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Negative Churn

<a
href=”http://derekpilling.com/wp-content/uploads/2015/03/melting-ice-psd-1.jpg”><img
class=”wp-image-1163 alignright” src=”http://derekpilling.com/wp-content/uploads/2015/03/melting-ice-psd-1-300×200.jpg” alt=”melting-ice-psd (1)” width=”218″ height=”145″ />In a board meeting yesterday, we had a brief discussion around “negative churn”. Negative churn is a catchy phrase and apparently a hot-topic in some SaaS circles. I like some of the concepts and disciplines that an understanding of negative churn implies, but I also think it is an unnecessary concept that actually makes it more difficult to understand the inner workings of an MRR based SaaS business. Some background…

What is Negative Churn?

Negative Churn is an increase in revenue which occurs when the change in revenue within an installed base of customers is net positive from one period to the next. Negative Churn implies that the revenue gained from existing customers who purchase more over time exceeds revenue lost from existing customers who purchase less over time, including customers lost outright.

The term “negative churn” is an attempt to understand net organic revenue growth within an installed base of customers in the context of churn. Understanding the change in revenue within an installed base of customers is really important. But seeking to understand organic installed base growth in the context of churn begs a question: What if the revenue gained from existing customers who purchase more over time is less than revenue lost from existing customers who purchase less over time. Such a scenario would indicate that Negative Churn is NEGATIVE! Can Negative Churn be negative? Should we call this scenario Negative, Negative Churn? Of course not.

Conflating Churn and Revenue Lift

The fact that Negative Churn is a double negative is the first reason to not like it. Further, Churn is always and unambiguously revenue reducing. Therefore, Churn is always negative. Churn is never, ever positive.

Churn should be analyzed independently from the revenue lift from upsell (or extension) that has the potential to drive organic revenue growth in an installed base of customers. Conflating the two is dangerous. To some degree, the concept of Negative Churn is a response to companies having difficulty calculating a churn rate. Calculating churn is never as easy as it seems it should be. There are two types of churn that are critical to measure and analyze, each separately.

Customer Loss Churn

Customer loss churn is the easiest type of churn to understand and measure. Customer loss churn occurs when a customer is no longer a customer and all of the revenue (MRR and otherwise) that the company earned from that customer is no longer.

<img
class=”mathtex-equation-editor” src=”http://chart.apis.google.com/chart?cht=tx&chl=Customer%5C%2CLoss%5C%2CChurn%20%3D%20%5Cfrac%7BMRR%5C%2CLost%5C%2CFrom%5C%2CCustomers%5C%2Cwho%5C%2CTerminated%5C%2CServices%7D%7BMRR%5C%2Cat%5C%2Cthe%5C%2CEnd%5C%2Cof%5C%2Cthe%5C%2CPrior%5C%2CPeriod%7D” alt=”Customer\,Loss\,Churn = \frac{MRR\,Lost\,From\,Customers\,who\,Terminated\,Services}{MRR\,at\,the\,End\,of\,the\,Prior\,Period}” align=”absmiddle” />

Customer loss churn can be measured in terms of either customer count or revenue; the revenue version used above. Unless your customers are homogeneous in terms of their monthly revenue, the revenue-based version of Customer Loss Churn is a far better indicator of the impact of churn on your business.

Revenue Churn

Revenue Churn occurs when the revenue you receive from a customer falls in total dollar amount. Several factors drive Revenue Churn. Common examples including a customer using less of your service (fewer seats, lower utilization, etc.), and a customer renegotiating the rate at which they buy from you downward. The customer is still a customer, but you’ve incurred a revenue reduction. I recommend that for each period over which you are measuring churn that you capture all of the Revenue Churn from customers whose revenue declined during a period and state it as a % of the MRR at the end of the prior period.

<img
class=”mathtex-equation-editor” src=”http://chart.apis.google.com/chart?cht=tx&chl=Revenue%5C%2CChurn%3D%20%5Cfrac%7BMRR%5C%2CLost%5C%2CFrom%5C%2CCustomers%5C%2Cwho%5C%2CDecreased%5C%2Cin%5C%2CRevenue%7D%7BMRR%5C%2Cat%5C%2Cthe%5C%2CEnd%5C%2Cof%5C%2Cthe%5C%2CPrior%5C%2CPeriod%7D” alt=”Revenue\,Churn= \frac{MRR\,Lost\,From\,Customers\,who\,Decreased\,in\,Revenue}{MRR\,at\,the\,End\,of\,the\,Prior\,Period}” align=”absmiddle” />

Once you have each of Customer Loss Churn and Revenue Churn nailed, you can add them together and derive Total Churn.

<img
class=”mathtex-equation-editor” src=”http://chart.apis.google.com/chart?cht=tx&chl=Total%5C%2CChurn%20%3D%20Customer%5C%2CLoss%5C%2CChurn%20%2B%20Revenue%5C%2CChurn” alt=”Total\,Churn = Customer\,Loss\,Churn + Revenue\,Churn” align=”absmiddle” />

Installed Base Growth/Decline

So now that we’ve got churn nailed, lets turn attention to the organic growth/decline conundrum that the concept of Negative Churn was designed to address. One of the great facets of SaaS businesses is that they have the potential to capture more share of wallet from their customers over time. In my experience greater share of wallet comes from three primary sources:

  • Higher Utilization: Many SaaS models have a utility based component to their pricing model. Utilization can be based on an unlimited number of factors including, but not limited to the number of transactions processed, cpu/storage utilization, etc. Higher utilization means more revenue.
  • More Seats: Most SaaS models have a seat-based component to their pricing. The more seats (users), the higher the cost to the customer.
  • Cross-Sell: SaaS companies should strive to capture greater share of wallet by selling other services that are adjacent to the core service offering, thereby capturing additional revenue per customer by providing a broader array of services those customers demand.

Whatever the source, it is important to measure and maximize revenue increases that are attributable to these sources. One can capture these revenue increases in a factor I refer to as Revenue Lift.

<img
class=”mathtex-equation-editor” src=”http://chart.apis.google.com/chart?cht=tx&chl=Revenue%5C%2CLift%20%3D%20%5Cfrac%7BMRR%5C%2CGained%5C%2CFrom%5C%2CCustomers%5C%2Cwho%5C%2CIncreased%5C%2Cin%5C%2CRevenue%7D%7BMRR%5C%2Cat%5C%2Cthe%5C%2CEnd%5C%2Cof%5C%2Cthe%5C%2CPrior%5C%2CPeriod%7D” alt=”Revenue\,Lift = \frac{MRR\,Gained\,From\,Customers\,who\,Increased\,in\,Revenue}{MRR\,at\,the\,End\,of\,the\,Prior\,Period}” align=”absmiddle” />

Revenue Lift is the opposite of Revenue Churn. Just like Churn can never be a positive, Revenue Lift can never be a negative number, because the numerator includes only those customers whose revenue increased during a particular period and is therefore a positive number.

Organic Growth/Decline in the Installed Base

Now we can answer the question that Negative Churn is trying to address: What is the organic growth/decline in revenue from our installed base of customers? Given that we’ve done the work to parse apart Customer Loss Churn, Revenue Churn and Revenue Lift, the remaining work is a snap.

<img
class=”mathtex-equation-editor” src=”http://chart.apis.google.com/chart?cht=tx&chl=Organic%5C%2CGrowth%2FDecline%20%3D%20Revenue%5C%2CLift%20-%20Revenue%5C%2CChurn” alt=”Organic\,Growth/Decline = Revenue\,Lift – Revenue\,Churn” align=”absmiddle” />

Stated as a percentage:

<img
class=”mathtex-equation-editor” src=”http://chart.apis.google.com/chart?cht=tx&chl=Organic%5C%2CGrowth%2FDecline%5C%2CRate%20%3D%20%5Cfrac%7BRevenue%5C%2CLift%20-%20Revenue%5C%2CChurn%7D%7BMRR%5C%2Cat%5C%2Cthe%5C%2CEnd%5C%2Cof%5C%2Cthe%5C%2CPrior%5C%2CPeriod%7D” alt=”Organic\,Growth/Decline\,Rate = \frac{Revenue\,Lift – Revenue\,Churn}{MRR\,at\,the\,End\,of\,the\,Prior\,Period}” align=”absmiddle” />

If the Organic Growth/Decline calculations results in a positive number, congratulations, the revenue from your installed and continuing base of customers is increasing; you have organic growth in your installed base. Lets also hope that your new logo bookings more than offset your Customer Loss Churn. If the Organic Growth/Decline calculations results in a negative number, you have Organic Decline in your installed base. In order to fill the hole, you need to book an even greater amount of MRR from new logos to offset your Customer Loss Churn and Organic Decline in revenue from your installed base

Note that I prefer to exclude Customer Loss Churn from the Organic Growth/Decline calculation because I prefer to evaluate the revenue trend for customers who have made the choice to continue to be customers in isolation from Customer Loss Churn. I’m not suggesting ignoring Customer Loss Churn; quite the contrary; by isolating it, you have to focus on it. In fact, you need your bookings from new logos to fill the hold from Customer Loss Churn and then some, if your business is going to grow.

Organic Growth/Decline vs Negative Churn

For me, Negative Churn tries to accomplish too much with one statistic. And because the results of the Negative Churn calculations can actually be a negative number (i.e. Negative, Negative Churn), I strongly prefer the Organic Growth/Decline calculations above to the Negative Churn construct.  I don’t argue with the intent behind the concept of Negative Churn; the intent is good. I just believe that looking at Organic Growth/Decline in revenue from an installed user base and each of its component parts can yield far greater insight and understanding.

I should add that the statistics presented here aren’t comprehensive for understanding Organic Growth/Decline. It is important to understand the distribution of where both Revenue Churn and Revenue Lift are coming from. If Revenue Churn is highly concentrated among a small set of customers, it is important to understand but perhaps not a crisis. On the flip-side if Revenue Lift is concentrated among a small number of customers it might not be repeatable, so you should stop the high-fives immediately. You should always take a look at the distribution and dispersion of Churn and Revenue Lift across your customer base as well as the root causes behind the results.

Other Negative Churn Resources

Much has been written about negative churn. From what I can gather, Dave Skok of Matrix Partners first coined the term in a 2012 post about <a
title=”Why churn is SO critical to success in SaaS” href=”http://www.forentrepreneurs.com/why-churn-is-critical-in-saas/” target=”_blank”>Why churn is SO critical to success in SaaS. Tomasz Tunguz of Redpoint wrote a piece focused on <a
title=”Negative Churn” href=”http://tomtunguz.com/negative-churn/” target=”_blank”>Negative Churn as did <a
title=”Negative SaaS Churn” href=”http://sixteenventures.com/negative-saas-churn-rate” target=”_blank”>Lincoln Murphy of Sixteen Ventures. There is a lot of good stuff in these posts and others that I’ve read. They key take-away is that if you can drive net positive organic growth in your installed and continuing base of customers, you win, particularly if you continue to acquire new customers at a rate that exceeds your Customer Loss Churn.

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Basics of Unit Economics Analysis

When an investment passes our first-screen at Meritage Funds, the first deep-dive we typically do is on the unit economics of the business. Unit economics are the fundamental financial building blocks of a business. If you can pin down the unit economics, you can determine contribution margins, break-even points and perform ROI calculations all of which can help to determine whether a Company’s economic engine works. Without an understanding of unit economics, predicting whether a business can be profitable in the long-term is all guess-work.

I’m a believer that every business – no matter the scale – should have a point of view on its unit economics. That includes you startups. However, the concept is not as easy to apply as most hope and is frequently mis-applied. Here are some basic principles I use when thinking about unit economics.

What is your unit?

The following is a master of the obvious statement; building unit economics requires you to first pick the unit. I recommend picking a unit at which the company has its most significant level of marginal investment.

For example, for consumer focused businesses the best unit is typically as single customer. The investment at the customer level is customer acquisition cost (CAC) and for businesses that deliver a physical good, the cost to deliver the product. A customer-level unit also typically works well for enterprise focused businesses.

Some businesses require multiple unit measures. For example, an infrastructure service provider that has a geographically distributed physical infrastructure (data centers, cloud, wireless towers, etc.) have significant marginal capital investment for each new deployment. As a result, these businesses should use each unit of physical infrastructure as their core unit and within each, use a customer unit as a secondary unit.

Key unit economic model assumptions

Identifying the level of unit economics is the easy part. Getting the calculations right is a different matter. On the outflow side, the inputs are:

  • Capital Expenditures: The up front capital cost to create the unit. For an infrastructure style unit economic model, this would be the capital expenditures required to build the unit.
  • CAC: The initial, pre-revenue cost to acquire a customer. For a customer unit economic model, this is the fully loaded customer acquisition cost, including variable sales, marketing, and implementation costs that can be directly attributable to customer acquisition and on boarding.
  • Marginal Operating Costs: This is the ongoing marginal cost to serve the customer or to operate the infrastructure over the life of the unit.
  • Maintenance CapEx: Physical assets degrade over time. As a result, for an infrastructure business, it is important to factor maintenance CapEx into the unit economic model. This is the amount of CapEx required over time to keep the infrastructure operating at a suitable service delivery quality.

On the in-flow side, the inputs include:

  • Revenue: No need to explain, although I do advocate that companies put together a fairly detailed set of revenue drivers in their unit model; a topic for a different post.
  • Duration: When building a unit economic model, it is important to know the usable life of the unit. In an infrastructure model this is the useful life of the asset, factoring in the maintenance CapEx. In a customer unit model, this is the average customer life. Duration or Average Customer Life in a customer-driven unit model is the flip-side of churn-rate, where the relationship between the two is captured by the following equation:

1/churn rate = average customer lifetime

It is important to note that the average customer lifetime will be in whatever time period you use for your churn rate. Input a monthly churn and get a customer life in months. The churn rate required for this calculation is a customer count churn rate, as opposed to a revenue churn calculation. I could spend several posts solely on how to calculate churn.

  • Growth/Decline: You may believe that revenue per unit will increase or decease over time. This is critical to reflect in your unit model.

Each of the inputs require their own set of calculations. Setting aside the details, what we’re driving toward is a unit economic model that helps us perform some business model viability calculations.

Does your unit hunt?

Once I have the unit economic model inflows and outflows set, I like to lay them out in a time series, showing each inflow and outflow on its own line item. Sum them all up and you get to contribution margin. Contribution margin is the amount of cash that a unit contributes to covering corporate overhead expenses. I look at is the number of months it takes for the unit to produce a positive contribution margin and the number of months it takes for the unit to return whatever up-front investment that was required to produce it. The month in which a unit generates a cumulative positive contribution margin is the payback month.

With some additional math you can calculate the number of units that are required to bring the entire business to profitability. To do so, simply divide the company’s fixed overhead by the unit contribution margin. Finally, for capital-intensive businesses, particularly infrastructure businesses, it may be useful to calculate a return on investment for a unit.

Again, each of these calculations has its own set of detailed mechanics behind it. The point I want to make here is that you can’t begin to know whether your business economic engine works until you’ve built a unit economic model. If you are considering raising growth capital, start building your unit economic model today. You’ll be thankful you did the work when a prospective investor asks to see it. Any growth stage investor worthy of investing in your business will surely ask.

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