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Keeping track of and understanding your company's revenue is an essential task. It is very hard to evaluate what factors are affecting your revenue stream by looking at your bank account. In this workshop, Pasan walks you through different metrics you can use to determine the relationships between your business activities and your revenue stream. By monitoring metrics such as MRR, Churn and Lifetime Value, you can react to business conditions faster and run your company more efficiently.

[Treehouse Workshops] ?[music]? 0:00 Hi, I'm Pasan, and in today's workshop we are going to look at 0:02 some important revenue metrics that you should be aware of when you run a web start up. 0:06 Now whether it's an e-commerce site or a software as a service company, 0:10 it is always important to keep an eye on certain metrics. 0:13 Now there are many revenue metrics you can monitors, 0:17 but we're going to focus on a few high-level metrics 0:19 that will give you a great overall picture on the health of your company. 0:22 But then you can also fine tune and get all those details that you need to. 0:25 There are many areas of your company that you should be actively measuring-- 0:29 acquisition, activation, retention, and so on. 0:33 Revenue is one of the most important because it is absolutely essential to your company's survival. 0:37 If your activation rates are dropping 0:41 you still have existing customers that you can lean on. 0:44 But the moment revenue starts dropping, you should be worried. 0:46 Now that doesn't mean that you should ignore those other metrics. 0:49 They are still very important. 0:53 Now in this workshop, we're going to use an example 0:55 of a generic software as a service--or SaaS company-- 0:58 to walk through understanding and how to use these metrics. 1:01 So let's build up our company. 1:04 Now this company called, XYZ Incorporated sells an online data analytics software package. 1:07 They break down their package by the number of data points 1:13 that you capture per month that you can purchase, 1:16 and their pricing model is as follows. 1:18 So you have 10,000 data points captured. 1:20 And that's the free individual account at $0.00 a month. 1:24 Then you have the small business account which is 100,000 data points for $100 a month 1:27 Mid-sized--which is a million data points--or $250 a month. 1:32 And then their last account--the premium account--which is five million data points for $500 a month. 1:36 So they have four tiers of pricing targeting four different types of customers. 1:41 Every time a customer pays their monthly bill, you earn revenue. 1:46 Now you can look at how revenue is growing by just checking your bank account. 1:50 But there are several disadvantages to that. 1:54 First, it doesn't give any indication of future earnings. 1:57 You only know of past and current data, but you have your historical data 2:01 which means you can't analyze your future data proactively. 2:06 You don't know what's coming up, and you cannot prepare for unknown scenarios. 2:09 Now it is very hard to interpret any meaningful relationships between 2:13 your customers behaviors and revenue that is coming in when you are only looking at your bank account numbers. 2:17 Now this can be remedied; by looking at metrics 2:22 it will give us a better overall picture and allows us to make more 2:25 informed decisions by connecting those dots between customer behaviors and revenue numbers. 2:28 So the first metric we are going to talk about is recurring revenue. 2:33 Recurring revenue is the amount of subscription revenue that your 2:37 customers owe you over a certain time period. 2:40 This can be measured annually, quarterly, or monthly. 2:43 But in web start ups--which is a fast-paced landscape that changes quite quickly-- 2:46 it makes more sense to look at a number that changes as quickly as the start up does. 2:51 So our metric of choice here is a monthly recurring or MRR. 2:55 MRR is a simple predictor of our growth, but not an actual measurement of our revenue. 3:00 Even though it doesn't show how much money is going into our bank accounts, 3:06 MRR is still a very important metric because it's an indicator of continued business 3:09 where we are going to get paid in the future. 3:14 Calculating MRR is relatively straightforward as well. 3:17 For each active monthly subscription that we have, 3:20 we determine what the subscription would be billed for a full month of service, 3:23 disregarding any discounts or credits. 3:28 So if you've given a customer a credit, you do not take 3:31 any of those things into account; you take the number that they would 3:33 pay if they were paying their month in full. 3:36 And then the sum of all those figures across all customers 3:38 gives us our monthly recurring revenue. 3:42 Now MRR changes constantly as customers change their product or service selections, 3:44 and if they leave the service, or if new customers add on. 3:49 So if a customer upgrades to a higher account, 3:53 naturally their contribution to MRR increases. 3:56 If someone leaves their contribution decreases. 3:59 Let's go over a few examples to clarify this. 4:02 A group signed on to our small business plan, contributes about $100 a month to our MRR, 4:04 even if they had a 50% discount--or any other discount that matter--when they sign up. 4:10 A user signed up on our individual account--which is $0.00 a month--adds $0.00 to our MRR. 4:15 So if a user receives a credit for 3 months off on a premium plan, 4:23 they still contribute this $500 monthly amount to MRR for all 3 months that they would have had credit. 4:27 So remember, even though they had a credit for 3 months you still take 4:34 into MRR the full amount that they would be paying if they didn't have a credit. 4:37 And finally--say a user upgrades from a small business account to a mid-sized account, 4:41 their contribution increases by 150 which is a $150 to $250 a month increase. 4:46 Because of the way that it is calculated, MRR isn't a great indicator of actual revenue being earned. 4:53 Instead, it serves as a predictor of the potential revenue you can earn 5:00 and its corresponding direction in magnitude. 5:04 Suppose our MRR was $180,000; this doesn't mean that we actually made $180,000 in the past month. 5:08 It means that if all of our active subscriptions in their current state, 5:16 is everyone paid--all those accounts have the potential 5:20 to generate us $180,000 every month. 5:24 If this number goes up, it means our potential revenue stream is increasing. 5:27 Let's take a look at some sample data. 5:32 This graph shows the MRR for XYZ Inc. for the past 16 months. 5:36 So while there are some dips like over here, here, and slightly over here, 5:41 the graph is trending up wards in general. 5:47 This means that we're increasing our earnings potential as the months go by-- 5:50 which is a good thing. 5:54 Now actual revenue is a complicated number 5:56 that can be affected by a lot of different things. 5:59 It includes things like--you know--your traditional monthly billing 6:01 to accounts that are paid yearly--even if you are doing monthly subscriptions some could be paid yearly. 6:04 And then there's also groups sales; there's other places you can earn money 6:09 if you have a large cash surplus sitting in the bank that will give you interest revenue 6:13 that adds to your total number--all these things add on. 6:17 So when you are looking at a revenue graph, it's very hard to understand 6:21 the relationships between revenue earned and customer behaviors. 6:24 So we can't really say that we're doing a great job of bringing new customers by looking at a revenue graph. 6:28 So lets look at this example to understand it better. 6:34 Now in this graph--around the 8th month or 7th month mark and the 6:37 12 month mark again--there's a significant increase in revenue for XYZ. 6:42 This is obviously good news for the company. 6:47 But what if we wanted to replicate this data? 6:49 Do we know whether the revenue increased as a direct result of 6:52 increased acquisition and activation methods? 6:55 Or did we bring in more customers? 6:58 Or did we simply decrease our expenses in some way? 7:00 Did we pay off a loan or maybe we cut back our marketing budget? 7:03 Consolidated staff and reduced wages? There are lots of different ways. 7:07 By just looking at revenue, it's hard to say whether we are making more 7:10 because we sold more accounts or if there is some other 7:14 underlying reason that we don't understand. 7:16 By monitoring MRR, we can see how our customer acquistion, 7:20 activation, and retention efforts direct affect our potential revenue. 7:23 Monthly recurrent revenue is easy to calculate when you have a monthly subscription business. 7:28 You just use the actual billed, invoice, or paid numbers; 7:34 you just pull that directly off your software to plug into your MRR calculations. 7:37 But when you have term subscription models it is slightly different. 7:41 And these models are something like--you know--if you allow the customer 7:44 to pay annually or semi-annually, then you don't have a direct monthly figure that you can plug in. 7:48 So with a term subscription to calculate MRR growth, 7:53 you just take the monthly value derived by normalizing the term transaction value. 7:57 For example, a $12,000 contract has a monthly value of $1,000. 8:03 So to calculate the term contribution to MRR--if it's an annual term 8:07 you divide the annual value by 12. 8:13 If it's a semi-annual term, you divide that total number by 6. 8:15 And for a quarterly term, you divide it by 3. 8:19 But to be even more accurate, we can fine tune our MRR number 8:21 to get CMRR. 8:25 Committed Monthly Recurring Revenue. 8:27 Before we do that--however--lets go over our second metric. 8:30 This will help us visit a few more concepts to understand CMRR better. 8:33 Now this second metric we are going to go over is churn. 8:38 Although it's a simple metric to calculate, churn is extremely important 8:42 and can help determine the very future of your company. 8:46 Churn is attrition; basically when a customer leaves your company, 8:48 and stops being a customer, they have "churned." 8:53 To monitor churn, we calculate the churn rate, 8:55 which is the rate at which we're losing customers. 8:58 To calculate churn, you divide the number of customers who cancelled 9:01 by the number of customers. 9:05 Churn kills growth at a SaaS company. 9:07 Since churn is the percentage of customers that leave your service, 9:10 the more customers you have, the more customers you will have will leave the service. 9:14 In simpler terms, total churn--which is the churn rate-- 9:19 times the number of customers is directly proportional 9:22 to increases in your customer base. 9:26 So the more customers you have, the more chances you have of losing those customers. 9:28 In this graph, we have total number of customers against time in years. 9:33 Let's say that you can take over 5 years to get 88,000 customers 9:39 without any churn. 9:45 Growth at this point along the line is 17,300 customers per year. 9:47 If you introduce churn into the picture--and churn is a natural fact of 9:52 running a business--so you will have churn. 9:57 It's naive to say that you will not have churn. 9:58 You can see that it's harder to get to that number. 10:01 In fact, you might not even get there. 10:05 Churn can kill your growth rate. 10:07 Looking back at this graph, in the beginning down here-- 10:09 when you have fewer customers, churn is quite low. 10:12 But as you increase your customer base, and the total number of customers is on the Y axis of the graph-- 10:16 remember your total churn increases as well. 10:22 This is total churn--again--not the churn rate. 10:26 Your churn rate should hopefully never increase. 10:29 Well with a constant churn rate of 20% as your total customer base increases, 10:32 the total churn number will increase we well. 10:37 In this sample graph, we have the line trends upwards initially. 10:40 This is because we are acquiring customers faster than they leave us. 10:45 Acquisition rate is greater than the churn rate. 10:49 When the graph plateaus up here or straightens out, that's when total 10:52 churn has equalled acquisitions. 10:58 So your customers joining exactly equal the customers leaving. 11:00 At this point the churn rate is equal to the acquisition rate. 11:05 Growth starts to slow down and can even stop right here when the graph flattens out. 11:09 So as I mentioned earlier, the acquisition rate was around 17,300 customers per year. 11:13 If our churn rate is 20%, then our acquisition rates equal 11:19 our churn rates at 86,500 customers. 11:24 So we plateau at 86,500 customers, and unless we increase 11:28 our acquisition rates, we won't be able to do better. 11:34 This is very important looking forward. 11:37 We need to know that we can either increase our acquisition rate, 11:40 or decrease our churn rate, or both. 11:44 If you look back at the graph--if we increase our acquisition rates, 11:47 then this purple line dips below. 11:52 If we decrease our churn rate, then the graph--the slope increases which 11:54 means that we can go past that acquisition number. 11:59 This is important if we want to increase our revenue past a certain point. 12:03 Now why is churn important? 12:07 Because churn has such a huge impact on revenue. 12:10 This makes sense if you think about it--obviously when people leave 12:13 you'll lose revenue because they are not paying you any more. 12:16 So let's go back to our MRR graph. 12:19 Right here--the orange curve represents our original MMR graph, right? 12:23 This has no churn; so no customers were leaving monthly. 12:29 This--the orange graph is our earnings potential. 12:33 Now the second graph is with churn introduced into the picture. 12:37 And this is--the blue line is a churn of 10%. 12:41 As you can clearly see, our revenue drops quite a bit-- 12:44 even with a churn of 10% 12:47 In reality, 10% is very modest, and--you know--honestly it will probably be more. 12:50 And the last line--this red line here--is our MRR graph 12:56 with a churn rate of 20%. 12:59 So with the churn rate at 20%, the drop in MRR is quite significant.. 13:02 Looking at the month of February right here, our MRR--our earnings potential-- 13:06 is around $155,000 a month with no churn. 13:12 With 10% churn, it drops down to $140,000. 13:17 With 20% churn, it drops down to $125,000. 13:21 With 20% of our customer base leaving monthly, 13:26 we are losing the chance to make $30,500 more a month. 13:30 That works out to be around $350,000 yearly. It adds up quickly. 13:35 Now when you have a small customer base and a lower MRR figure, 13:41 10% or even 20% churn might not see like a big deal. 13:46 If you go back to the graph, at the very low end-- 13:50 in February--again--one-year ago from our hypothetical scenario, 13:53 we're only losing a couple thousand dollars a month because our customer base is very small. 13:56 So 20% churn means fewer people are leaving than our 20% churn one-year later in February again. 14:02 Keeping churn constant thought, this grows to a much larger dollar amount 14:11 as we grow our customer base and revenue stream. 14:16 Churn provides another valuable insight that directly relates to revenue. 14:18 First off--you should understand that the higher you churn 14:24 the longer it takes to reach profitability. 14:28 Let's look at another graph of MRR in dollars plotted against time in years. 14:31 Now in this graph, the green line over here represents 14:37 our MRR with no churn. 14:41 Our total acquisition cost--for the sake of this example--are 14:43 constant at $30,000. 14:46 In this example, it takes XYZ close to 2½ years to reach break even. 14:49 The point where revenues equal our cost as is indicated by the 14:56 intersection of the white line and the green line in the graph. 14:59 In this example again, we're not considering all costs just directly the 15:02 cost of acquiring the customer against the revenue that those customers bring in. 15:06 Now with a churn of 25%--as is indicated by the blue line here. 15:10 So we're introducing a trend of 25% to this original MRR graph--the green line. 15:15 So it brings it down here. 15:20 The acquisition rate constant--again--at 30,000. 15:22 The slope of the MRR graph decreases eventually. 15:26 And the curve flattens out because--as I explained earlier-- 15:29 with acquisition rates constant, your churn rate could eventually meet up it. 15:32 So your churn numbers equal your acquisition numbers. 15:38 So customers are leaving as fast as XYZ is bringing in new customers. 15:41 So originally with the green line in the no churn MRR, it took us 15:46 2½ years to reach break even. 15:52 With 25% churn which is realistic, then you see it takes longer to get to profitability. 15:54 We're almost taking 5 years.. 16:00 That's twice the amount of time it takes to reach profitability with just a 25% churn rate-- 16:02 which is a huge time gap. 16:08 And then there's a potential third scenario that's even more negative. 16:10 So this third orange line here represents churn rate of 35%. 16:14 Now that is 10% higher than this one, but in this case because 16:20 the churn rate is higher, the graph flattens out earlier than this one. 16:24 So we're reaching our acquisition rate number or compared to this graph, 16:28 then--as you can see--the graph flattens out before he even reached the total customer acquisition costs. 16:33 At this churn rate, MRR never has a potential to grow above acquisition costs. 16:40 What does this mean? It means that XYZ can never reach profitability with the trend rate of 35%. 16:45 Now looping back over to MRR, when you include your churn figures 16:52 in MRR calculations, you are now measuring committed or contracted MRR. 16:56 CMRR only calculates the recurring portions of the subscription revenue 17:02 and removes all thees cancellations that churn brings into account. 17:07 To calculate CMRR, you just take the total number of paying accounts 17:10 that you have in a month, you subtract the number of accounts that you think 17:15 are going to cancel denoted by a churn number. 17:19 And then you multiply that by the relevance monthly subscription amounts 17:22 based on the tier these accounts are in to get CMRR or Contracted Monthly Recurring Revenue. 17:25 So, what have we learned from the past 2 metrics? 17:33 MRR is an indicator of our earning potential. 17:37 It's not actual revenue earned, but combined with cancellation figures 17:41 it gives us a great idea of what we can expect to earn in the upcoming months. 17:45 So this takes away from--you know--when we mentioned earlier 17:50 revenue numbers are either current or historic. 17:52 You can never see future revenue numbers. 17:55 MRR gives you that opportunity. 17:57 Secondly, churn is bad. 18:00 Constantly aim to lower churn. 18:02 There's a couple reasons why. 18:04 So churn--as you saw on these graphs--lowers your MRR. 18:06 This is bad in general. 18:09 If your earnings potential is being lowered, then obviously so are your actual earnings. 18:12 Churn--as we saw in the very most recent graph--means a longer 18:17 time to break even or reach profitability. 18:20 Churn rates should finally always be lower than your acquisition rates. 18:24 If they are equal--as we saw in multiple scenarios--you plateau, 18:28 the graph straightens out, and you will always bring in the same amount of money 18:32 regardless of how many new customers you bring in because that same 18:36 number of customers is exiting the company. 18:39 Finally, if churn is higher than acquisition, you are just going to hemorrhage money over time. 18:42 That brings us to the last metric in this workshop. 18:47 Customer lifetime values. 18:50 Customer lifetime values refers to the revenue that a customer brings in 18:53 for the entire amount of time that they use your service or their lifetime using your product. 18:57 The development and retention of profitable customer relationships, 19:02 is crucial to the success of any business. 19:06 But by understanding customer lifetime values, you can focus on 19:09 long term revenue generating capabilities of each customer, 19:12 And not just short term profits that get month to month. 19:16 Lifetime values affects the execution of many activities across the organization 19:19 including customer acquisition, activation, and retention, 19:24 and it ultimately drivers shareholder value in company equity. 19:27 Now calculating lifetime values or LCV is not so straightforward unlike churn. 19:32 I am going to use a very simple method here to calculate it, 19:37 but in reality determining some of the numbers that go into calculating 19:41 your lifetime values, can be complicated for certain companies. 19:44 You have to decide what contributes towards lifetime values for example. 19:48 Like if Customer B signs up for XYZ small business account through a referral, 19:52 they are obviously bringing in revenue. 19:58 Does this increase the lifetime value for customer A? 20:01 So the person who sent out that initial referral invite, does it increase 20:04 their customer value because they indirectly increased 20:08 our revenue through a referral activity. 20:11 But those are decisions that--you know--each company should make 20:14 relevant to their situation and how their customers behave. 20:17 To get the average revenue per user, divide the total revenue 20:20 by the number of paying accounts. 20:23 So--you know--XYZ has a free tier that I mentioned earlier. 20:26 These obviously don't contribute any sort of revenue to XYZ, 20:29 and so we really don't have a lifetime value for them in our simple scenario, so let's just exclude them. 20:33 For this example--also let's assume our average revenue per user is $2.97. 20:38 Now the way you can get that is just take the number of paying accounts 20:43 across all your customer base, and then divide the total 20:46 revenue by the number of accounts to get average revenue per paying user. 20:49 To determine the average length of a customer relationship, you take the inverse of churn. 20:53 So say our monthly churn rate is at 20%. 20:58 We can use this to calculate the average time our customers stay with us 21:03 or stay with our service. 21:07 So you divide one--one divided by 20% is 5. 21:09 So since we measure churn in months, this means the average 21:12 length of a relationship is 5 months. 21:15 And this is a simple calculation because the rate of which people are leaving us 21:18 is churned, the inverse of that will give us the people that we retain. 21:21 So our LTV is 5 months--the average length of a customer relationship 21:26 times the average revenue per user which is $2.97, 21:30 so that gives us $1,485. 21:33 So on average each customer brings in approximately $1,500 of revenue. 21:37 Lifetime values should always, always be greater than customer acquisition costs. 21:43 If it's not, you're doing something wrong. 21:49 Because if we're spending $1,800 to bring in one account, 21:51 then at a lifetime value of $1,500 approximately, 21:55 we are obviously never making money off the customer. 21:58 We spend more bringing them in than they give us during their entire lifetime. 22:02 And this approximates the lifetime--this is the maximum lifetime 22:06 that we think we can get out of a customer. 22:09 Obviously some people could leave earlier, churn could be higher, 22:11 and then they could give us a certain customers lifetime value--it could even be $100 22:14 and we spend $1,800 bringing them in, and now we only get $100. 22:19 And we're out $1,700. 22:24 So like MRR, lifetime values are also related to churn. 22:26 By decreasing churn, you can keep customers around longer 22:31 and increase their lifetime values; by increasing lifetime values 22:34 you get 2 things done--2 important things. 22:38 First by increasing the amount of profit each customer gives you 22:41 you've increased your MRR. 22:44 This increases your actual revenue. 22:47 Because if you're increasing your earnings potential, then obviously 22:50 your actual earnings can increase as well. 22:52 And this increases your long term profitability. 22:54 Second, by working towards increasing customer lifetime values, 22:58 you are essentially keeping your customers happy and persuading them to stay. 23:02 So if you are trying to increase the lifetime value, you're decreasing churn, 23:05 so you are digging in to why these customers are leaving you in the first place. 23:09 And by trying to solve those problems you are just making the whole experience better, 23:13 and you retain them longer, you earn more money off of them. 23:17 And this is many benefits--the most important being increase referrals. 23:19 There are several ways an increased relationship can lead to higher lifetime values.. 23:24 By keeping customers around longer, you not only increase the base profit that they give you. 23:30 So--for example--you have a customer who pays you $15.00 monthly for 3 months--$45.00 23:34 or if you--you know--make them stay for 7 months, you increase 23:42 that by 3 more months, that'd give another $45.00. 23:45 So now you have $90.00 in total. 23:48 So--but then you also open the door for profit from increased purchases. 23:50 THey can buy more stuff from you; they can raise their accounts. 23:55 And XYZ for example, if they're happy and they stay around for longer, 23:57 and their company grows, they can go from a small business tier 24:02 to a mid-size tier to a premium tier. 24:05 You can also open the door for price premiums, referrals, 24:07 and reduce operating costs over the lifetime of that customer. 24:11 So there you have it--MRR, churn, and lifetime values. 24:15 By monitoring these really important metrics, you should have 24:20 a good understanding of what is affecting your long run profitability 24:23 and what you can do to increase revenue, retention, and lower costs. 24:27 Thanks for watching, and I hope you enjoyed this workshop. 24:33 [Treehouse Workshops] ?[music]? 24:35

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