Since my post entitled SaaS Sales Compensation Made Easy, I’ve received a number of inquires about how to adjust SaaS sales commission percentages for very short and very long term subscription contracts, e.g., renewal periods of 1 month vs. 2 years. Clearly a 2 year contract paid in advance is worth more than a monthly renewal and should pay a higher commission. But, how much more?

In the model, I propose as best practice that SaaS sales commissions should be paid 100% up-front in proportion to the lifetime value of the sale (LTV). But to keep things simple, recurring revenue (ARR, QRR, or MRR) is substituted as the everyday measure of LTV, because LTV is always directly proportionate to recurring revenue. Basically, pay on recurring revenue in SaaS just like you would pay on price for any other product. It’s that simple….provided: 1) contract terms don’t vary widely and 2) the churn rate is uniform across customers (no churn cohorts).

However, adjusting your SaaS sales commission plan for these two factors isn’t complicated. You can do the LTV math in the background to produce a simple table of adjustments to the baseline SaaS sales commission for each contract term and/or churn cohort. Then, include this simple table of adjustments in your SaaS sales commission plan. The spreadsheet below does exactly this. (you can “Click to Edit” and play with the numbers or download to Excel. Go ZOHO!).

This enhanced SaaS sales commission model incorporates the effect of payment terms
and churn on lifetime value. The top table adjusts for contract term only,
whereas the bottom table allows for churn cohorts as well.

From the previous SaaS sales commission model post, we know that the lifetime value of a SaaS sale comprised of recurring subscription payments made in advance is given by the following formula:

i = cost of capital; a = churn rate

It is evident from this formula that if either contract term (i) or churn (a) vary across a wide range, then the calculation of the SaaS sales commission based on LTV should be adjusted accordingly (see LTV notes in the spreadsheet for the impact of contract term on i ). Put simply, if your contract terms (renewal periods) vary from monthly to every 2 years, you should consider adding a premium to the SaaS sales commission for 2 year contracts and a discount to the SaaS sales commission for monthly contracts. Or, if monthly customers cancel much more frequently than annual customers, say at a churn rate of 20% for monthly compared to a churn rate of 5% for annual, then you should again discount the SaaS sales commission paid on monthly contracts.

Using the formula above, the spreadsheet calculates a table with the commission percentage for each contract term and churn cohort. This table is created by taking the baseline commission percentage and multiplying it by the ratio of the LTV for each scenario to the baseline LTV. In the spreadsheet, an annual contract is used as the baseline.

To calculate the adjusted SaaS sales commission table that is right for your SaaS business, start by entering the target quota and target commission at quota to generate the baseline commission percentage. Then, you must select a cost of capital that reflects how much your SaaS business values cash up front. The more you value cash up front, the higher the number you put in for cost of capital. For a rapidly growing venture-funded startup, the cost of capital can be well in excess of 25%.

If your SaaS business experiences dramatically different cancellation rates by contract term, then you should adjust the churn rate for each contract term using the second table at the bottom. You can also use the spreadsheet to create adjusted SaaS sales commission tables for two different churn cohorts by entering one churn rate for the top table and a second churn rate that is the same for all contract terms in the bottom table.

It is also instructive to type in a value of 100% churn, implying that contracts are never renewed. In this case the SaaS sales comission payout is 1/12X, 1/4X, 1X, 2X, 3X for monthly, quarterly, annual, 2 year and 3 year contract terms respectively. This is the source of SaaS Sales Compensation Mistake #1 – Paying SaaS Sales Commission on Explicit Total Contract Value. Unless your churn rate is 100% or your cost of capital is infinite, you should not pay SaaS sales commissions based on total contract value. Over time, an automatically renewing annual contract will bring in exactly the same amount of money as a three year contract (provided the churn rate is the same). The only difference is the interest you can earn (or save) on the money up front, which is represented by the cost of capital.

I think it would be hard to overemphasize the importance of upgrades and upsells in SaaS product marketing. In an industry where free trials, freemium versions, bargain basement subscription prices and simply hoping to recover customer acquisition cost with first year revenue are the norm, few things are sweeter than a customer that actually wants to spend MORE money with you. Upgrades and upsells can lead to orders of magnitude difference in SaaS financial metrics. If you can acquire customers at $100/mo and rapidly upgrade them to $1,000/mo, then you may be able turn a profit in one year instead of ten years. And. if those $1,000/mo customers have a lifetime value of $100,000 instead of $10,000, then you may also turn a $50million SaaS company valuation into a $500million SaaS company valuation. ‘Nuff said.

Upgrade vs. Upsell in SaaS

Although the terms upsell and upgrade are often used interchangeable, I personally use them to distinguish between two very specific SaaS product marketing scenarios. For the purposes of this discussion, I will use the following definitions:

• Upgrade : Higher revenue from increased usage of current SaaS product capabilities.
• Upsell : Higher revenue from new SaaS product capabilities.

The reason for my distinction is that the buying dynamic is very different for the two scenarios. Upgrade potential of a SaaS product depends on the customer’s need to increase consumption of a known solution to a known problem, and deepens commitment to a particular capability. Whereas upsell potential of a SaaS product depends on the customer’s need to find new solutions to new problems, and widens your SaaS product footprint. This is not to say that upgrades and upsells are completely independent, because the need for increased usage can be highly correlated to the need for new capabilities as a growing customer’s business often entails greater volume as well as greater complexity.

Measure Value, Not Use

When SaaS product marketers think of upgrades and upsells, their minds immediately turn to pricing and packaging. Pricing and packaging are important, but you should always keep in mind that they are just a means to an end: purchase. The most important principle to follow in designing your SaaS product offering is to align pricing and packaging with customer value, or in B2B sales lingo “customer pain,” because the more a customer values a particular capability of your SaaS product, the more a customer will pay for it. In order to price what the market will bear, you must package your SaaS product into value bundles and price them using the measures that most closely correlate to customer value. You can use features, users, usage, performance, or any measure you like to price and package your SaaS product into bundles, but never forget that these measures serve as surrogates for customer value. A hundred bucks might buy you one feature or one hundred, but if that bundle of features doesn’t equate to value, your customers won’t pay it, or worse they might pay for it and still feel cheated or manipulated in the process.

Bundle Purchase Scenarios, Not Features

While customer value is the proper measure of your SaaS product bundles, it won’t tell you where to draw the pricing and packaging lines between your subscription plans. Some customers may place high value on pretty charts, while others may not value them all. The customer of a helpdesk SaaS product may value the first ten support rep users considerably more than the next fifty sales users. The first month’s use of a tax computation SaaS product may be significantly more valuable than use for the rest of the year. Competition may drive the margin for email features to zero, while unique social media capabilities may garner a premium.

The goal of any SaaS product pricing and packaging strategy is to maximize total profit by dividing it up into separate profit streams that add up to more than the profit of a single SaaS product offered at a single price. This is accomplished by segmenting the market into purchase scenarios of various customer groups and then further segmenting the stream of purchases of a single customer over time (upselling and upgrades!). More simply, you should bundle purchase scenarios, not features. OK, enough of the pricing 101. Let’s talk about how to drive upgrades and upsells.

Open The Front Door Wide

You can’t upgrade or upsell if you don’t have a customer, so it is critical to make it as easy as possible to adopt your SaaS product. Customer’s will come to you with varying degrees of sophistication and immediate need, so make sure you have an entry level offering that services the lowest, most common rung on the ladder. You may not wish to spend a lot of time and money on these customers in the beginning, especially if you have a freemium strategy. But, trial and purchase are merely the first steps to a long and profitable customer relationship when upgrades and upsells drive customer lifetime value well above that of the initial purchase.

Grow With Your Customers

If your customer only has ten salespeople, you will have a hard time upgrading your sales automation SaaS product to twenty users. If your customer has just launched it’s new website using your content management SaaS product, then advanced BI of usage statistics might be a tough sell. However, as your customer expands both its business and its understanding of your SaaS product, its need for greater usage and greater capability will expand as well. Therefore, you should map out the growth path your customer’s needs and align it with increasing SaaS product value. When your SaaS product value bundles and prices align with your customers’ growth trajectory, they will upgrade naturally, painlessly and frequently of their own accord, feeling that you have served them well and delivered what they need in return for a fair price.

Design For Discovery

Aligning value with need is a two way street. Your customer must have the need, but it must also see the value, and not necessarily in that order. You should design your SaaS product so that your customer naturally discovers and digests new capabilities just-in-time as its needs grow. Done well, this not only maximizes upgrades and upsells, it streamlines usability and simplifies adoption. There is nothing worse than being clobbered over the head with hundreds of features and options, when you only need and understand one. Or, being charged for stuff that you simply don’t need.

Track Penetration Against Potential

If you’ve done a good job segmenting your customers and their growth paths over time, then tying these standards back to actual data closes the loop and enables you to drive upgrades and upsells by personalizing your SaaS product experience, your marketing communications, and your sales interactions to the immediate needs of individual customers. Moreover, you can estimate potential customer lifetime value by type of customer and measure your upgrade and upsell penetration against it. One of the great advantages of SaaS is the ability to measure and understand in great detail exactly how your SaaS product is used, and then personalize the experience for the customer. Intelligent and considered application of customer profile and usage information can transform the discovery process from poking around a static user interface to an ongoing dialog between you and your customer. For example, the content management system above might automatically recommend checking out your BI module and offer a free trial once site traffic and back end reporting usage reaches a certain level. But, this can only be done if potential customer value is known and compared to the actual penetration in the form of customer use.

Enable Self-Service

This idea is an extension of SaaS Do #3 – Accelerate Organic Growth that claims that you should build your SaaS product such that customers can buy from you even if you don’t show up for work. If your customer has the need, and your upgrade offers the value, and your customer sees that value because you’ve pointed it out just-in-time, then you certainly don’t want your customer to fumble around because it can’t figure out how to buy it. Great self-service should allow your customer to see current subscription status and usage, evaluate the cost and terms of new capabilities, see what other customers have to say about them, try them out, buy them, and receive help getting them up and running.

Don’t Farm When You Should Hunt

Just because your customers can upgrade and upsell themselves even if you don’t show up for work doesn’t mean that you shouldn’t show up for work! When the gap between upgrade and upsell potential and penetration is limited by external customer constraints, you should farm. If you waste your time trying to sell customers stuff they don’t need in SaaS, all you will accomplish in the end is high acquisition costs, high churn and low profitability. On the other hand, when a significant value gap exists between potential and penetration simply due to a lack of understanding of either the need or the solution, you should hunt. For example, if you sell an event management system and your customer only has three events per year, your wasting your time trying to upgrade it from 5 events to 10 events. But, your customer might benefit from the social media add-on module if you can demonstrate the value. IMHO, this is the fundamental dividing line between hunting and farming. Hunting is not just for acquiring new customers. If an existing SaaS customer has a value gap that can be closed by an upgrade or upsell, then you should hunt it down and sell it. And, you should compensate sales reps for the incremental recurring revenue. If upgrades and upselling are constrained by your customer’s current state of growth such that no value gap exists, then you should farm a low churn rate by focusing on service. But, don’t farm when you should hunt, or you’ll miss out on the full potential of upgrades and upsells.

Recent weeks have brought a bewildering number of competing claims around SaaS and cloud computing. On one hand we are debating whether the SaaS experiment is over, IaaS is just an incremental advance in hosting technology, and the cloud is just hype. While on the other, Gartner estimates SaaS is now 10% of the enterprise market, Amazon AWS is a $500 million dollar business and Jim Cramer is picking his favorite cloud stocks. What’s a person to think? I for one think that recent reports of the cloud’s death are greatly exaggerated, and here is why…

The Cloud is Real. The Cloud is BIG.

It’s absolutely true to say that the cloud is simply the next evolution in computing, but saying it is an incremental change and isn’t all that different from traditional hosting or time sharing is like comparing the Internet to a T1 line. There are lot’s of new technologies and standards, big and small, that go into the cloud. And, there will continue to be others added as it matures. But, you shouldn’t allow the technology to cloud your thinking. The cloud, the REAL cloud, is about bringing any and all of the computing resources available on the Internet together to create Inter-networked applications and computing infrastructures. Consumer mash-ups perhaps being the simplest and earliest of these, but it isn’t that hard to imagine much bigger iron, mission-critical business applications running the same way. Most Internet innovation to date has focused on users and content, and has been strangled by a lack of bandwidth and integration standards. As these constraints erode, the cloud will continue to emerge. The cloud is about the machines. It is as big as all the computers connected to the Internet.

The Cloud is Hard

Security is and will remain the most difficult problem of SaaS and cloud computing, with reliability following close behind. But, this is more a matter of proliferating standards and best practice than technology. The problems are completely tractable. In the end, public standards and SLAs backed by SaaS, PaaS, and IaaS professionals working in their own areas of expertise will ultimately outperform all but the largest and most sophisticated internal IT departments. Most companies hire security firms to handle their physical security, why would they do any different with their IT infrastructure? Specialists do it better.

Cloud Adoption will be Gradual and Inexorable

The cloud is fundamentally an enterprise phenomenon, because it is about building applications and infrastructure. This is the business of businesses. And, like all things enterprise you can be sure of two growth characteristics. One, it will happen cautiously, slowly and gradually. Two, it will follow the money. The economics of the cloud are as simple as commodification, specialization and scale. Each year, more applications and infrastructure that have historically been hand-crafted on-premise by generalist IT departments becomes available online as specialized commodities. The movement from centralized generalist application deployment to distributed specialist application delivery is made possible by the Internet, and will continue to gain momentum as bandwidth and standards allow more sophisticated applications, data and computing power to be delivered over the public networks.

Cloud Fatigue is Unavoidable

So here we are. The cloud is real, the cloud is big, but the cloud is slooooowww. Salesforce.com has been preaching “no software” since 2000, and has taken a decade to build a billion dollar business, while consumer apps like FaceBook reach 500 million users in just a few years. It’s no wonder we’re tired of waiting already. All we are really seeing is that the cloud excitement is outstripping the pace of cloud adoption. And, this is likely to remain the case for the decade to come.

This week’s post is a throw down to see just how much cloud wisdom can be packed into a Twitter post of 140 characters or less. I did the best I could, but what have you got? Comment with yours and be sure to re-tweet your favorites to spread the words. I’ve coined a new tag #twisdomofclouds for Twitter tracking, so be sure to tack it on if you have room. Tweet on. JY

• Cloud skeptics think control is safety, but fear of flying doesn’t make you a pilot. #twisdomofclouds tweet it!
• A-SaaS-in enterprise software has a license to kill. #twisdomofclouds tweet it!
• Life is better on cloud 99.999%! #twisdomofclouds tweet it!
• High customer acquisition costs are a pain in the SaaS. #twisdomofclouds tweet it!
• Every cloud has an API binding. #twisdomofclouds tweet it!
• Value your SaaS customers and they’ll last a lifetime. #twisdomofclouds tweet it!
• GNU’s code-envy. Free is the cloud. #twisdomofclouds tweet it!
• Hybrid SaaS : A half-SaaSed attempt at on-demand. #twisdomofclouds tweet it!
• Fans hack Stones virtual tour on Azure private cloud. Jagger warns “Hey! You! Get off of my cloud.” #twisdomofclouds tweet it!
• DYJHIW DIY turns N2 WTF? DWBH CUZ SAAS EZ123 w/ OTH TCO!
  #twisdomofclouds tweet it!
• Don’t be CRUD on the cloud. #twisdomofclouds tweet it!
• Get your PaaS in gear and your thread in the clouds. #twisdomofclouds tweet it!
• Private cloud? Raise your hand if you own the Internet. #twisdomofclouds tweet it!
• SaaS for hire. Have software. Will travel. #twisdomofclouds tweet it!
• Need a Web service? There’s an OP for that. #twisdomofclouds tweet it!
• Without customers, SaaS is vaporware. #twisdomofclouds tweet it!
• You gotta go viral to stand out from the cloud. #twisdomofclouds tweet it!
• No room to tweet with all these dumb #AaaS acronym-as-a-service tags!
  #SaaS #PaaS #IaaS #DaaS #EaaS #twisdomofclouds tweet it!

To include the retweet link in your comment, just add the following hyperlink:

<a href=”http://twitter.com/home/?status=RT+your+twisdom+here
+%23twisdomofclouds+http%3A%2F%2Fbit.ly%2FabbcJu” > tweet it! </a>
Please tack on the #twisdomofclouds hash tag and hyperlink http://bit.ly/abbcJu back to the post if you don’t need all 140 characters, so folks can find your tweet on Twitter and their way back here to your comment.

It’s old news that the Internet has disrupted channel structure across numerous industries. So why go on about the channel now? Because, cloud computing is transforming the Internet as a channel. The evolution from Internet applications that service people (SaaS) to Internet applications that service other applications (cloud computing) transforms the Internet from a direct website channel to an indirect cloud channel and fundamentally alters the economics of the Web. This evolution has already transformed consumer advertising with the rise of syndication and social media, but the impact will not be limited to B2C communication channels. It will deepen and spread through online B2B channels with the rise of cloud computing and platform-as-a-service (PaaS).

In this post, I’ll provide some concrete examples of how the new cloud channel, or more specifically how cloud computing in the form of Web service APIs and PaaS, is driving a fresh wave of channel disruption that leaves new entrepreneurial opportunities in its wake.

Marketing Channels 101 – A Quick Review

Marketing channels accelerate revenue by streamlining the communications and logistics required to connect buyers and sellers. As such, disruptive improvements in channel cost, velocity and structure can transform industries. Basic channel functions can be categorized as follows:

• Promotion – Communicating the availability and value of a product or service
• Purchase – Facilitating and negotiating the actual sale of a product or service
• Distribution – Cost effectively transporting the product or service from seller to buyer
• Sorting & Packaging – Transforming a raw product or service into a more attractive one
• Risk – Shifting risk from buyers and sellers to channel vendors

Most channels provide more than one of these functions, and on the Internet it can be difficult to tell one from the other as content and applications are fluidly mixed and remixed as they cross the Web. In fact, it is the ability of cloud computing and PaaS to facilitate and accelerate this mixing process that is opening the new cloud channel. Instead of a single threaded link from buyer to seller through the browser, the cloud channel allows sellers to promote through, purchase through, distribute through, resort & repackage through, and shift risk through the network from application to application to application before reaching the final browser destination in front of the buyer.

Cloud Channel Disruption – Promotion

Communication, particularly advertising, is the mainstay of the consumer Web, and the impact of cloud computing on this channel can hardly be overstated. The most obvious example is the role of the RSS standard in transforming content distribution from a direct channel ruled by websites and portals to a cloud channel ruled by syndication and sharing. The combination of this standard data exchange format with Web service standards has created the penultimate “promote through” cloud channel as content is passed from blog to news site to friend to tweet and so on. It is the technical underpinnings of cloud computing as machine-to-machine interaction that enables the far reaching content syndication and person-to-person interactions of social media. Web service APIs create the conduit of the cloud channel, while the RSS standard makes the cloud channel indeterminate, organic and viral.

Cloud Channel Disruption – Purchase

Unlike blog posts and tweets, financial market data like real-time stock quotes is content of such high value that it still costs real money. In fact, according to Burton-Taylor the market for financial information and analysis is a $23 billion market. Unfortunately, market data is also incredibly difficult to buy. Mirroring the enterprise software model, market data is mostly purchased offline through third party data providers in the form of bulk, complex data feeds that require lots of on-premise data management software, hardware and professional services to parse, scrub, store and serve it to final applications and invariably force customers to buy and manage more market data than they actually consume.

Delivering market data over the Internet using standard Web service APIs, Xignite transforms the way market data is both bought and sold. Market data powers financial applications like electricity powers kitchen appliances. The Xignite market data cloud channel creates a power grid that connects the generators of market data: stock exchanges, trading networks, major brokers, etc., directly to financial applications using a Web service API as the standard socket. Immediate online access allows prospects to evaluate data fit and quality before they buy. Transparent, usage-based pricing facilitates online purchase. Web service delivery enables real-time sorting and packaging of the data to meet specific customer needs in a fashion unavailable to bulk data feeds, allowing customers to consume and purchase only the data they need. By simplifying and accelerating purchase, data providers like NASDAQ and CME Group can reach a wider global audience, including customers that can’t afford the time, effort and cost of buying a traditional data feed product.

Cloud Channel Disruption – Distribution

Application adoption and customer on-boarding is a primary challenge of every SaaS startup. While shuffling snippets of content around the Internet may satisfy the monetization needs of many a B2C Web business model, B2B SaaS companies need to move product to make money. Without APIs, the distribution channel of a SaaS application is limited to a single URL and adoption is constrained by the manual processes available from UI tools and professional services. For data-integration-intensive SaaS applications, such as BI and ERP, the adoption cost challenge seems almost insurmountable as highlighted IMHO by the failure of LucidEra and elusive profitability of NetSuite.

Frankly, I’d almost given up on these SaaS categories until I recently put the question to Roman Stanek, CEO of GoodData, and he coolly pointed out that the solution was right in front of my face: the cloud is the channel. The GoodData BI PaaS platform, puts APIs ahead of BI and cheats the adoption cost barrier outright by leveraging the cloud channel. While most SaaS BI startups sell direct, relying on low TCO and enterprise sales prowess to motivate customers over high adoption costs, GoodData plans to drive distribution through the cloud channel with a ground-up PaaS architecture, canned integration to major SaaS applications, cloud solution partners and strong support of its developer network. The SaaS BI space is crowded, competitive and unpredictable, but pure-play PaaS is the strongest and most disruptive strategy I’ve seen to date, because it focuses like a laser on eliminating the biggest obstacle to SaaS BI adoption, data integration.

Cloud Channel Disruption – Sorting and Packaging

If you use Twitter, chances are you don’t really use Twitter.com, because seventy-five percent of Twitter traffic flows through its APIs. That means that most people are using Twitter just about everywhere else, like their mobile phones, Facebook, LinkedIn, TweetDeck, and Seesmic just to name a few. Twitter is not a micro-blogging website; Twitter is a micro-blogging PaaS. Individual tweets are just not all that interesting, but when you mash them up with friends, colleagues, interest groups, search, and related Web content, they become a conversation. Had Twitter taken on a portal strategy common to social networks like Facebook, chances are it would have failed miserably. By allowing developers to easily repackage Twitter to meet the divergent needs of a myriad of market segments, Twitter leverages the cloud channel to drive adoption and use, while remaining focused on the core value of it’s service.

Cloud Channel Disruption – Risk

A common objection is that the cloud is just too risky. This despite the fact that only the largest IT organizations can come close to internally matching the dedicated expertise, SLAs and security of established SaaS and cloud companies. However, it is important to remember that the role of the channel is to absorb risk not shirk it, particularly inventory risk. On the cloud channel, inventory is measured in IT workloads, and the more unpredictable the workload, the higher the risk of managing it in-house, and the greater the value in shifting it to the cloud. I especially like this slide that the Windows Azure folks put together to illuminate this concept.

The cloud channel absorbs the risk of fluctuating IT workloads through shared infrastructure just like a wholesaler absorbs the inventory risk of fluctuating demand for physical goods.

As the cloud channel matures, I believe it will become more effective at absorbing risk of all kinds. While there are certainly applications where privacy, security and compliance concerns may permanently preclude moving them to the cloud, the vast majority of applications will succumb as the technology advances. Ten years ago, many businesses would have balked at putting their customer databases on the cloud. Now it is a common practice that Salesforce.com has turned into a billion dollar business.

The most common fallacy of the cloud channel is the illusion that control reduces risk, when in reality it is simply a reaction to fear. But, fear of flying doesn’t make you a pilot, and you probably aren’t safer flying the plane yourself.

I’ll say it again: SaaS is NOT cloud computing. As the industry rushes to embrace cloud computing, too many SaaS experts and vendors are simply updating their marketing messages with cloud buzzwords. This is not enough.

When I started this blog, the biggest challenge faced by SaaS vendors was getting our heads around the new lightweight paradigm for marketing and selling an on-demand Web application versus the heavy-handed direct sales approach of traditional enterprise software.

Today, a new challenge is arising. However, this time the threat comes not from the past, but from the future. Just as SaaS vendors have found their Internet footing, cloud computing is destabilizing the very ground beneath our feet. Depending on your SaaS business, cloud computing could impact everything from application architecture to channel strategy. Or, it may not affect you at all. Either way you should know. What is your cloud computing IQ?

The Cloud is the Computer

John Gage’s prophetic remark “The Network is the Computer” beautifully highlights the difference between SaaS and cloud computing. While SaaS applications provide on-demand services to millions of users across the Internet, cloud applications provide on-demand services to millions of other applications across the Internet. The network really is the computer.

Why should this matter to SaaS experts and vendors? Two reasons. First, because most SaaS applications today exist as silos that only solve a piece of a customer’s puzzle. Second, because cloud computing enables new economies of scale through shared infrastructure that properly designed SaaS applications can leverage to further drive down total cost of service.

SaaS Model Economics 101 states that SaaS competitive advantage comes in two Internet-enabled flavors: network-based differentiation and lower cost from economies of scale. Cloud computing creates new opportunities for SaaS vendors to extend their competitive advantage by opening their applications to the cloud through Web services and further driving down costs by running on shared cloud infrastructure.

SaaS Silos vs. Cloud Platforms

SaaS Do #9 – Open Up to The Cloud encourages SaaS vendors to reach out to complementary applications on the Web through open, standards-based APIs. But opening up to the cloud is not just about easy integration. Comprehensive Web service access will transform your SaaS application into a cloud computing platform. Virtually everyone today knows about Facebook. But, what not everyone in the SaaS community knows is that the fundamental reason Facebook kicked the crap out of Myspace and all the other wannabees vying for social network dominance was the introduction of the Facebook platform that allowed independent developers to create Facebook applications. Platform-as-a-service (Paas) opportunities are not limited to pure play PaaS companies making cloud development and deployment toolkits, PaaS opportunities are open to every SaaS vendor that thinks beyond the browser and is willing to expand its definition of “user” to include not only people, but other applications as well.

Have SaaS, Will Travel

It’s hard to believe, but we already have a “traditional model” for SaaS application architecture based on database multi-tenancy and a vertically integrated delivery infrastructure. This architectural model is the foundation of the SaaS cost advantage. However, it originated in a pre-cloud computing world based on the pre-cloud computing assumption that the SaaS application would run on a static host infrastructure.

To fully realize the cost advantages available on the Internet, the next generation of SaaS applications will not only be multi-tenant, but will be multiple tenants in their own right on shared cloud infrastructure. Monolithlic, vertically integrated SaaS applications will be broken up into loosely coupled, multi-layered Web service components that can be dynamically deployed to multiple cloud platforms in order to meet production requirements. This trend is so visible to the VC community, that the folks at Bessemer promoted it to the #1 spot of their recently revised 10 Laws of Cloud Computing and SaaS.

Blooming Channels

The inadequate grasp of cloud computing in the SaaS community was highlighted for me by some of the reactions of my fellow SaaS evangelists to this recent post of the emerging PaaS channel opportunity. As if the emergence of the PaaS channel somehow devalues the “pure” SaaS channel. This is not the case. There are fewer “pure” SaaS channel partners simply because SaaS vendors are doing a good job of making their applications easy for people to deploy and use. This is a good thing!

The fact that there are fewer “pure” SaaS channel partners does not in any way discount their value. SaaS channel partners have naturally gravitated to very high value services such as business strategy, process design, requirements definition, vendor selection, and training. However, from the SaaS vendor’s perspective these types of channel partners are gatekeepers. They don’t move product. And, anyone who has spent any amount of time in consulting will tell you that while a strategy project may net you $100K in services revenue, a development project can net you $1M. So, I’ll say it again. Cloud channels will follow the money.

This is not to say that we’re going back in time with the PaaS channel reliving the custom development glory days of enterprise software VARs. PaaS channel partners will be leading the charge into a new paradigm of cloud-based application development, sewing SaaS applications and Web services together into flexible mash-up cloud applications and application suites that are dynamically deployed across the Internet. The retooling required of traditional software VARs to deliver these services is no less daunting than the shift required of enterprise software companies to deliver SaaS. (How long did it take SAP and Oracle to get with the program?)

SaaS vendors with high cloud computing IQs recognize the cloud as the new channel. They will transform their applications into cloud computing platforms and will see their PaaS channel opportunities bloom. Whereas today’s “pure” SaaS channel opportunities are largely limited to marketing referrals from trusted advisers and affiliates, tomorrows PaaS channel partners will redistribute SaaS applications over the cloud as components, complements and containers of other applications. They will extend both the market reach and product capabilities of SaaS vendors that embrace PaaS the same way they have already done this for Salesforce, Facebook, Google and Twitter. The network is the channel.

SaaS channel partners have definitely received the short end of the stick compared to their software channel counterparts. With a few notable exceptions like Salesforce.com, Netsuite (and largest, but least recognized as SaaS, Google AdWords) there simply have not been enough customers or enough work to engender a thriving ecosystem of SaaS channel partners, at least not when compared to the sprawling extent of enterprise software channels. I think this is about to change.

Channels Always Follow the Money

There is one universal law that governs all channel management: CHANNEL PARTNERS MUST MAKE MONEY. The biggest channel mistake made by many a SaaS start-up CEO is to fall into the fantasy that SaaS channel partners are there to help your business. They are not. They are there to help themselves. And, how much money they can make boils down to a very simple formula.

SaaS channel money = SaaS channel value-add x SaaS application customers

And right here is the rub. The self-serviceability of many SaaS applications from customer acquisition through deployment significantly reduces the value-add for SaaS channel partners. In fact, if all SaaS vendors embraced SaaS Top Ten Do #3 – Accelerate Organic Growth, then the SaaS channel situation might be even more dire. Moreover, the number of SaaS applications with enough customers to drive SaaS channel development can be counted on your fingers and toes.

Unfinished Business is the Business of Channels

The work required to realize the benefit of your product is the same whether you do it, your customer does it, or a channel partner does it. Channel partners add value by finishing the unfinished work that you and your customer start, but for business reasons can’t complete. They simplify and speed adoption by shouldering tasks that they can do better, cheaper and faster. The greater the gap between your service and your customers’ ultimate needs, the greater the value delivered by the SaaS channel partner and the greater the SaaS channel opportunity.

SaaS Total Cost of Service – Visualizing the SaaS Channel Slice of the Pie

I like to visualize this as the cloud channel partner’s contribution to total cost of service (TCS), because the success of your cloud channel strategy will always hinge on a) your cloud channel partners’ ability to make money and b) your customers ability to realize value that exceeds total cost of service, including the money made by your cloud channel partner.

Developing in the Cloud: The Emerging PaaS Channel Opportunity

The problem with SaaS channels to date is that there simply has not been enough for them to do. I think this is about to change, but I also think it will happen one layer down in the cloud technology stack. If you examine the raison d’etre for the vast array of enterprise software channels it comes down to the fact that enterprise software is delivered in an unfinished state, leaving plenty for enterprise software channel partners to do and lots of it requiring very specialized technical knowledge with which customers simply don’t want to bother.

These attributes are also present in the emerging platform-as-a-service space (PaaS). Whether it is building, deploying and managing a new application on Amazon AWS or simply extending and integrating existing SaaS applications using the ever expanding pool of Web services APIs, the number of opportunities for pure cloud-based development is increasing and is sure to grow to a scale that rivals enterprise software. Unlike SaaS applications that are designed with the business user in mind, PaaS and IaaS offerings are designed for developers. They are by their very nature brimming with potential value, unfinished and highly technical–making them ripe for channels.

Whereas SaaS providers have struggled to develop the interest of potential SaaS channel partners, IaaS, PaaS, and PaaS tool vendors are likely to find their businesses increasingly dependent on cloud channel partners focused on pure-cloud application development and deployment. Moreover, you can expect these cloud channels to spark a proliferation of home-grown development, deployment and monitoring tools that will ignite and accelerate the already hot PaaS tools sector as cloud channel partners product-ize their home-grown systems and take them to market.

So, if you are an enterprise software channel partner and have been scratching your head for the last few years trying to figure out how to jump on the cloud channel bandwagon, then think PaaS channel not SaaS channel. And, get started already or you may miss the boat.

The annual SaaS Summit is next week in San Francisco, so if you are going and would like to meet up, send me a note at joelyork [at] chaotic-flow.com. The program is All About the Cloud and while I’m a little bummed there isn’t more SaaS-specific content, you gotta roll with the times and this year is definitely all about the cloud.

This year the SIIA has stepped up to the plate
and is clearly taking the SaaS Summit to the next level.

I’m particularly looking forward to the Public Cloud vs. Private Cloud debate to be queued up by Phil Wainewright and Jeff Kaplan and will likely weigh in with my own view afterward. I expect this debate will not go away anytime soon and we’ll see a proliferation of private cloud software vendors and services, but in the end there is no escaping the reality that private clouds are to public clouds as your intranet is to the Internet. Big difference.

You can also follow the conference chatter on Twitter under the tag #aatc

This may sound like evangelical cloud mumbo jumbo, but I’m actually alluding to the central importance of the ongoing customer relationship in the SaaS business model and its direct linkage to the financial success of a SaaS business. In the SaaS business model, the ongoing customer relationship is a continuous source of revenue, cost, business activity and risk. This contrasts sharply with traditional software where the short-term sales transaction has always taken center stage.

A traditional software vendor makes and sells perpetual license copies, whereas a SaaS business makes and sells ongoing service subscriptions. Each new SaaS customer brings a new thread of recurring revenue and cost which are woven into the larger tapestry of customers to create the total SaaS recurring revenue stream and associated SaaS cost of service. This fundamental shift in the unit of value from copies to customers turns the economics of licensed software upside down, and is still an elusive financial concept for the industry when evaluating SaaS costs, profitability, business valuation and capital efficiency.

Customers vs. Copies

In traditional licensed software, value is equated to the intellectual property of the code, and is monetized using copyrights in a fashion similar to books, music, and movies. Volume is measured in licensed copies and value is measured by the price of a license. But in the SaaS business model, volume is measured by the number of customer subscriptions and value is measured by recurring revenue. A software vendor invests in developing code, and then operates a sales and marketing infrastructure that scales to sell more licensed copies. A SaaS business invests in acquiring customers, and then operates a service delivery operation that scales to service customer subscriptions. Mathematically….

software profit = ( license price – transaction cost ) x copies – R&D costs

SaaS profit = ( recurring revenue – recurring service cost ) x customers – acquisition cost

Operational costs that are fixed relative to the number of license copies sold in the software business model are now variable relative to the total number of customers in the SaaS business model, such as product development which in SaaS becomes part of the recurring service cost and extends far beyond the initial source code investment to the entire business infrastructure (see note below: Breaking Down Total SaaS Cost of Service and SaaS Do #5 – Build the Business into the Product). Alternatively, sales and marketing costs that are variable relative to the number of license transactions in the software business model are suddenly fixed customer acquisition costs relative to the total number of customers in the SaaS business model, variable instead with the number of new customers.

Happy Customers Drive SaaS Business Model ROI

Capital efficiency is about achieving the highest possible return on investment (ROI). High ROI in turn is achieved by minimizing the up front fixed costs of a business and then maximizing margin by scaling revenue well in excess of variable costs. Like putting a down payment on a rental property, and then making sure the the rental income covers the operating expenses and interest payments. In the license software model, capital efficiency is measured by product ROI, but in the SaaS business model the best measure of capital efficiency is customer ROI, or the average customer rate of return (aka Joel’s SaaS Magic Number).

Where “ARR” is the average recurring revenue per customer, “ACS” is the average recurring cost of service per customer, and “CAC” is the average customer acquisition cost. Software ROI is achieved by selling more copies to cover your R&D investment. SaaS ROI is achieved by acquiring more customers and maximizing customer lifetime value through upselling and retention to cover your customer acquisition cost.

In the end, it all has to add up to happy customers. Service subscriptions are perishable. They can’t be copied and stored like a book or a movie or a software CD. A SaaS business without customers simply doesn’t exist—like the sound of a tree falling in the woods with no one around to hear it. In the SaaS business model, the customer really is king.

From time to time, I come across what IMHO are really fantastic and enlightening blog posts and SaaS best practice guides that truly stand out above the rest….by authors other than Chaotic Flow . To me the value of these gems is immeasurable, because I generally have to read through a lot of crap to get to them. It’s a big Internet.

In the hope of adding more value than I alone can muster for my loyal Chaotic Flow readers and in the spirit of supporting the authors of these high quality gems by spreading their words to my small corner of the SaaS and cloud computing business community, I’m launching a new SaaS best practices community blog companion to Chaotic Flow dubbed Open Current (cute right?).

Open Current is an open repository of SaaS best practice insights and tools for executives charged with building SaaS and Cloud Computing businesses…moderated by yours truly, so ONLY THE BEST will be make it through the rigorous evaluation process (basically, I have to read it and think it’s earth-shatteringly good…but, please don’t let that deter you….help wanted, submit your favorite SaaS and cloud related posts!)

ANYONE CAN POST to Open Current and I need your help! Please comment on this post, email info[at]open-current.com, or directly submit your favorite SaaS and Cloud Computing blog posts, SaaS best practice guides, and industry research and reports for inclusion.

For the life of me, I still can’t fathom how VCs value early stage startups. I think it is one part business logic and five parts voodoo (no offense to my VC friends, but you know what I mean). However, I’m guessing most SaaS-focused VCs know this SaaS company valuation principle in their gut even if they can’t reduce it to a financial projection: SaaS Customer Lifetime Value Drives SaaS Company Value. For what is a company if not the sum of its customers?

This is the final post in a series that aims to uncover the mysteries of SaaS financial metrics from a new angle, a little mathematics. In this installment, I’ll explore the important SaaS metric of customer lifetime value (CLTV) and introduce a new SaaS financial metrics rule-of-thumb that relates SaaS CLTV to SaaS company value.

Buyer Beware: The ideas presented in this installment of the SaaS metrics series are not meant to offer methods or models for evaluating the value of any particular SaaS company, but rather to offer credence to the gut reaction above. Use the formulas herein at your own discretion. Chaotic Flow, i.e., me, accepts no liability thereof.

SaaS Metrics Rule-of-Thumb #10
SaaS Customer Lifetime Value Drives SaaS Company Value

The financially accepted method for estimating the value of company is the calculation of the discounted value of its future cash flows, or net present value. Now, I’m not saying that anyone in InternetWorld actually uses this method, but for the sake of this series on SaaS financial metrics, this is the only approach that lends itself to mathematical analysis. So, I am stuck with it.

The exact mathematical statement of SaaS Metric Rule-of-Thumb #10 above is expressed as follows (see SaaS Metrics Math Notes below for the derivation):

SaaS Company NPV = CLTV x NEW_LTV

Where CLTV is the average SaaS customer lifetime value and NEW_LTV is an analogous measure for the lifetime value number of customers that represents the discounted number of new customers acquired by our SaaS company during its lifetime, using the standard NPV formula.

NEW_LTV = NEW₁/( 1 + i ) + NEW₂/( 1 + i )² +…+ NEW_N/( 1 + i )^N

Here NEW_n is the number of new customers acquired during the period n. NEW_LTV is the present value of all the new customers that the company will ever acquire discounted by how long it takes to acquire them. If market penetration is slow, then NEW_LTV might be less than 10% of the total number of customers at maturity. Whereas, if market penetration is fast and absolute, then NEW_LTV will be closer to the total number of potential customers.

The formula above elegantly encompasses three critical questions asked by SaaS VCs:

• What is the value to the customer? (CLTV)
• How big is the market? (NEW_N)
• How fast can you get there? (NEW_LTV)

The link between SaaS CLTV and SaaS company valuation arises naturally from the SaaS subscription model where topline company revenue emerges as the sum of individual customer revenue streams. In this regard, this new SaaS metrics rule-of-thumb linking customer value to company value is really a corollary of SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even, which had I been more esoteric (as if this SaaS metrics series isn’t already esoteric enough!), I might have stated as SaaS company cash flow follows SaaS customer cash flow (most SaaS CEOs can validate this version of the principle without any need for advanced mathematics).

While CLTV can be calculated for each individual customer, it is more commonly quoted as a generalized metric that describes the average SaaS customer as follows:

CLTV = ARR_LTV – ACS_LTV – CAC

CLTV = (ARR₁ – ACS₁)/( 1 + i ) + (ARR₂ – ACS₂)/( 1 + i )² +…+ (ARR_N – ACS_N)/( 1 + i )^N – CAC

Where “ARR_LTV” is average lifetime recurring revenue per customer, “ACS_LTV” is the average lifetime recurring cost of service per customer, and “CAC” is the average customer acquisition cost. ARR_n and ACS_n are the average customer recurring revenue and cost of service for the period n, and “i” is the cost of capital, which for VC funded startups is 30%+.

I’ve explicitly separated revenue from costs, because costs are variously omitted from CLTV depending on the application. For example, if I want to compare the “lifetime value” of a customer in terms of net contribution vs. the cost of acquiring a customer, then I omit the acquisition cost from the CLTV calculation. Or, if I wan’t to measure the “lifetime value” as the money a customer pays during its lifetime, then I’d only keep ARR_LTV. The formula as written is the total net present value of all cash flows related to acquiring and servicing the average SaaS customer.

Using this “fully loaded” CLTV, we can also give a useful variation to the formula for total SaaS company value when the company already has current customers, C_old, as follows:

NPV = CLTV x NEW_LTV + ( CLTV + CAC ) x C_old

or

NPV = CLTV x NEW_LTV + ( ARR_LTV – ACS_LTV ) x C_old

Where in this case NEW_LTV represents all the future customers still yet to be acquired and C_old represents the number of current customers. Notice that using our “fully loaded” CLTV we must add CAC back for current customers, because it is a sunk cost. If new customers are somehow different from old customers, or CLTV changes over the customer lifetime, then the old customer CLTV / CAC values would also be different from the new.

In the simple case of constant recurring payments and costs per period, CLTV for the average customer is calculated as follows:

CLTV = (ARR – ACS)/( 1 + i ) + (ARR – ACS)/( 1 + i )² +…+ (ARR – ACS)/( 1 + i )^N – CAC

CLTV = ( ARR – ACS )/i x ( 1 – ( 1 + i )^-N ) – CAC

When there is no limit placed on the number of payments (an annuity).

CLTV = (ARR – ACS )/i – CAC

And, if we throw churn and viral growth into the mix CLTV becomes.

CLTV = ( ARR – ACS – gCAC )/( i + a – g ) – CAC

with the constraint g < i + a

Where “ARR” is the average recurring revenue per customer, “ACS” is the average recurring cost of service per customer, “a” is percentage churn rate, “g” is the viral growth rate. This last formula should be used with extreme caution in high growth, big g scenarios as treating viral growth as something that extends indefinitely is unrealistic. Sooner or later you hit the market limit and growth slows. Which is why the formula blows up when g = i + a.

Check out the rest of the SaaS Metrics Rules-of-Thumb

• SaaS Metrics Rule-of-Thumb #1 – SaaS Churn Kills SaaS Company Growth
• SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn
• SaaS Metrics Rule-of-Thumb #3 – Viral Growth Trumps SaaS Churn
• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even
• SaaS Metrics Rule-of-Thumb #6 – Growth Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #7 – Churn Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #8 – Upselling and Upgrades Accelerate SaaS Profitability
• SaaS Metrics Rule-of-Thumb #9 – Joel’s SaaS Magic Number
• SaaS Metrics Rule-of-Thumb #10 – SaaS Customer Lifetime Value Drives SaaS Company Value

I just have to say it. SaaS sales compensation is not nearly as complex and mysterious as it has been made out to be. I’ve read so many discussions on SaaS sales compensation that claim you should do this in one case and that in another case, such that by the time you finish you can’t see the forest for the trees. Since I’m in the middle of this series on SaaS metrics, it seems high time I got around to addressing this topic (which I’ve been avoiding simply because I did not want to plant yet another tree).
So, here is the scoop….

Wait! Relax. Although at first glance, lifetime value may appear to be an overly complex metric to use for sales compensation, it is always proportionate to recurring revenue. So, you simply have to replace “price” with MRR or QRR or ARR in your favorite sales compensation model and you are fine. That’s it! Now you can apply any of the various sales compensation models that you already know and love. Your particular choice should match the specific goals, products, pricing and culture of your specific business, as with any other sales compensation design challenge.

The primary principle of sales compensation is to pay the sales rep in proportion to the value of the deal, usually measured by the price of the product. The value of the deal in turn is wrapped up in the sales commission percentage, which is calculated by dividing the target commission at quota by the sales rep quota:

commission % = target commission at quota / quota

The quota in turn is determined by what is achievable for such a sales rep in terms of number of deals and the average deal value.

quota = target # of deals x average deal value

And, the actual sales compensation is calculated by multiplying the commission percentage by the actual sales.

sales compensation = commission % x actual sales

The target commission is determined by the labor market rate for the type of sales rep you need to fulfill the sales role. This is important, because it is at this point in the sales compensation plan design that we clearly see that sales compensation is NOT about paying the sales rep a percentage of revenue, it is about allocating a target commission payout based on a measure of performance (quota). The measure we use for performance (license revenue, recurring revenue, margin, etc.) is completely arbitrary. We consciously choose a measure that scales with deal value, so that sales compensation aligns sales rep performance with company performance.

You can get really fancy with tiers, spiffs, margin vs. revenue, etc., but these basic formulas are the cornerstone of any sales compensation plan, and this does not change for SaaS. What does change is how you measure deal value, and thus the relevant measure of sales performance.

In a subscription business with a recurring revenue stream, the value of the deal is not as clear cut as the price of a software license. As any MBA or bond trader will gladly tell you, the true value of a subscription deal is the present value of the future cash flows, which amounts to summing up all the recurring revenue over time, taking into account churn, and discounting it by your cost of capital. For a simple subscription with constant recurring revenue, “RR”, this is given by the following formula:

SaaS Subscription LTV = RR + RR (1 – a)/(1 + i) + RR [(1 - a)/(1 + i)]^2 … RR [(1 - a)/(1 + i)]^N

SaaS Subscription LTV = RR ( 1 + i ) / ( i + a )

Where “i” (for interest) is the cost of capital and “a” (for attrition) is the churn rate, and N is the number of payments made over the customer’s lifetime. If the customer follows the normal churn rate, the top LTV formula simplifies to the bottom LTV formula. Again, the MBA’s in the audience will recognize this as the formula for the present value of an annuity.

I say again….do not fear! As previously mentioned, the LTV of the deal is always proportionate to recurring revenue of the deal. The salient word here being “proportionate.” When it comes to designing our SaaS sales compensation plan, we can use ANY measure of recurring revenue (MRR, QRR, ARR) that is proportionate to lifetime deal value. We do not need to calculate the absolute LTV for the deal, because the commission percentage will scale up or down as needed to make sure we payout the target sales compensation. Thus for SaaS, we simply change the calculation to the following:

SaaS commission % = target commission at quota / quota in recurring revenue

SaaS quota = target # of deals x average deal value in recurring revenue

SaaS sales compensation = commission % x actual sales in recurring revenue

Recurring revenue can be measured monthly, quarterly, or annually, because the sales commission percentage scales accordingly. But, once a time-frame for recurring revenue is chosen for calculating the sales commission percentage, it is critical to stick with the same recurring revenue time-frame throughout your SaaS sales compensation plan, i.e., if you calculate average deal value and quota in ARR, then you must measure actual sales in ARR as well to get the correct actual sales commission payout.

Failing to stick with the same recurring revenue time-frame throughout creates an expensive bait-and-switch problem that is the root cause of SaaS Sales Compensation Mistakes 1 & 2 below. Psychologically it is often best to base your SaaS sales compensation plan on a recurring revenue time-frame (monthly, quarterly, or annually) that equals your most common contract renewal term, e.g., if you mostly sign annual renewal contracts, then base your sales compensation plan on ARR, if most renewal contracts are monthly, then use MRR.

To recap…replace unit price with MRR/QRR/ARR…done.

The picture above shows a quick visualization for two sales compensation plans for two sales reps with similar skill sets and market labor rates: one at a software company, and another at a SaaS company. In both cases, the sales rep has a base salary of $50K. On the left, the goal is to motivate the software sales rep to bring in $2M in license revenue. The software sales compensation plan has an accelerator such that payout is $100K at $1.5M and $150K at $2M, and unlimited upside if the sales rep can blow it out of the water.

On the right is a SaaS sales compensation plan where the goal is to motivate the SaaS sales rep to bring in $1M in annual recurring revenue. The plans are IDENTICAL except for the scale of the performance measure on the x-axis (swapping license price with ARR). The SaaS sales compensation plan has a base pay of $50K and an accelerator such that the payout is $100K at $750K ARR and $150K at $1M ARR, and again with unlimited upside to motivate your top sales performers. If we want to recast the SaaS sales compensation plan from ARR to MRR or QRR, we simply change the scale of the x-axis by calculating average deal value, target quota and actual sales in MRR or QRR, 1/12 or 1/4 of ARR respectively.

OK. Visual, but maybe not so easy. Below is a simple numerical example that walks you through the calculation.

How much easier could it be? Well…here are some very common mistakes to avoid.

SaaS Sales Compensation Mistake #1
Paying SaaS sales compensation on explicit total contract value

Happy customers renew their contracts. Unhappy customers don’t. Unhappy customers cancel early, and ask for refunds. If your customers are happy, then the primary benefit of a long term contract is up-front cash payment, not lock-in. Happiness = Lock in. Your SaaS sales compensation plan should reflect this reality. Consider a service that costs $100/month. A monthly renewal contract appears to be worth $100, while a 1 yr renewal contract appears to be worth $1200, and a 2 yr renewal contract appears to be worth $2400. In reality, all three contracts have the same recurring revenue ($100 MRR or $1200 ARR), and should therefore pay the same baseline commission. This is the essence of Bessemer Law for being SaaS-y #1, which states that “bookings are for suckers.”

Longer term contracts are worth more, but the difference in value is your cost of capital which is typically in the 5-30% range depending on your source of funding. The financially sound SaaS sales compensation approach is to pay a baseline commission on the recurring revenue of the deal, then provide an accelerated payment incentive for longer contracts in the 5-30% range that reflects your own cost of capital. (See the numerical example above for a more detailed explanation). If you base your SaaS sales compensation plan on ARR, then sign a 2 yr contract and foolishly plug the explicit contract value of $2400 into your SaaS sales compensation payout formula because the deal FEELS like it is worth $2400, then you are paying as if the deal was worth twice as much. It isn’t.

SaaS Sales Compensation Mistake #2
Trying to manage cashflow through your SaaS sales compensation plan

This is the reverse bait-and-switch of SaaS Sales Compensation Mistake #1 above, arising when you sign contracts with short subscription terms, e.g., monthly. In this case, there is a tendency to not what to pay out sales compensation in advance of receiving payment. Tough! It isn’t the sales rep’s job to manage cash flow. It’s the sales rep’s job to bring in the deal. If your customers are happy, then a monthly payment plan is just as valuable as an annual plan, minus a small percentage for the time value of the money. The best approach is to pay the sales rep in-full, up-front based on the recurring revenue, then tack on a 5-30% penalty for short term contracts as described in SaaS Sales Compensation Mistake #1 above.

If you are one of those lucky SaaS companies that has high early churn and then things settle down, you might want to break the payment up into two, e.g., 50% now and 50% when things settle down. But, you should NOT leave the sales rep waiting and waiting to get paid over time in an attempt to match cash flow to sales compensation. If your churn rate is very very high, say 50%, then you might ask yourself if you are in a recurring revenue business in the first place and simply revert back to paying on actual contract value.

SaaS Sales Compensation Mistake #3
Not including fully loaded sales compensation in customer acquisition cost

Customer acquisition cost should include all the labor it takes to get a new customer signed, not just out of pocket sales and marketing costs. Generally, adding up all sales and marketing expenses is the best way to calculate your customer acquisition cost. This way you don’t miss anything. When you do this, you will almost certainly find that fully loaded sales compensation costs are a dominant contributor to total customer acquisition cost. As indicated in the SaaS metrics series, controlling acquisition costs is a critical factor in reaching profitability. Therefore, it is important to set a target for the ratio of fully loaded annual sales compensation to new annual recurring revenue that gives a sales contribution sufficient to support overall business profitability (i.e., sales contribution = 1 – sales expense ratio).

SaaS Sales Compensation Mistake #4
Not scaling sales compensation with sales productivity

Some good benchmarks to plug into the commission formula above are $100K in total sales compensation for $1M ARR. On a 50:50 split, this gives a commission percentage of 5%. But, what if you are a start-up and a quota of $1M ARR is just plain unachievable? For example, if your current average deal size is $1000, your sales rep would need to close 1000 deals/year! In this case, you might need to pay 20% on a quota of $250K ARR just to get your business off the ground. However, a sales contribution of 60% is unlikely to be profitable in the long run, because you are paying $100K in sales compensation for a measly $250K ARR (i.e., 60% = 1 – 100K/250K). In this scenario, you should work hard to increase both your average deal value and your achievable quota. As you grow, it is important to scale your commission percentage in lockstep with your increasing achievable quota, otherwise you will get locked into a low sales contribution percentage that will sink your long term profitability.

One of the mysteries I hoped to solve when I embarked upon this little SaaS metrics mathematical journey was the reality behind “The SaaS Company Magic Number” introduced by then Omniture CEO, Josh James, and immemorialized by my pal Lars Leckie over at Hummer Winblad. In principal, this number tells you how aggressively you should be spending to build up your customer base: “the key insight is that if you are below 0.75 then step back and look at your business, if you are above 0.75 then start pouring on the gas for growth because your business is primed to leverage spend into growth. If you are anywhere above 1.5 call me immediately.”-Lars Leckie’s Blog

In this installment of the SaaS metrics series, I will show why this benchmark works, and introduce what IMHO is the single most important SaaS financial metric for measuring the overall health of a SaaS business. Now, being as Josh and Lars have already laid claim to “The” SaaS Magic Number, I really have no alternative but to put all humility aside and dub my latecomer SaaS metric as “Joel’s” SaaS Magic Number (After all, I did similarly snag “The” Top Ten Do’s and Don’ts of SaaS, so it’s all good.)

SaaS Metrics Rule of Thumb #9 – Joel’s SaaS Magic Number

The truth be told I feel a bit guilty about the name, because Joel’s SaaS Magic Number is neither magic, nor mine really. It’s simply the the average customer rate of return, or rather the inverse of the average customer baseline break-even, 1/BE₀, that has so consistently popped up as a driver and a constraint in the SaaS metrics rules-of-thumb.

Where “ARR” is the average recurring revenue per customer, “ACS” is the average recurring cost of service per customer, and “CAC” is the average customer acquisition cost. Customer rate of return is powerful, because it measures the economics that make a SaaS business work (or not), whereas the individual revenue and cost metrics are simply accounting figures that in isolation say little about the health of the business. Let’s recap some of the things we know about this nifty magic number from earlier SaaS metrics rules-of-thumb.

Intuitively, the long run profitability of SaaS companies requires
the recurring contribution of current customers to cover the acquisition cost of new customers,
therefore the average customer rate of return for SaaS companies
must exceed both the current customer churn rate and the new customer growth rate.

So, what is a good value for Joel’s SaaS Magic Number? Well, I don’t think anyone could argue with 1, a valiant goal, but rather optimistic. If your average customer rate of return is 100%, chances are you don’t need VC money, because you can bootstrap your way to the top given that your customers pay for themselves within the first year. Personally, I’m prejudiced toward profitable growth in the long run, not just growth (call me old fashioned). In which case, I’d recommend shooting for something in the J ≥ 50% per year range, implying a minimum time to profit of 2 years (probably more like 4 years with growth and churn) and the ability to grow annually at upwards of 50%.

At the very least, you should set a goal for average customer rate of return that significantly exceeds your combined churn and target growth rates, J > a + g, unless you are prepared to burn cash for a very, very long time and build up a very, very large accumulated loss deficit on your balance sheet. But, focusing exclusively on growth to the detriment of profit is a dangerous game in SaaS. Most SaaS markets are not as wide-open as enterprise software markets were twenty years ago. Personally, I believe there is very little a weak executive team can do for $110M in expense at a $10M loss, that a strong executive team can’t do better for $90M in expense at a $10M profit. To each his own.

I’ll let the interested reader refer to Lars’ original blog post for the specifics, but after a little comparison I’ve concluded that “The” SaaS Company Magic Number is roughly equivalent to following ratio in my SaaS metrics model.

The SaaS Company Magic Number = ARR ÷ CAC

(for newly acquired customers with ARR measured annually)

Thus, the difference between Joel’s SaaS Magic Number and The SaaS Magic Number is the explicit inclusion of recurring cost of service, giving IMHO a stronger metric for the financial health of SaaS companies that includes the full measure of both recurring revenue and total cost of service. In relation to The SaaS Magic Number we have the following:

Joel’s SaaS Magic Number = [ ARR - ACS ] ÷ ARR x The SaaS Magic Number

Joel’s SaaS Magic Number = Contribution Margin x The SaaS Magic Number

Let’s plug in some numbers and see what we get. If we want a quick and dirty comparison of The SaaS Magic Number to Joel’s SaaS Magic Number, then the easiest approach is to assume a contribution margin of 50%. This isn’t so outrageous given the cost structure of many SaaS/software companies that even in the early stages tend to spend about 50% on sales and marketing (CAC) and 50% on everything else (ACS).

When Contribution Margin = 50%

Joel’s SaaS Magic Number = The SaaS Magic Number / 2

Aha! Now we have a rhyme to the reason of why Lars just might want to talk to you if The SaaS Magic Number is > 1.5, because you are primed for a profitable, annual viral growth rate of up to 75%, something VCs like very much. However, I have to take issue with “pouring on the gas” if your The SaaS Magic Number is simply above .75 . In this example, your average customer rate of return is about 38%., giving you a best case time to profit of 2.7 years. In reality, if your annual growth is approaching 38% (which your investors will very much desire) and your contribution margin is anything less than 50% (very likely in the early stages), then your real time to profit is probably double or triple that (8 years!), because you aren’t even covering your acquisition costs let alone your total cost of service. Depending on your actual contribution margin, you may very well be burning through wads of cash by stepping on the gas. Personally, I’d up this requirement to a clean The SaaS Magic Number of > 1.0 with the added requirement that ARR ≥ 2 x ACS, so that your contribution margin can quickly recover acquisition costs. This is consistent with the prevalent SaaS metrics conventional wisdom that you’d like to recover your customer acquisition cost in the first 12 months, but with the added requirement that you need to pay for your ongoing service costs as well.

Almost done! There is one more post in this SaaS metrics series, because clearly we can’t stop until we reach SaaS Metrics Rule of Thumb #10 and have a complete SaaS metrics top ten list. The next and final post in the SaaS metrics series entitled SaaS Customer Lifetime Value Drives SaaS Company Value will take things up a level to examine the highest level SaaS financial metric of company valuation, and it has some fun, no-holds-barred extra credit math notes for the math heads. Stay tuned!

Check out the rest of the SaaS Metrics Rules-of-Thumb

• SaaS Metrics Rule-of-Thumb #1 – SaaS Churn Kills SaaS Company Growth
• SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn
• SaaS Metrics Rule-of-Thumb #3 – Viral Growth Trumps SaaS Churn
• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even
• SaaS Metrics Rule-of-Thumb #6 – Growth Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #7 – Churn Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #8 – Upselling and Upgrades Accelerate SaaS Profitability
• SaaS Metrics Rule-of-Thumb #9 – Joel’s SaaS Magic Number
• SaaS Metrics Rule-of-Thumb #10 – SaaS Customer Lifetime Value Drives SaaS Company Value

Too much churn, you lose money. Grow too fast, you lose money. Customer acquisition cost too high, you lose money. Recurring cost of service too high, you lose money. Just shoot me now! How on earth do you make money in SaaS?

If you’ve been following this series on SaaS metrics, then you’ve probably worked your way up to just such a level of frustration. Because, that pretty much sums up the last four SaaS metrics rules-of-thumb on SaaS profitability:

• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even
• SaaS Metrics Rule-of-Thumb #6 – Growth Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #7 – Churn Creates Pressure to Reduce Total Cost of Service

It just can’t be! This is high tech. This is the Internet! Software, not hardware. SaaS can’t just be a low-cost commodity business. There must be a value-based approach. A SaaS revenue solution!

There is. But, it doesn’t mean you can ignore the fundamentals. Driving down total cost of service through automation and economies-of-scale is fundamental. SaaS executives that ignore this put the long term profitability of their SaaS businesses in peril. But, enough on lowering SaaS costs. Let’s talk increasing SaaS revenue!

The previous post in this SaaS metrics series entitled Growing Up Poor – How Foolish SaaS Companies Lose Money was a bold attempt to once and for all solve the mystery of why seemingly successful SaaS companies lose money…in excruciating detail (sorry for that). The cornerstones of the analysis were the relationships established between the values of churn, “a”, growth, “g”, and the baseline average customer break-even time, “BE₀” as follows:

BE₀ = CAC ÷ [ ARR - ACS ]

In the formula above, “CAC” is the average acquisition cost per customer, “ARR” is the average recurring revenue per customer, “ACS” is the average recurring cost of service per customer, and the 0 attached to the BE is intended to indicate the absence of churn, i.e., the baseline break-even.

These constraints were the basis of SaaS metrics rules-of-thumb #6 and #7 which claim that both growth and churn, respectively, increase pressure to reduce total cost of service (CAC and ACS) in order to accelerate profitability (reduce BE₀) and to ensure that profitability is even possible (gBE₀,aBE₀ < 1). However, the viable SaaS revenue strategy of increasing average recurring revenue (ARR) without increasing total cost of service was carefully set aside for later examination. Leading us to...

SaaS Metrics Rule-of-Thumb #8
Upselling and Upgrades Accelerate SaaS Profitability

What exactly does it mean to increase average recurring revenue without increasing average customer acquisition cost or average recurring cost of service? First, no additional customer acquisition cost means that we must increase recurring revenue from current customers. Second, no increase in average recurring cost of service means that we must do so in the normal course of business with very little extra effort, preferably through customer self-service (self-selling!). In other words, SaaS companies can accelerate time to profit by upselling and upgrading current customers, but only if it follows an exceptionally low cost purchase process distinct from the new customer acquisition process. The chart below depicts the impact of upselling and upgrades on SaaS time to profit.

Upselling and upgrades leverage the initial investment of customer acquisition cost
to accelerate SaaS time to profit by countering the delays of both growth and churn.

The chart above depicts the effect of upselling on the two uglier examples presented in the last SaaS metrics series installment where times to profit where 8 years and never, respectively. These are determined by the intersections of the blue line, which depicts the recurring contribution (recurring revenue minus recurring cost of service) of a SaaS company with a growth rate of 20%, zero churn, and an average recurring contribution per customer of $1000 – $500 = $500 per year, with the two red lines representing average customer acquisition costs of $2000 and $2,750 respectively.

The green line depicts the impact of increasing SaaS revenue over time through upselling and upgrades. With upselling, the 8 year time to profit scenario is accelerated to just under 5 years, and never has been magically transformed to about 7.5 years as represented by the intersection of the green line with the same red CAC lines. The green line represents the recurring contribution of the same SaaS company, but with an upselling strategy that increases contribution margin, (ARR – ACS), without incurring any one-time acquisition costs by $75 each year, or an upsell percentage of 15%. (see SaaS Metrics Math Notes below)

Finally, some light at the end of the tunnel! Pure upselling as defined here, reduces BE₀ by increasing recurring revenue without significantly increasing total cost of service, i.e., money for nothing. What could be more strategic!

Two great examples of upselling and upgrades in practice are Salesforce.com and Xignite. Salesforce.com has standard user-based subscription pricing, but then breaks its subscriptions into carefully designed modules of increasing functionality. If you’ve ever been a salesforce.com customer, then you know that 90% of the upgrade process consists of you, as the customer, repeatedly bumping into the limits of your current subscription. When you need more users, or you need the capabilities of enterprise over professional, then you go online or pick up the phone and order them. The cost to salesforce.com is minuscule compared to the original customer acquisition cost (which includes not only customers, but all the prospects that didn’t buy). Salesforce.com is a master of application discovery, which is the process of letting less experienced customers discover for themselves the value of more advanced product capabilities.

Xignite is a cloud services provider of on-demand market data (Who was that guy?!). Unlike monolithic end-user applcations such as Salesforce.com, Xignite’s Web services can be purchased separately and mixed and matched at will. The company offers a market data catalog of more than 50 services with usage-based subscription plans, all of which can be easily purchased online. The range of potential recurring revenue from the lowest plan for a single service to the largest plan for all services gives an upsell potential for each customer of around 1000:1 or total potential upsell of 100,000%!

This post concludes the mini-series on SaaS profitability, but it is not the end of the SaaS metrics series. Surely, we’re only up to SaaS Metrics Rule-of-Thumb #8 and we can’t possibly stop until we round it off to #10. The next post in the series entitled Joel’s Magic Number for SaaS Companies will focus more deeply on what IMHO is the most important SaaS metric of all: average customer rate of return, and will go beyond the math to provide some simple benchmarks to help your SaaS business grow up healthy and profitable.

Check out the rest of the SaaS Metrics Rules-of-Thumb

• SaaS Metrics Rule-of-Thumb #1 – SaaS Churn Kills SaaS Company Growth
• SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn
• SaaS Metrics Rule-of-Thumb #3 – Viral Growth Trumps SaaS Churn
• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even
• SaaS Metrics Rule-of-Thumb #6 – Growth Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #7 – Churn Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #8 – Upselling and Upgrades Accelerate SaaS Profitability
• SaaS Metrics Rule-of-Thumb #9 – Joel’s SaaS Magic Number
• SaaS Metrics Rule-of-Thumb #10 – SaaS Customer Lifetime Value Drives SaaS Company Value

Over and over again, I see exciting headlines for SaaS companies like this…

That when I dig a little deeper, I end up having my bubble burst by a dismal financial statement that looks something like this…

Where is all the money going? Why do so many successful SaaS companies, startup and public alike, have such a difficult time turning a profit?

This is the fourth post in a series on SaaS metrics that will once and for all solve the mystery of why seemingly successful SaaS companies lose money by using a little mathematics. But, before I jump into the technical details, here is the short answer: foolish SaaS companies don’t seriously tackle the problem of reducing Total Cost of Service through automation and economies-of-scale, and they foolheartedly chase after the Recurring Revenue Mirage.

In the last installment in this series, I introduced the following two SaaS metrics rules-of-thumb:

• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even

Which in concert make the claim that the time to profit for a growing SaaS company will always be greater than the baseline break-even time for the average SaaS customer.

t_profit ≥ BE₀

BE₀ = CAC ÷ [ ARR - ACS ]

Where “CAC” is the average acquisition cost per customer, “ARR” is the average recurring revenue per customer, “ACS” is the average recurring cost of service per customer, and the 0 attached to the BE is intended to indicate the absence of churn, i.e., the baseline break-even.

In this post, we’ll zero in on the interplay of growth and profitability with customer acquisition cost and recurring cost of service (collectively total cost of service), starting with…

SaaS Metrics Rule-of-Thumb #6
Growth Creates Pressure to Reduce Total Cost of Service

We know from the earlier SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn, that successful SaaS companies must strive to grow new customer acquisition at a percentage growth rate, “g”, that exceeds the churn rate. This growth model is quite general. It applies equally well when growth is slow and plodding with a small value of g and when growth is rapid and extremely viral with a high value of g. The only requirement is that our successful SaaS company grow consistently from year to year, which is of course what we all want. In this case, the relationship above between SaaS company profitability and SaaS customer break-even can be made much more exact (see math notes below):

Since no SaaS company in this universe will throttle back on growth, the only acceptable strategy is to reduce the value of BE₀ such that g x BE₀ is significantly less than 1, otherwise it may be a looooooong time to profit, perhaps well after the company stops growing altogether (gasp!).

This creates pressure to reduce total cost of service by lowering the average customer acquisition cost, CAC, and lowering the recurring cost of service, ACS. Since growth is the culprit, the surest and most effective defense is to fight fire with fire by reducing total cost of service through automation that provides cost-lowering economies-of-scale. (The one other viable solution, increasing ARR without increasing CAC or ACS will be the topic of the next post in the series entitled SaaS Revenue – The Beauty of Upselling and Upgrades) This latest SaaS metric rule-of-thumb is visually depicted in the chart below.

New customer acquisition costs are paid with the recurring contribution of current customers.
If a SaaS company grows rapidly, growing acquisition costs can outpace
the build-up of recurring contribution, such that profitability is impossible.

As outlined in the previous post on SaaS profitability, time to profit occurs when the rate of profit is zero:

[ ARR - ACS ] C(t_profit) – CAC ΔC_new(t_profit) = 0

Or, when recurring contribution, [ ARR - ACS ] x C, equals new customer acquisition costs CAC x ΔC_new. The blue line in the chart above shows the recurring contribution for a SaaS company with a customer acquisition growth rate of 20%, zero churn, and a recurring contribution per customer of $1000 – $500 = $500 per year. The three red lines represent CAC values of $1250, $2000 and $2,750 respectively. In these three scenarios, the baseline break-even values are 2.5 years, 4 years and 5.5 years, giving values for g x BE₀ of .5, .8 and 1.1 respectively. We can see that in each case the actual time to profit values of 3.5 years, 8 years and never significantly exceed the respective baseline break-even values. And, in the case of g x BE₀ = 1.1 profitability is unattainable. If we add a churn rate of 25% to the mix, such that our growth is drowned out by churn, then we end up paying a hefty bill on both ends of the customer lifecycle, and profitability becomes even more difficult to attain as depicted in the chart below.

New customer acquisition costs must be paid for by current customers.
While growth drives up total acquisition cost,
churn erodes the revenue base available to cover it,
pushing time to profit out even further.

Perhaps not so surprisingly, given the mirror image relationship between viral growth and churn explored in the second post in this series, the impact of churn on profitability mirrors that of growth.

In the example depicted in the chart above, churn has pushed our growth delayed times to profit of 3.5 years, 8 years and never, out to 5.8 years, never and of course still never, respectively. Leading to the mirror image SaaS metrics rule-of-thumb for churn.

SaaS Metrics Rule-of-Thumb #7
Churn Creates Pressure to Reduce Total Cost of Service

New customer acquisition costs must be paid for by current customers. While growth drives up total acquisition cost, churn erodes the revenue base available to cover it, pushing time to profit out even further. Therefore, churn generates the same pressure to reduce total cost of service as does growth

The harsh judgment of this unbiased, objective SaaS metric math seems pretty clear all around. If you want your SaaS company to ever be profitable, then lower your total cost of service already! These new SaaS metric rules-of-thumb provide the basis of the original claim at the beginning of this post. Only fool-hearty SaaS companies believe that they can grow their way to profitability, it is the recurring revenue mirage that can never be reached, because profitability will only be achieved as growth slows or stops entirely. The combination of growth and profitability requires an extreme discipline of lowering total cost of service through economies-of-scale.

If you are now as bummed as I was when I first fully digested this dilemma, then do not fear! It is always darkest before the dawn. Earlier, we set aside one other viable strategy for accelerating profitability: upselling, or rather increasing recurring revenue without increasing customer acquisition cost or average recurring cost of service. The next post in this series entitled SaaS Recurring Revenue – The Beauty of the Upsell will explore the importance of upselling and upgrades as an essential SaaS strategy to accelerate profitability.

Check out the rest of the SaaS Metrics Rules-of-Thumb

• SaaS Metrics Rule-of-Thumb #1 – SaaS Churn Kills SaaS Company Growth
• SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn
• SaaS Metrics Rule-of-Thumb #3 – Viral Growth Trumps SaaS Churn
• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even
• SaaS Metrics Rule-of-Thumb #6 – Growth Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #7 – Churn Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #8 – Upselling and Upgrades Accelerate SaaS Profitability
• SaaS Metrics Rule-of-Thumb #9 – Joel’s SaaS Magic Number
• SaaS Metrics Rule-of-Thumb #10 – SaaS Customer Lifetime Value Drives SaaS Company Value

Well, I can’t be sure beyond a reasonable doubt, so you be the judge. On Feb 2, I published this post entitled Viral Growth Trumps SaaS Churn, which makes the simple case that the best way to fight churn (exponential decay) is with virality (exponential growth). About two weeks later on Feb 15, Seth Godin published this strikingly similar post on viral growth entitled Viral Growth Trumps Lots of Faux Followers, which makes the simple case that the best way to fight faux followers (exponential decay) is with a viral idea (exponential growth).

Hmmmm…great minds must really think alike!

First I should say, I love Seth Godin’s stuff. I’ve snagged way more of Seth’s stuff than vice versa, for example SaaS Do #4 Craft a Compelling Story is completely Seth Godin’s and is the main topic of his book All Marketers Are Liars (and, is listed in the Chaotic Flow Worthy Reads blogroll). Believe it or not, my wife Christy is currently reading Seth Godin’s latest book Linchpin as I write this (and highly recommends it). But, IF Seth Godin really is reading Chaotic Flow, I think at the very least a pingback or comment is in order. C’mon Seth, share the love.

As an avid admirer of all things ironic and self referential (like…uh…viral growth), I couldn’t pass on the opportunity to examine this particular case study in light of itself. So, I am proposing a second order derivative viral growth vs. big followers principal of Seth Godin’s first order derivative viral growth vs. faux followers principle of the original viral growth vs. churn principle.

Highly Connected Followers Trump Viral Growth

Seth’s principle that Viral Growth Trumps Faux Followers claims that it is better to spread a good idea to a small group and rely on the strength of the idea to move it along through viral growth than it is to spread a mediocre idea to a big group of faux followers by brute force, because their interest will soon wane and your idea will eventually die out. I’ve recast Seth’s depiction of this principle in the chart below.

Seth’s viral growth vs. faux followers chart shows how many people are talking about your idea at any given time. This version, which is more in line with the original viral growth vs. SaaS churn post shows the total number of people who have heard of your idea.

There is an underlying assumption in Seth Godin’s viral growth model that when removed is the source of this new principle. Seth assumes that all your followers are created equal, such the viral growth rate at which the idea spreads is constant. That is, I tell two friends, then they tell two friends, and so on. But, what happens when just one of your followers is an outlier that taps into another huge group of followers. Say, like…uh…Seth Godin. Or, Oprah. Let’s call this the Oprah Chain Reaction, as a recurring case of the Oprah Effect. Here I tell two friends, but one of them happens to be Oprah Winfrey. And, one of her friends happens to be Seth Godin, and so on. This principle is shown in the chart below.

Even if your idea is kinda stupid, influential followers may pass it along wider and faster
than a good idea that is waiting around for the hockey stick takeoff of viral growth.

In all fairness, I should note that this “new” viral growth vs. BIG followers idea is itself highly derivative. This Oprah Chain Reaction is really just a new name for a very old idea. It’s not what you know; its who you know. Or, recast for the fast paced world of social media…

It’s not what you tweet; it’s who’s following you!

For example, the original principle of viral growth trumping churn is an OK idea, but realistically the math is over 200 years old, and it isn’t like viral growth is going to improve your sex life or cure baldness (in which case Seth Godin and I would both be all over it!). Unfortunately, Chaotic Flow’s number of followers is much closer to 1,000 than 100,000, so viral growth appears to be the only option to widely spread an idea, even if it is just OK. Wait a minute! Seth Godin on the other hand is a VERY connected guy with lots of followers. So, let’s take a look at what happened when this just OK idea made it into his network of followers. Whereas the original viral growth vs. churn post has a measly 19 retweets at current count, Seth’s viral growth vs. faux followers post has a whopping 1,392 retweets (and climbing)! As another measure, let’s take a look at the results for the Google searches on viral growth and viral growth trumps.

Because Seth’s Blog has so many more backlinks than Chaotic Flow
he has more Google juice to spread the word with or without viral growth.
Hence, his post goes straight to the top of search results for viral growth.

Seth Godin’s followers retweet his posts to Google ubiquity.
So, search results for viral growth trumps are swamped with syndicated retweets and refeeds.
It is so cool that Google cut that deal with Twitter!
Chaotic Flow readers…GET WITH THE PROGRAM
and retweet those posts!

Profitability, one would think, should come quite naturally to a successful, growing SaaS company.  But, SaaS startups have consistently struggled to reach profitability.  Unprofitable SaaS companies have gone public and remained unprofitable for years after their IPOs, even as they grow revenues into the hundreds of millions of dollars.  SaaS companies have eschewed economic convention, with management and investors alike calmly shrugging off the passe’ advice of their obsolete microeconomics professors who cry out in vain from their blackboards that “the role of the firm is to maximize profit.” Many authors have tried to make sense of this morass, two of the more interesting attempts are Bob Warfield’s post entitled Why do SaaS Companies Lose Money Hand Over Fist, and this really cool analysis by Christian Chabot of tech IPOs comparing software companies that were profitable to those that were not profitable at the time of their IPO.  And, I’ve certainly made no secret of my own opinion in posts like this one entitled SaaS Failures – The Recurring Revenue Mirage.

This is the third post in a series on SaaS metrics that will unravel the mystery of  SaaS profitability (and the lack thereof) from a different angle, a little mathematics.  Once and for all we’ll solve the puzzle of why seemingly successful SaaS companies lose money. So, even if you’re not a math junkie like me, please be patient and plough your way through the technical mumbo jumbo. I’ll guarantee some of these results will surprise you!

SaaS profitability is such an important topic that I’m breaking it up into three separate posts (this being the first) that will build on each other by examining three increasingly complex scenarios: 1) stable growth with churn, 2) viral growth, and 3) growth through upselling and upgrades.  Along the way, I’ll also introduce a number of new SaaS Metrics Rules-of-Thumb that highlight the impact of customer acquisition costs and recurring cost of service on long term SaaS profitability.
So, let’s get going…

SaaS Metrics Rule-of-Thumb #4
Company Time to Profit Follows Customer Break-Even

This subtle, strikingly simple rule will reverberate through all that comes to follow on SaaS profitability. And, it provides a simple sanity check for predicting when, if ever, your SaaS business will reach profitability. The gist of the rule is that your SaaS recurring revenue over time is nothing more than the sum of its parts. Therefore, the sooner you break even on a single customer, the sooner you will reach profitability as a company.

The chart below visually shows this principle for a SaaS company with a constant rate of customer acquisition eroded by churn which was closely examined in the first post in this SaaS metrics series.

The accumulated recurring contribution of a SaaS company at any time
mirrors the lifetime accumulation of the typical SaaS customer
directly linking company time to profit with customer break-even time.

The average break-even point for an individual customer without churn, “BE₀” is given by the following formula:

BE₀ = CAC ÷ [ ARR - ACS ]

Where “CAC” is the average acquisition cost per customer, “ARR” is the average recurring revenue per customer, “ACS” is the average recurring cost of service per customer, and the 0 attached to the BE is intended to indicate the absence of churn, i.e., the baseline break-even.

Now let’s compare this simple individual customer SaaS metric with the more complex SaaS metric of company time to profit. At any given time, the rate at which a SaaS company generates profit is given by the following formula:

Profit = P(t) = [ ARR - ACS ] C (t) – CAC ΔC_new(t)

Where C is the number of customers and ΔC_new is the new customer acquisition rate. Time to profit occurs when this expression changes from a negative loss to a positive profit, or when profit is equal to zero.

P(t_profit) = [ ARR - ACS ] C(t_profit) – CAC ΔC_new(t_profit) = 0

If we consider the simplest case scenario of a constant new customer acquisition rate with no churn, “b”, then after time t, we will have b x t total customers, giving the following equation for time to profit:

P(t_profit) = [ ARR - ACS ] x bt_profit – CAC x b = 0

t_profit = CAC ÷ [ ARR - ACS ] = BE₀

In this simplest of cases, time to profit not only follows break-even, it equals break-even. This relationship between company time to profit and break-even time for the single average customer is a completely general principle for SaaS (or any recurring revenue subscription business). Unfortunately, the simple case scenario above is also the best case scenario as spelled out in the next SaaS metrics rule-of-thumb.

SaaS Metrics Rule-of-Thumb #5
Best Case Time to Profit is Simple Break-Even

SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn states that if you want to break free of the churn limit, then you must increase new customer acquisition to compensate. Unfortunately, this mandate places you neatly between a rock and a hard place with respect to profitability. On the one hand, your customer acquisition costs increase each year, while on the other hand churn is eating away at your ability to break-even on every new customer you bring the door. The net result is that both churn and growth push SaaS profitability out beyond the single customer break-even point in direct relation to their intensity. The higher your churn, the longer it takes to reach profitability. The higher your growth rate, the longer it takes to reach profitability. And, if either your percentage churn rate or growth rate are too high given your customer acquisition cost and recurring contribution, your SaaS business will never reach profitability. The chart below shows this general principle for the simple case of a constant new acquisition rate subject to churn.

For a growing SaaS company subject to churn,
the best case time to profit is the average break-even time for a single customer.
If churn is too high, profitability becomes impossible to achieve.

In the next installment in this series entitled Growing Up Poor – How Foolish SaaS Companies Lose Money, I plan to zero in on the root causes that lead seemingly successful SaaS companies to lose money. And, then move on to the solutions to this obstinate problem. Some of the concepts presented in this post as well as earlier SaaS Metrics Rules-of-Thumb were developed in previous installments in this SaaS Metrics series:

• SaaS Metrics – Viral Growth Trumps SaaS Churn
• SaaS Metrics – SaaS Churn Kills SaaS Growth

Check out the rest of the SaaS Metrics Rules-of-Thumb

• SaaS Metrics Rule-of-Thumb #1 – SaaS Churn Kills SaaS Company Growth
• SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn
• SaaS Metrics Rule-of-Thumb #3 – Viral Growth Trumps SaaS Churn
• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even
• SaaS Metrics Rule-of-Thumb #6 – Growth Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #7 – Churn Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #8 – Upselling and Upgrades Accelerate SaaS Profitability
• SaaS Metrics Rule-of-Thumb #9 – Joel’s SaaS Magic Number
• SaaS Metrics Rule-of-Thumb #10 – SaaS Customer Lifetime Value Drives SaaS Company Value

Everybody wants their Internet startup to go viral. But, just what does going viral mean? In his book, The Tipping Point, Malcolm Gladwell spells out the mechanics of how ideas spread virally by modeling the roles of key individuals that he calls connectors, mavens and salesmen (highly recommended on the Chaotic Flow blogroll Worthy Reads). When it comes to the Internet, Josh Kopelman eruditely points out that you can’t go viral by bolting it on as a last minute marketing program. You must apply SaaS Top Ten Do #5 and build viral growth into the product.

The aspiration of this post is not to add to the complexity of these theories of viral growth, but to uncover the simplicity of viral growth through a little mathematics. This is the second post in a series on SaaS metrics that explores the impact of viral growth in SaaS using a simple heuristic model with the goal of extending the list of SaaS Metrics Rules of Thumb started in the first post in the series regarding SaaS churn.

The mechanics of viral growth vary greatly by product, customer, market, and even culture. But, the mathematics pretty much boil down to the singular idea expressed so well in the kitschy Faberge shampoo commercial from the 70’s and 80’s.

Viral growth is customer growth that is proportionate to the number of customers.

C_{n + 1} = ( 1 + g ) x C_n

All the connectors, mavens, salesmen and friends are rolled into the little “g” (for growth rate) in the formula above, which states that the number of customers in the time period n + 1 is equal to the number of customers in the time period n, plus a multiple of those same customers. You can think of g as the percentage of friends who actually told two friends who actually then went out and bought some shampoo divided by the amount of time it took them all to complete this circuit.

Like churn, viral growth scales with the number of customers.
When the viral growth rate exceeds the churn rate,
growth explodes through the churn limit.

If you read the previous SaaS metrics post on SaaS churn, you might recognize this formula, because it is identical to the churn formula only the negative churn rate -a has been replaced with the positive viral growth rate g. Thankfully, we can skip over the algebra this time and jump to the solution, simply by replacing -a with (g-a). This quick slight-of-hand gives us the formula for the number of customers in the time period n, C_n, that incorporates viral growth as well as churn.

C_n = b⁄(g-a) x ( ( 1 + g -a )ⁿ -1)

In this formula, ”b” is the baseline constant customer acquisition rate prior to either viral growth or SaaS churn kicking in. The mirror-like relationship between viral growth and SaaS churn in the formula above leads us to our next SaaS metrics rule of thumb.

SaaS Metrics Rule-of-Thumb #3 – Viral Growth Trumps SaaS Churn

The previous SaaS Metrics Rule-of-Thumb #2 claimed that in order to break through the churn limit, new customer acquisition growth must outpace churn. Because churn increases in direct proportion to the number of customers, the surest approach is to drive growth at a higher rate that also increases in proportion to the number of customers, i.e., viraly.  Moreover, investors generally expect companies to increase revenue on a percentage basis year over year.  Holding products and prices constant, this again requires viral growth of your customer base.  Viral growth can come from many sources, but I like to classify it into the following three distinct stages.

Stage 1 Viral Growth – Brute Force Sales and Marketing  (small g)

In any given industry, most companies will spend a rather fixed percentage of revenue on sales and marketing, regardless of the size of the company.  When the effectiveness of these efforts scales in proportion to the level of spending (which is clearly not always the case), they will drive growth at a rate proportionate to revenue.  In a SaaS business, this will also be proportionate to the number of customers.  Hence, it is possible to drive growth in proportion to the number of customers simply through nuts and bolts sales and marketing.  This stage is arguably not viral growth in the usual marketing sense of the words, but it does meet the strict mathematical definition where customer growth is proportionate to the number of customers.  This in fact is the beautiful irony of the Faberge shampoo ad, which was a very effective nuts and bolts marketing campaign, but was probably less successful at getting even one friend to tell one friend about the product, let alone two.

Stage 2 Viral Growth – Customer Advocacy (modest g)

When you are successful at driving word-of-mouth and getting your customers to recommend purchasing your product to new prospects you reach stage 2, the most commonly understood variation of viral growth made famous by the Faberge ad.  SaaS customers hold great potential to be advocates, because they confirm their commitment day after day as they continue to use your product and month after month after month as they send in their renewal payments.  Driving viral growth through active customer engagement that turns customers into advocates and advocates into evangelists should be high on the agenda of every SaaS marketing plan.

Stage 3 Viral Growth – Ecosystem Buzz  (BIG g)

The ecosystem for your product extends beyond your customer base to include all potentially interested parties such as press, analysts, bloggers, social media hounds, partners, vendors, investors, employees, and perhaps even the general public. Most SaaS compaines engage in public relations, tracking down and pitching Mr. Gladwell’s mavens and connectors in the hopes that they will pass the word on to their respective audiences and networks.  But, true and lasting stage 3 ecosystem buzz is invariably built upon strong stage 2 customer advocacy.  Twitter is a great curent example.  If it weren’t for the dedicated and comparatively small group of Silicon Valley Web 2.0 junkies that were the early adopters of Twitter, you would not be able to follow CNN tweets today.

As previously mentioned, this is the second post in this series on SaaS metrics.  In the next post, I’ll start adding revenue and costs to the model to explore the impact of viral growth and SaaS churn on SaaS profitability over time.

Check out the rest of the SaaS Metrics Rules-of-Thumb

• SaaS Metrics Rule-of-Thumb #1 – SaaS Churn Kills SaaS Company Growth
• SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn
• SaaS Metrics Rule-of-Thumb #3 – Viral Growth Trumps SaaS Churn
• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even
• SaaS Metrics Rule-of-Thumb #6 – Growth Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #7 – Churn Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #8 – Upselling and Upgrades Accelerate SaaS Profitability
• SaaS Metrics Rule-of-Thumb #9 – Joel’s SaaS Magic Number
• SaaS Metrics Rule-of-Thumb #10 – SaaS Customer Lifetime Value Drives SaaS Company Value

This is the first post in a series on SaaS metrics where I plan to develop a variety of SaaS financial metric models using simple mathematical heuristics. In the process, I hope to highlight important relationships between key SaaS metrics and develop a short list of valuable SaaS Metrics Rules-of-Thumb.

SaaS Metrics Rule-of-Thumb #1 – SaaS Churn Kills SaaS Company Growth

Consider a SaaS company that acquires new customers at the constant rate of “b” (for bookings), and has a percentage churn rate of “a” (for attrition). The number of customers after n periods of time “C_n” is given by the following formula:

C_n+1 = b + ( 1 – a ) x C_n

C_n = b + b (1-a) + b (1-a)² + b (1-a)³ … + b(1-a)^n-2 + b(1-a)^n-1

C_n = b⁄a x ( 1 – ( 1 -a )ⁿ )

This formula can be approximated at the two extremes of early growth and maturity.

These two boundaries are shown in the chart below along with the blue curve representing total customers over time.

As a SaaS company grows, absolute churn increases with the total number of existing customers and will limit growth if new customers are not added at a faster and faster rate.

In the early days, churn is small and the customer base grows unimpeded at the customer acquisition rate. As the customer base grows, the absolute value of churn increases and soon overwhelms new customer acquistion. When the customer acquisition rate, b, equals churn, a x C, then the number of customers coming in the door is exactly equal to the number leaving. At this point further growth is impossible, limiting the total customer base size to the new customer acquisition rate divided by the percentage churn rate. This limit might be more than satisfying if you run a bootstrapped, private SaaS business as your primary means of personal income. But, it is unlikely to satisfy investors if you are a VC-backed SaaS startup, bringing us to…

SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn

The bad news is that if you want to grow your SaaS company without limits, you can’t just sit back and book a hundred new customers per year and expect recurring revenue to accumulate, because sooner or later churn catches up with you. You must not only acquire new customers, but you must acquire them at an increasing rate that outpaces your increasing churn. The good news is that the lower your percentage churn rate, the longer you have to figure it out, because your growth won’t slow unless your new customer acquisition rate remains constant for a time equal to one divided by the percentage churn rate. But, who wants to acquire customers at a flat rate anyway?

In the next post in this SaaS Metrics series, I’ll explore how viral growth is the surest path (albeit not the only path) to achieve the goal of SaaS Metrics Rule-of-Thumb #2 above and break the chains of SaaS churn.

Check out the rest of the SaaS Metrics Rules-of-Thumb

• SaaS Metrics Rule-of-Thumb #1 – SaaS Churn Kills SaaS Company Growth
• SaaS Metrics Rule-of-Thumb #2 – New Customer Acquisition Growth Must Outpace Churn
• SaaS Metrics Rule-of-Thumb #3 – Viral Growth Trumps SaaS Churn
• SaaS Metrics Rule-of-Thumb #4 – Company Time to Profit Follows Customer Break-Even
• SaaS Metrics Rule-of-Thumb #5 – Best Case Time to Profit is Simple Break-Even
• SaaS Metrics Rule-of-Thumb #6 – Growth Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #7 – Churn Creates Pressure to Reduce Total Cost of Service
• SaaS Metrics Rule-of-Thumb #8 – Upselling and Upgrades Accelerate SaaS Profitability
• SaaS Metrics Rule-of-Thumb #9 – Joel’s SaaS Magic Number
• SaaS Metrics Rule-of-Thumb #10 – SaaS Customer Lifetime Value Drives SaaS Company Value

SaaS Do #8 Enable Mass Customization is a core principle for building SaaS applications. Salesforce.com, for example, has taken it to new heights with offerings such as the Force.com platform. However, do SaaS-based development platforms such as Force.com represent a fundamental shift in application development, or are they simply the SaaS equivalent of Microsoft Visual Basic for Access? How do they stack up against cloud computing platforms like Amazon Web services? This post examines the potential for competitive advantage through mass customization in cloud computing vs. SaaS.

The short answer is this…
Mass customization in cloud computing is more natural, more flexible, and offers more potential for competitive advantage than in the wildest dreams of SaaS, because cloud computing is built on Web services that are a) inherently abstracted, b) independent components and c) accessible at every layer of the technology stack.

Note: In a previous post, I claimed that the salient difference between SaaS and cloud computing is that SaaS has largely been about Internet applications used by people, whereas cloud computing is about Internet application components used by other computers. More succinctly, Websites vs. Web Services. Although everyone seems to have their own definition of all the cloud buzzwords, I’m going to be rather specific and equate them as such: Cloud = Internet, SaaS = Websites for human users, Cloud Computing = Web services for computer users. My intent is not to debate or define the industry terminology, but simply to keep track of what the heck I’m talking about here at Chaotic Flow.

The Role of Meta-data in Mass Customization
Mass customization in SaaS is achieved by converting hard-coded application functions into meta data configuration settings.  For example, multi-tenancy converts hard-coded deployments of multiple customer databases into a single database infrastructure where each customer deployment is identified by a unique customer ID. All the technical miracles that distinguish one customer’s data from another customer’s data are abstracted to this single piece of meta-data to enable data-driven functionality like Customer[1].Name = “Company X” and “Customer[2].Name = Company Y”. Voila!  Mass customization = meta data abstraction of functional capability.

More Natural – The Inherent Abstraction of Web Services
Mass customization is more natural to cloud computing vs. SaaS for one simple reason: meta-data abstraction is inherent to Web services, but it is optional for websites. SaaS applications must be carefully architected to enable mass customization at all, i.e., it is a matter of good SaaS application design discipline to employ a multi-tenant database, configurable security settings, customizable page views, etc. In contrast, every function of a Web service is inherently abstracted to meta-data in the XML inputs and outputs of the API.

The Xignite stock quote Web service can return a wide variety of information
such as the current stock price, an intraday stock chart, and financial news
that varies by the stock symbol (meta-data) supplied to it.

For example, given a particular stock symbol (meta data), the stock quote Web service above can return a wide variety of information about a company such as the current stock price, an intraday stock chart, and financial news. Let’s say Company X above is a manufacturer that uses this Web service to create a website with detailed, current financial information about the company for potential investors. Now let’s say Company Y is a Web publisher that uses this Web service to create a widget that provides in-line stock quotes for companies discussed in its news stories. Here we have two completely different applications built from a single Web service. Imagine trying to architect this degree of mass customization into an end user SaaS application, i.e., a single Web application that can present anything from a detailed company financial profile Web page to a single stock quote widget simply by changing application configuration settings. Sounds like iGoogle to me. Not easy.

More Flexible – Independent Components vs. Monolithic Applications
The stock quote example above also demonstrates the flexibility of enabling mass customization through independent components over that of a monolithic application. Changing a single feature from hard-coded to configurable in a SaaS application can require modification and refactoring at every layer of the software stack from the database structure to the user interface, e.g., adding user-defined custom fields. Moreover, the introduction of  new configuration settings can have a multitude of known and unknown impacts on existing and seemingly unrelated features, e.g., changing an address format from a standard US postal structure to a configurable structure that better supports international clients. The result is that even the simplest modifications to a SaaS application must be carefully considered and become more difficult the more complex the application.

Web services are relatively independent, loosely coupled components. New functions can be added to current Web services, and entirely new Web services introduced with minimal impact on other Web services. For example, I use Google’s chart Web service to generate the charts on the SaaS Model Scorecard. If Google wants to add new chart types to this Web service, it simply creates new values for the “cht” parameter and any other relevant options. However, a SaaS charting application would require changes to the UI to select the new chart type, select the new chart type options, visually edit the new chart type and display examples of the new chart type. Depending on the architecture of the application, this could be a modest change or a monumental change.

Moreover, independence allows customers to assemble solutions from best-of-breed components more easily. The stock quote web service above supplies the data and charts, but the UI can be constructed using the customer’s tool of choice, including any SaaS application that supports Web services. Application integration across functional silos has proven to be a consistent challenge for SaaS companies. Most have turned to open APIs, i.e., Web services to address this challenge. The more a SaaS application opens itself through Web services, the more it acquires the flexibility for mass customization available to native cloud computing solutions. Pushed to the limit, it can become difficult to tell the website from the Web service.

Wildest Dreams – Morphing Applications and Infrastructure, not Just Features
Imagine building a SaaS application that could magically morph from CRM to ERP through configuration settings. The complexity of building such an application is staggering, not to mention the subsequent configuration. Again the Force.com platform comes to mind. Now consider cloud computing. Let’s say I store the respective CRM and ERP application executables on Amazon S3. And, I create a Web service with two calls: gimme CRM and gimme ERP. When I log in, I select ERP or CRM. This Web service automatically downloads the specified application and instantiates it on a farm of Amazon EC2 virtual server instances, where it can be accessed from the URL www.elastic_crm_or_erp.com. This neat trick is possible, because Web services allow mass customization at every layer of the software stack. In this particular case, the configuration reached down below the application layer itself to the O/S and swapped out the entire application. From the user point of view, I just magically see my website change from ERP to CRM.  This approach is really overkill for this simple example, but it makes clear the ability of cloud computing to handle meta data driven, ad-hoc modification at any layer in the technology stack.  It could just as well be accomplished at a much higher level in the stack using two SaaS applications and a single sign-on…uh, Web service.

Mass Customization and Competitive Advantage in Cloud Computing
Although cloud computing offers greater potential for mass customization than SaaS, cloud computing does not really compete with SaaS. Amazon AWS and Force.com are unlikely competitiors, because they segment the market into the high-end and low-end of mass customization respectively, and customers will choose one or the other according to their requirements.

Like SaaS, cloud computing competes against on-premise software, offering many of the same benefits such as lower TCO and mass customization. But unlike SaaS, cloud computing does not compete head-to-head for a final end-user applications. It competes for components at every layer of the technology stack from storage to user interface. As a result, the competition centers around architecture as much as outsourcing. While SaaS adoption is usually driven by functional executives, cloud computing adoption is driven by IT executives. Adopters of cloud computing must rethink how they build applications, employing interchangeable components that may or may not exist within their own firewall. In order to overcome this barrier, cloud computing vendors should leverage mass customization to offer their customers orders of magnitude improvements in functional versatility, deployment flexibility and infrastructure elasticity in addition to lower TCO.

In SaaS, it’s virtually impossible to sell someone a lemon, because SaaS customers typically get to try before they buy, and they can walk at any time simply by canceling their subscription. In contrast, traditional enterprise software vendors are notorious for obscure product capabilities and pricing, because up-front purchase creates a short term financial incentive to avoid disclosing any more information than the minimum necessary to close the deal. The enterprise customer thus enters a long and intricate dance with the enterprise sales rep in order to develop the trust required to overcome the risk of signing that fat license check. When combined with the uncertainty of buying a business critical application over the Web, most SaaS startups quickly find themselves between a rock and a hard place by the need to engender an even higher level of trust than their enterprise competitor, while simultaneously having nowhere to hide their shortcomings.

A SaaS marketing strategy of complete and total business transparency
removes constraints to unleash the volume and deal size of online transactions.

So don’t! The best SaaS marketing strategy for building trust is complete and total transparency. With the right attitude, this apparent weakness can be deftly turned into a competitive strength that accelerates growth by streamlining SaaS adoption costs and risks. When you apply the SaaS marketing tactic of public online disclosure of your product capabilities, pricing, terms, service level agreements, support process, performance metrics, platform security, privacy policy, company history, customer satisfaction ratings, etc., you remove constraints to unleash the volume and deal size of online transactions by simplifying the buying process, preempting risk-related objections, and building a reputation of the highest integrity.   Moreover, you ensure high rates of customer satisfaction and success by avoiding the project failures that have historically characterized enterprise software by only signing customers that are a good fit for your service.

Ask yourself how much you spend right now on Google AdWords without ever having spoken to a sales rep. How does this compare to your own average selling price for online transactions?  Now, ask yourself why.  The answer is transparency, from company reputation to cost-per-click.

PS Trish Bertuzzi from Bridgegroup asked for specific examples, so please see the comments if you are interested in the response. And, feel free to add your own examples of SaaS vendors that are doing a good job at transparency.

More posts in the SaaS Marketing Tips Series:

• SaaS Marketing Tips – Metrics that Make a Difference
• SaaS Marketing Tips – Don’t Be CRUD on the Cloud
• SaaS Marketing Tips – Search is About People, Not Engines

The growth challenge of most SaaS vendors can be boiled down to the following simple formula:

revenue growth = price x volume = average MRR x new sales velocity

Delivering on the promise of low total cost of ownership, the price of SaaS is often an order of magnitude lower than the price of licensed enterprise software. This low price point creates enormous pressure on volume. Reaching profitability may require a new customer every week, every day or even every minute! Increasing sales velocity is the essence of the SaaS business challenge.

At each stage of the buying process, your SaaS prospect will encounter adoption costs and risks that reduce your sales velocity. I like to compare this to scaling a cliff where adoption costs are measured by the height of the cliff and adoption risks are measured by the difficulty of the climb.

How high are the adoption costs and risks that your SaaS prospects must surmount?

…Here are seven proven strategies for increasing SaaS sales velocity by reducing the adoption costs and risks more >>>

The preceding is an excerpt from a guest blog post by Chaotic Flow at Sandhill.com
Just click through for the complete post. Cheers! JY

I’m in the process of updating my blogroll, and I’d like to expand the SaaS-Cloud section. If you write a SaaS, Cloud, Startup, Sales or Marketing blog, or have some favorites that you read, besides Chaotic Flow of course, please leave a comment or send me an email. Looking for active blogs with loyal readers that deliver consistent, well thought out original content, and I’m happy to do a link exchange if your blog meets these criteria. (blogroll located at the lower right sidebar)

Cheers,
JY

It seems that everyone is jumping on the cloud bandwagon.  Cloud this, cloud that, everything cloud.  Salesforce.com has all but rebranded its entire business as cloud.  Instead of sales force automation, we now have “Sales Cloud 2” (and “Service Cloud” and “Custom Cloud” and “Collaboration Cloud” with nice little TM’s attached, so if you were thinking of using them for yourself, you can forget it!).  I suppose it might be a good thing.  Personally, I was getting pretty tired of Salesforce.com trying to “force” this brand, “force” that brand on me.  I really don’t have a problem with the cloud buzz per se.  I think it is good for the industry, because it creates excitement, momentum and funding for B2B Internet companies.  But, I am concerned that all this unbridled rebranding and repositioning is obscuring the underlying technological and economic shifts which characterize this next stage of Internet evolution.

Cover from the Pink Floyd album Obscured by Clouds.
Not really relevant, but I needed a picture.
Retweet if you’re a Pink Floyd fan!

The Web 1.0 Internet revolution, of which classic software-as-a-service is a part, arose as a result of the universal interface offered by the Web browser.  Suddenly, anyone could access any global computing resource over the Internet as long as they had this one, standard client application.  It didn’t really matter what happened on the back end, because everyone was plugging into the same application on the front end.  I like to think of this as application – user interoperability.  The economic implication of this paradigm shift was that you could now aggregate customers around the globe onto a single Internet application.  Say for example, ordering books or sales force automation.

The shift we are seeing now is driven by increased interoperability on the server side, or rather application – application interoperability.  And, because it is on the back end, it is occurring at every layer of the software stack from the virtual machines of cloud computing to the really simple syndication (RSS) of personal blogs.  Not only have underlying Web service standards like XML, SOAP and JSON gained broad acceptance, but general openness, public APIs, and application development frameworks are becoming the cultural norm for Internet applications.

Let’s be clear on the magnitude of this technology shift.  The current Web 2.0 boom, call it the social Internet revolution, is realistically 95% new product ingenuity and 5% new technology.  A little AJAX, a little RSS, and voila!  Facebook.  Twitter.  The application-application interoperability of the cloud is a fundamental technology shift that has the potential to unleash the same kinds of disruptive economies-of-scale and disintermediation of legacy business models by aggregating computing resources in the same fashion that Web 1.0 did by aggregating users.  But, this time the war won’t be fought at the user level between brick-and-mortar businesses and Web businesses.  It will be fought at the application level between traditional closed, proprietary on-premise software and open, standards-based cloud offerings.

For example, this is the essential value proposition of Xignite.  Xignite supplies on-demand market data via Web services.  As Salesforce.com “Sales Cloud 2” is to Oracle-Siebel, Xignite is to legacy data feed application vendors like Thomson-Reuters and Bloomberg.  But, instead of serving a multitude of users from a single application infrastructure to create economies of scale and reduce TCO, Xignite creates new economies of scale and reduces TCO by servicing a multitude of applications, such as WorlframAlpha, NetSuite, Forbes.com, corporate financial apps at GE and iPhone apps at startups like Palantir.

For me, this giant leap forward in application-application interoperability is the essence of this revolution we call The Cloud.   The rest is window dressing.

If you read my SaaS Sales Management Tips series, then you may have noticed a glaring absence of detail with respect to specific SaaS sales organization strategies. The reason for this conscious omission is that there is no one right strategy. There are only the strategies that are right for your specific SaaS business at a specific point in time with your specific situation, i.e., customers, products, growth, maturity, etc. However, these strategic decisions can make or break the growth and profitability of the business, because more than any others they determine the balance between maximizing revenue and minimizing acquisition cost. They are some of the toughest choices a SaaS Sales VP or CEO has to make.

The SaaS Adoption Dilemma
The third post in the SaaS Sales Tips series discusses strategies for accelerating organic growth (SaaS Success Do #3) by making it possible for your customers to buy from you even if you don’t show up for work. But, what do you do when you need revenue today and your under-educated customers and your overly-complex SaaS product just can’t seem get it together on this approach? You’ve just encountered the SaaS Adoption Dilemma, a situation that arises when your adoption costs are way too high and you must choose a strategy for lowering them. Your very unpleasant short term choices are a) forego revenue until your online marketing and support reach maturity or b) cover up the problem with people and wreck your acquisition costs (SaaS Don’t #4). If you’re measured on revenue as opposed to margin and you earned your sales stripes in enterprise software, then you will probably choose option b) without a second thought. But, you may have just made your quarterly commission while sinking your company, your stock options and your job when the business runs out of cash.

The organizational strategies of option b) typically come in two flavors: pre-sale lead reps to find, educate and qualify prospects and pre/post-sale technical services reps to ensure successful on-boarding and ongoing use of the product. While the vision should be for these activities to be 100% automated, the reality is that they rarely are in the early days and that there is a limit at maturity to the achievable degree of automation set by the inherent complexity of your product and self-serviceability of your customer. These constraints imply a steady state organization at maturity–for example a ratio of 3 sales reps to one lead rep and one technical services rep–that you are sure to overstaff in the early stages before you have fully automated adoption through online marketing and support. The danger is that you lock into this bloated, early stage organization model and create excuses for not simplifying adoption through automation, thus killing your long term profitability. A great way to stay on top of this threat is to include all ancillary staff in your calculation of sales productivity: revenue per rep, where rep includes everyone required to acquire and keep a customer, not just the sale rep.

SaaS Sales Organization Options Arranged by the Strategic Dimensions They Address

Hunting, Farming, and Other Pastimes
Conventional wisdom holds that SaaS sales organizations should be split into separate sales and account management groups that are responsible for new business and recurring business, hunters and farmers respectfully. While this is a good rule of thumb, it is not always the case. I’ve seen plenty of SaaS sales organizations that do not follow this model and they usually have good solid reasons for doing otherwise. So, it’s worth reviewing the rationale for this split in the first place: churn. Churn is the rate at which customers cancel their subscriptions. If it is greater than your new business bookings rate, then you are shrinking instead of growing! Many SaaS businesses target a churn rate of less than 5% annually, which is no small feat–it requires very, very satisfied customers, hence the account management function. In addition to lowering churn, a strong account management organization will also drive upgrades by increasing use of the product through continuing education and support. The overarching goal of this organizational strategy is to maximize lifetime customer value, the topic of SaaS Sales Tip #9.

If your SaaS application follows the monetization model of end user-based pricing broken out by functional level such as base, professional and enterprise versions and it is frequently adopted by a smaller group within a larger organization, then there is a very good chance that the tried-and-true hunting vs. farming split will work for you. In this scenario, revenue from existing customers is maximized by deepening and broadening each customer’s use of your application. But what if greater product use is NOT the primary driver of revenue from current customers? What if you sell a large portfolio of relatively straightforward products, like Zoho or Xignite? In this case, revenue from current customers is just as likely to come in the form of up-selling additional products. What if you are a B2B2C platform, where the growth rate of your customer’s customers is the primary driver of future revenue? And, how important is the continuity of interpersonal relationships between the customer’s decision makers and your sales team? Given all the organizational choices presented here, the worst case scenario is that your strategic relationships are continually shuffled from lead rep to sales rep to technical services rep to account manager and back again. In addition, the split between new sales and account management is time-dependent on market maturity, i.e., prospects vs. customers, so it will change as the business grows.

What’s Your Magic Number?
I’ve mentioned several times already that the root cause of these tough SaaS sales choices is the trade-off between revenue generation and acquisition costs. In theory, there is an optimal strategy for growth that doesn’t sacrifice long term profitability. When it comes to measuring the impact of sales organization strategy on both growth and profitability, the magic number to watch is revenue per rep.

revenue per rep = average deal value x close rate x qualification rate x leads / reps

And, its close financial cousin sales margin.

sales margin = 1 – cost per rep / revenue per rep

Where revenue and deal value are valid SaaS measures for recurring revenue
for a given time period, i.e., monthly (MRR), annual (ARR), or lifetime (LTV), and reps are the staff
responsible for producing said revenue and costs during that time.
Broader measures that explicitly include churn, upgrades, etc. and all relevant staff
are best for avoiding the recurring revenue mirage.

Most SaaS companies follow an inbound sales model where the sales capacity must be matched to the inbound lead flow, otherwise adding reps causes revenue per rep to decline (note the ratio of leads/reps in the formula). Simply put, if marketing delivers 100 leads and you have 2 reps, then they each get 50. If you have 4, then they each get 25. And, so on. This is in contrast to an outbound sales model where leads per rep is a constant and the number of leads scales automatically with the number of reps, i.e., more reps, more sales calls, more leads. Adding reps in an inbound sales model when you don’t have the leads to support them is the proverbial pushing on a string.

Therefore, the labor-intensive sales organization strategies above should only be applied when the investment demonstrably increases revenue per rep in the form of higher qualification rates, higher close rates, higher deal values, and shorter sales cycles (less time per deal). A sales organization that generates $2M ARR per rep and has an annual cost per rep of $100K will be far more profitable than one that generates $200K ARR per rep. If you are at $200K ARR today, can you increase the efficiency of your sales organization and accelerate organic growth to reach $2M tomorrow?
What’s your magic number?