ending MRR = MRR at the end of the Month

    ARR = Annual Recurring Revenue (more often used in business where most of the contracts are one year in length). ARR = 12 x MRR

    ACV = Annual Contract Value, this is often used as a way to measure how much was booked in a month or quarter. ACV = the sum of all contracts booked in the quarter, looking at the annual recurring revenue of those contracts.
    Deal size: I usually use that term in the context of “average deal size”. In the recurring revenue world, it is a little hard to work with this term if you have bookings of differing terms (e.g. some monthly, some annual). In that situation the best way to normalize these is to bring them back to MRR, even though the length of the commitment is different. If you were looking at Bookings, you may want to track the committed value of each new deal closed. But if the time periods are mixed, the number is going to be highly confusing and not tell you much. So again, I’d recommend bringing everything back to one normalized value, using either MRR if there are mixed term lengths, or ACV if they are all at least one year in length.
    To calculate Contract Length simply compute the average length of each of the new contracts booked. That will give you a sense for how well sales are doing at closing deals with longer contract lengths, which is usually advantageous.
    Please let me know if I missed a part of your question, or if there is still a question. Best, David