David Cummings on Startups

Category: SaaS

  • Publicly Traded SaaS Company Valuations

    In December of 2010 I wrote a post titled Publicly Traded SaaS Companies detailing the companies, market cap, quarterly revenues, and number of employees. Since that post the numbers have moved upwards nicely along with a couple being acquired (SuccessFactors and Taleo) and a few new ones going public (Responsys, ExactTarget, and Demandware). Let’s take a look at the current numbers:

    • salesforce.com (NYSE:CRM) – customer relationship management SaaS company.
      Market cap: $21.52 billion
      Last reported quarter’s revenues: $631.9 million
      Employees: 7,785
    • NetSuite (NYSE:N) – enterprise resource planning (accounting, inventory, etc) SaaS company.
      Market cap: $3.45 billion
      Last reported quarter’s revenues: $64.09 million
      Employees:  1,265
    • Constant Contact (NASDAQ:CTCT) – email marketing for small business SaaS company.
      Market cap: $873.79 million
      Last reported quarter’s revenues: $57.53 million
      Employees: 926
    • SuccessFactors – human resources SaaS company.
      Bought by SAP for $3.4 billion
    • Taleo – human resources SaaS company.
      Bought by Oracle for $1.9 billion
    • LogMeIn (NASDAQ:LOGM) – remote machine access SaaS company.
      Market cap: $846.84 million
      Last reported quarter’s revenues: $32.32 million
      Employees: 482
    • LivePerson (NASDAQ:LPSN) – live chat SaaS company.
      Market cap: $899.43 million
      Last reported quarter’s revenues: $36.51 million
      Employees: 524
    • Responsys (NASDAQ:MKTG) – email marketing SaaS company.
      Market cap: $587.27 million
      Last reported quarter’s revenues: $37.24 million
      Employees: 693
    • Demandware (NYSE:DWRE) – ecommerce SaaS company.
      Market cap: $774.98 million
      Last reported quarter’s revenues: ~$15 million
      Employees:  215
    • ExactTarget (NASDAQ:ET) – email marketing SaaS company.
      Market cap: $1.62 billion
      Last reported quarter’s revenues: ~$50 million
      Employees: ~1,100

    The companies that get the largest premium are the leaders in their space and have the fastest growth rates. In almost all cases market cap, quarterly revenues, and employees have grown since the last report 16 months ago. Software-as-a-Service continues to be hot.

    What else? What are your thoughts on publicly traded SaaS company valuations?

  • Successful SaaS Startups Grow Slower Than a Hockey Stick Curve

    The proverbial hockey stick-like growth curve for startups has been talked about many times, including yesterday. That growth curve is rare, and even more rare over extended periods of time. In reality, startups that experience the hockey stick growth curve often do so for a limited period of time, while the market adoption is at it’s peak, and then the growth abruptly slows down or goes away. So, instead of a hockey stick over a short period of time (< 7 years) it is really an ‘S’ like curve slanted to the right where there’s slow growth, hyper growth, and finally slow/no growth.

    Crazy hockey stick-like growth is more often attributed to companies with truly revolutionary products or strong network effects where the value of the system keeps building on itself indefinitely (e.g. Facebook). Software-as-a-Service (SaaS) or cloud-based software products that are successful have growth curves flatter than a hockey stick. Here are a few reasons why:

    • SaaS revenue layers on itself year after year which makes it easier to keep growing but harder to keep accelerating growth due to the law of large numbers.
    • SaaS contracts are often annual with the payments made quarterly, making payments of the lifetime value of the customer stretch out over several years whereas installed software products get most of the value up-front, and thus installed software products can have a sharper revenue growth curve, everything else being equal.
    • Customer churn for SaaS companies (read about the leaky bucket number) eats away at growth and even if the renewal rate stays constant, the number of new customers needed to grow at the same rate continues to increase.

    SaaS companies that break out are likely to have a growth curve flatter than a hockey stick but continue to grow as a business for longer periods of time due to the layering of recurring revenue.

    What else? What are your thoughts on successful SaaS startups growing slower than a hockey stick curve?

  • Sales Reps Without Territories for SaaS

    One of the more common strategies associated with sales reps is assigned geographic territories. Territories make sense when field sales are involved but with the growth of Software-as-a-Service (SaaS), more and more sales are done over the phone and internet. A major downfall of territories is that in a fast-growing startup every additional sales rep that’s hired  shrinks someone’s territory, and shrinking territories is tough on morale. With a modern marketing automation system or CRM system there’s a better way.

    Here’s one way to have sales reps without territories for SaaS-type sales teams:

    • Score and grade all inbound leads automatically and route them to a market response rep
    • Route sales qualified leads to a queue that distributes leads in a round robin fashion to the account executives
    • If there’s a particular source of lead that is sales qualified but even more valuable, like from a test drive, route those to a second queue of the same account executives (the idea is to have equitable distribution of the regular qualified leads and the best leads)

    With one or more round robin lead queues, reps are assigned leads in a straightforward manner that is minimally dilutive when an additional sales person is added.

    What else? What are some other ideas around sales reps without territories for SaaS?

  • The Scalability of a Programmer’s Effort

    Recently I was talking to a friend of mine who’s an attorney. We were talking about how most law firms operate with an intense focus on the billable hour including a number of tactics around CYA and risk mitigation that result in more dollars billed to clients. As an example, each year we get an external financial audit and as part of it they’re required to ask our law firm if we have any outstanding litigation, and that results in a $500 lawyer bill because each of the corporate-related departments has to chime in and say they don’t know of any thing. That $500 is a waste but I understand why it happens. I was excited to read that in England they passed a law allowing non-lawyers to be equity partners in firms that offer legal services. That’s right, in the United States you can’t own part of a firm that offers legal services unless you’re a lawyer — how crazy is that?

    Law firms live and die by the billable hour due to a number of reasons one of which is the scalability of their efforts. Think about it: for each client they use boiler-plate documents but then spend extensive time customizing them to the situation, and there are always a thousand permutations. There are some economies of scale for senior lawyers with the associate pyramid scheme whereby junior people work hard for several years in hopes of becoming a partner, and the big pay increase that comes with it. Now, contrast that to the scalability of a skilled programmer’s efforts.

    A skilled teenager can write software in his dorm room to help with the dating scene on campus and become a billionaire many times over less than a decade later (Facebook). The power of software is astounding. In fact, software is eating the world according to Marc Andreessen. With the proliferation of open source providing re-usable components at no cost, cloud computing for infinite scalability, and smart phones in millions of pockets the scalability of a programmer’s effort increased by a magnitude, if not more.

    Of course, without users or customers the value of a programmer’s efforts can be minimal but for startups that make it, economies of scale of software engineering is astronomical. Pinterest had over 10 million visitors last month, been in business a couple years, and yet only has 16 employees. The scalability of a talented programmer’s effort is incredible.

    What else? What are some other thoughts on the scalability of a programmer’s effort?

  • Two Schools of Thought on Scaling B2B SaaS App Data

    Scaling the data storage for B2B Software-as-a-Service (SaaS) applications typically falls under two schools of thought: one or more fully-contained accounts per database or specialized multi-tenant sub-systems that handle certain types of data. There are pros and cons to each approach.

    Fully-Contained Accounts

    B2B apps are often simpler than B2C apps when it comes to data storage. In a B2B app, one account/user doesn’t need to know about another, whereas in a B2C app accounts/users have to have a global context for all other accounts/users (think Facebook Friend requests). Fully-contained accounts can be on individual databases or multi-tenant such that one or more accounts are on the same database delineated by an account ID.

    One analogy I like to use is housing for people. A fully-contained account on a private database is a like a single family home. Multiple fully-contained accounts on one database is like one building in an apartment complex where everyone gets their own space but there are greater economies of scale having everyone together.

    Challenges for fully-contained accounts in a multi-tenant environment arise when the size of the accounts start changing and growing at different rates. Back to the apartment complex example, one family wants a home gym and decides they want a new bedroom for it, only all the other three bedroom apartments in the complex are full. What does the family do? Well if the family can afford it the tendency is to go to a single family home that is suited uniquely to them.

    A single family home is much more expensive to maintain, on a per family basis, compared to a building in an apartment complex. Services like landscaping, security, and amenities like a gym or pool are much more affordable when spread out over dozens or hundreds of people. A single family home can have all those accoutrements but the cost structure is no where near the same.

    Specialized Sub-Systems

    Now, assume some accounts in the multi-tenant fully-contained database approach grow so large that they need their own dedicated database. With the housing analogy, larger families start moving to single family homes from the building in an apartment complex. Assume the apartment complex didn’t have a pool — the app didn’t have that feature yet. Now, the startup decides a new feature is needed — the equivalent of a pool — and adds it to the application. The pool is manageable in the apartment complex that houses 100 families with the cost of chemical treatments, cleaning, etc spread out over a large number of users. For the single family homes that were created by the accounts that got too large, each now has a pool by the nature of SaaS applications having a single code base for all customers, and those pools all need to be managed. Going from pool to pool, even with automated tools and help, becomes less efficient and more costly to do chemical treatments, cleaning, etc.

    Specialized storage and application sub-systems are designed to solve this problem. Think of a simple survey application. The info for the accounts, users, billing, survey questions, and more are pretty simple and not storage intensive. What is storage intensive is keeping track of all the survey responses and survey respondents. That information is going to grow exponentially compared to the core account data. It deserves a dedicated sub-system.

    Now, back to the housing analogy. Instead of families desiring a home gym moving to single family homes, the apartment complex introduces new buildings in the same complex, only the different buildings serve specific functions like a gym with an indoor pool, parking deck, and storage units for for each family. The individual features and storage needs get dedicated attention such that the regular gym with pool can grow into a 100,000 square foot facility with Olympic-size pool, and all the families can stay put in the apartment building that’s part of the same complex. Areas that change disproportionately can get the necessary attention without affecting other aspects of the application.

    Conclusion

    When starting out, fully-contained accounts is easier to implement and doesn’t require much overhead, making it the right choice for young B2B SaaS apps. If data grows linearly and everything is tightly related, keep it simple with fully-contained accounts. As the application grows, and certain types of data grow disproportionately faster than others, specialized sub-systems scale better and in a more cost-effective manner, making them the right choice for mature, data-intensive B2B SaaS apps.

    What else? What are your thoughts on these two schools of thought for scaling B2B SaaS app data?

  • Pre-Paid SaaS Contracts are Free Working Capital for Startups

    Software-as-a-Service (SaaS) as a business model has a number of advantages including alignment of value between customer and vendor, strong cash flows, high gross margins, and great economies of scale. As with any growing startup, one of the most limiting factors is cash — the faster the business grows, the more cash it eats. Another benefit of SaaS that should be mentioned more often is that of pre-paid contracts.

    With pre-paid contracts, like Salesforce.com requires, payments are made in advance of service being rendered. These contracts are often pre-paid quarterly or pre-paid annually with a discount (e.g. pay for the full year and get 10% off). For the startup this results in free working capital to grow the business. Yes, there’s an unearned income liability and an obligation to fulfill the service, but with the money in the bank, many startups use it to grow the business even faster than if they didn’t have pre-payments.

    There’s another secondary benefit of pre-paid SaaS contracts: potential profits in the bank aren’t taxed until revenue is recognized and profit earned. Say it is December 31st and the startup’s bank account has $100,000 more than it started the year. Normally, if that’s profit it would be taxed around 30% leaving only $70,000 left to invest and grow the business. Well, with accrual accounting and $100,000 of unearned income due to pre-paid contracts, that money isn’t taxed until the revenue is recognized resulting in more capital to grow the business on January 1st.

    Pre-paid SaaS contracts provide free working capital for startups and should be considered when thinking through business ideas (e.g. can we get customers to pre-pay us to help fund the business?).

    What else? What are your thoughts on pre-paid SaaS contracts as free working capital for startups?

  • The Power of Recurring Revenue in Startups

    At today’s MIT Enterprise Forum Atlanta Entrepreneurs Uncensored Sanjay and I were asked if there were things that kept us up at night. Being the first to respond, I quickly said that I sleep great at night (unrelated to my Tempur-Pedic bed but that’s nice as well) for one simple reason: recurring revenue.

    Recurring revenue with high gross margins is the holy grail of business models.

    Here are some reasons recurring revenue is so powerful for startups:

    • Recurring revenue makes cash flow forecasting very easy (running out of cash is the #1 reason startups fail)
    • Recurring revenue makes predicting hiring needs straightforward so that you can recruit well in advance
    • Recurring revenue is often indicative of a business model that has strong economies of scale
    • Recurring revenue makes banks more comfortable with providing debt to finance growth (most businesses won’t qualify for debut unless the entrepreneurs have significant personal assets and are willing to do personal guarantees)

    Recurring revenue businesses are more difficult to get off the ground but once they’re going they’re easier to manage. Recurring revenue helps entrepreneurs sleep better at night.

    What else? What are some other reasons recurring revenue is so powerful for startups?

  • Product Stickiness Spectrum for SaaS Products

    In the Software-as-a-Service (SaaS) world one of the questions investors love to ask is, “what’s your annual renewal rate?” The idea is that products with a higher renewal rate, and thus a lower churn, are more desirable, everything else being equal. After the renewal rate question comes questions around why customers leave and under what circumstances. Not all products and markets are created equally — there’s a product stickiness spectrum for SaaS products.

    Here are some example SaaS product categories with levels of stickiness:

    • High
      Ecommerce (switching costs, SEO, payment gateways, product catalogs, etc result in many moving parts)
      Content management (especially with a high number of pages integrated and users trained)
    • Medium
      Marketing automation (CRM integration, scoring + grading rules, email templates, landing page templates, tracking code, etc)
      Payroll (the nuances of electronic deposit, vacation days, risk of error, etc make people less likely to switch)
    • Low
      Email marketing (CSV file of contacts, email templates, DNS changes, etc)
      Virtual meetings / webinars (event sign-up form, URLs, etc)

    As with anything there are tradeoffs. Typically, categories with higher levels of stickiness have higher integration and consulting costs to make the system work, so there’s going to be a heavier people component, and lower economies of scale.

    What else? What are some other SaaS categories and where do they fit on the stickiness spectrum?

  • SaaS Leaky Bucket Number

    Software-as-a-Service (SaaS) has a number of important metrics for the business model with one of the most important being customer renewal rates / customer churn. Josh James, the co-founder of Omniture, which was bought by Adobe for $1.8 billion a couple years ago, sent this tweet out last week:

    http://twitter.com/#!/joshjames/status/154644835490463744

    The idea that they’d sign up 1,200 customers per month and have 800 customers leave per month drives home the need to closely watch customer renewals. The ratio of new customers to lost customers is critical and now has a formal name:

    Leaky Bucket Number = New Customers Per Month / Customers Lost Per Month

    Note that it doesn’t take into account the average revenue per new customer vs the average revenue per customer that leaves as well as customer upgrades or downgrades. Generally, it’s a good metric to monitor because it’s easier for people to understand we signed 29 customers and lost 11 customers because it continues to keep the number of lost customers top-of-mind. And, it’s especially important for this number to be greater than one otherwise the startup is losing more customers than it’s adding.

    What else? What do you think of the SaaS leaky bucket number?

  • Measure Customer Engagement for SaaS Apps

    One of the many things Salesforce.com does well is generate a monthly customer engagement email that gets emailed to account administrators. In the email, there’s a separate line for each of the major functions of the application as well as how many times it was used by the account in the last month, or if it hasn’t been used yet. Salesforce.com has automated part of the account management process, but more importantly, helped customers get more value from the software.

    Software-as-a-Service (SaaS), since it’s delivered over the web, can have end-user interaction measured using standard web analytics tools like Google Analytics. Like with any application, it’s easy to measure which users use which features. SaaS providers should measure customer engagement in their app.

    Here are some potential customer engagement categories to measure:

    • Value generated by the application (e.g. return on investment)
    • Number of user logins, as well as logins by type of role
    • Modules used, frequency of usage, and importance of modules (e.g. the more important modules are weighted more heavily)
    • API calls, if applicable, which measure the activity of third-party integrations with the SaaS app

    SaaS providers should measure customer engagement for their apps and incorporate it into their processes.

    What else? What other customer engagement categories should be measured?