David Cummings on Startups

Category: SaaS

  • 8 Sales Questions and Answers for Early Stage SaaS Startups

    Earlier today an entrepreneur reached out seeking help. His company has recently cleared the $1 million in annual recurring revenue milestone and he’s working on the strategy to build out a sales team.

    Here are his eight questions and my answers in the Pardot context:

    1. At what stage in the company did you hire your first salesperson (headcount, years since founding, revenue level)?
      Pardot was started March 1, 2007. Our beta (minimum respectable product) was ready at the end of the summer and we hired our first two sales people, while still be pre-revenue, at the same time on September 1, 2007 (always hire sales people in pairs, if possible).
    2. Was your initial sales team functioning as ‘explorers’ or were they repeating a process that you had already defined?
      The initial sales team functioned as explorers and worked to figure out the best places to hunt. One of the salespeople didn’t work out and was let go of quickly while the other sales person worked out incredibly well.
    3. How long before that person became profitable?
      The sales person that worked out was profitable by their second quarter with us.
    4. How long before you hired subsequent salespeople?
      Our next sales person was brought on in Q1 2008 as it was clear the first sales person was doing great. As a simplistic rule of thumb, I like the ratio of $1 in sales rep expense to $3 of new annual recurring revenue.
    5. Did you use the predictable revenue model of one SDR to three Account Execs?
      We implemented Predictable Revenue at Pardot and used the 1:3 SDR to AE ratio (we implemented an appointment setting team before the book was published). In some cases, I’ve seen a 1:1 ratio of SDR to AE.
    6. If so, did you consider other methods?
      We didn’t use a different methodology but have always liked the idea of one team to set appointments and one team to close deals.
    7. What are the biggest things that you would do differently in building a sales team knowing what you know now?
      I’d invest more aggressive in sales people once the model was proven (we could have hired many more sales people) and I’d use more modern sales acceleration tools like SalesLoft and WideAngle.
    8. How narrowly did you focus on verticals at the beginning of your sales process i.e. did your initial team sell across verticals or not?
      Early on, we realized the companies that received the most value from marketing automation were technology companies as they had more tech-savvy marketing teams and good budgets. We didn’t divide the team up by vertical but most of the proactive sales efforts were to other tech companies.

    I appreciate the entrepreneur sending me the questions and I look forward to providing more information about what worked well, and didn’t work well, over our five year journey.

    What else? What are some other sales questions for a seed or early stage startup?

  • SaaS Churn Rates With Early Exit Customers

    Whenever I talk with Software-as-a-Service (SaaS) entrepreneurs, the topic of growth rates, and corresponding churn rates, always come up (see Quantifying the SaaS Valuation Growth Rate Multiplier). After talking about churn rates, I like to ask the following question: how long do customers have to stay with you to know they’re in it for the long haul?

    For the first few years of Pardot, most customers were month-to-month without an annual contract. At first, we paid commissions out to our sales reps at a rate of roughly 12% of the first year’s revenue. Quickly, we realized that if customers weren’t a good fit, they’d leave within the first four months. Customers that stayed longer than four months would be customers indefinitely. To make things more aligned, we changed our commission with sales reps to be 50% of the first four months of customer revenue, paid monthly as revenue came in, so that the sales reps would sign good-fit customers.

    Now, there’s a debate in the SaaS metrics world about calculating churn. Do you count all new customers signed or do you only count new customers that have made it past the critical starting period (e.g. the first four months in the early Pardot example)? As a course of business, it’s easier to count all new customers as that makes it easy to track and measure the critical SaaS metrics. For the health and long-term view into the business, I prefer not counting customers that churn in the critical starting period. Cost of customer acquisition, renewal/churn rates, lifetime value of the customer, etc all have to take into account not counting early churn customers, if that’s the route the entrepreneur chooses to take regarding metrics.

    Some variances of this practice include analyzing cohorts on a weekly/monthly/quarterly basis as well as only counting customers if they meet certain size requirements (e.g. it’s usually the smallest of businesses that have the highest churn rates, so if you exclude any customers below a designated size when tallying the metrics, they don’t negatively affects the startup’s real numbers). Put another way, don’t assume that all new customers should be tracked the same way from a metrics perspective.

    What else? What are some more thoughts on measuring customers that churn early as part of the overall customer metrics?

  • Dreamforce 2014

    This week is the annual Super Bowl of Software-as-a-Service (SaaS) with the Dreamforce 2014 event in San Francisco. It’s the biggest event of its kind and draws 100,000+ people from all over the world. While I’m not attending this year, I’ve been many times in the past.

    Here are some thoughts from previous years:

    If you’re a software entrepreneur and haven’t been to a Dreamforce event, I’d highly recommend it.

    What else? What are some other thoughts on Salesforce.com’s annual Dreamforce event?

  • Meaningful Metrics When Industry Metrics Don’t Make Sense

    Recently an entrepreneur was lamenting that his cost of customer acquisition (CAC) was significantly higher than the first year’s revenue for a customer (and even higher than the lifetime value for a customer). Naturally, I started asking more questions and digging into the situation. Turns out, it was a classic case of applying industry metrics to a business that was still in its infancy. Metrics like the cost of customer acquisition being less than the first year’s revenue is a great standard, but isn’t relevant when signing up the first 10-100 customers (unless the customers pay an unusually large sum).

    Imagine having two sales reps ($4,000/month each), a marketing manager ($4,000/month), modest pay-per-click spend ($1,000/month), and a tradeshow ($5,000 one-time) one quarter. Over the course of three months, that’s a sales spend of $24,000 (no commissions) and a marketing spend of $20,000. Now, say it was a good quarter and 20 new customers were signed paying an average of $1,000/year. $20,000 is new annual recurring revenue was added (no churn), yet $44,000 was spent on customer acquisition, resulting in a business with a poor magic number. Only, assuming this was early in the life of the product, say within the first 12 months, it’s too soon to definitively say that the customer acquisition model isn’t going to work.

    When industry metrics don’t make sense yet, the focus should be on growing 10% every week. Weekly metrics, especially as a percentage, work well because the absolute numbers are so small. Eventually, after things go well, the absolute numbers get bigger and industry metrics become applicable. Apply the right standard to the right situation.

    What else? What are some other examples when industry metrics don’t make sense?

  • One SaaS Application of Record Per Job Function

    Software-as-a-Service (SaaS) is entering its third phase of maturity. Phase one focused on enterprise applications that became platform products like Salesforce.com, NetSuite, and others. Phase two was about general point solutions, mostly for the small-to-medium sized business market like Pardot, Mailchimp, and Zendesk. Phase three is new vertical-specific SaaS applications as well as more specialized solutions that represent portions of more complicated products.

    One way to think about it is that there is an application of record for each job function (that is, a product that people in that job function spend a large number of hours per week to perform their job). The application of record often feeds data into a more general platform (like Salesforce.com) such that data is made available to any other product that might need it. Here are a few examples of applications for job functions:

    Disclosure – I’m an investor in SalesLoft and Rivalry.

    Think about all the different job functions in a mid-sized company. Now, think about the SaaS applications currently used. What job functions currently use a generic solution, but would be better served by a more specialized solution? Look for more SaaS solutions to emerge that help run specific job functions.

    What else? What are some more thoughts on one SaaS application of record per job function?

  • The Difficulties in Getting a SaaS Startup Off the Ground

    Continuing with yesterday’s post on SaaS and Barriers to Entry, if it seems like Software-as-a-Service (SaaS) products are easy to reproduce from a functionality perspective, why are there so few successful ones? Software development and delivery costs have dropped 10x over the past 15 years due to the rise of open source software and cloud computing. Technically, it’s easy to take one product and make a barebones reproduction of the most basic functionality. Only, there’s so much more than that.

    Here are a few reasons why it’s so difficult to get a SaaS startup off the ground:

    • Initial minimum respectable SaaS products still require years of continuous development to reach maturity and broad applicability (while it might cost a few hundred grand to get a decent product to market, it’ll take several million over a few years to get a robust product to market)
    • SaaS products are often billed monthly, with the occasional annual pre-pay, meaning SaaS companies are really in the financing business as it takes years before a customer is profitable (compare this to enterprise software companies that get paid upfront for the license fees and are immediately profitable, but become much more difficult to maintain growth)
    • Most SaaS products have retail prices in the sub $1,000/month price range, requiring thousands of paying customers to build a meaningful business (at $1,000/year per customer, 5,000 customers are required to build a $5 million/year business, which is a huge amount of effort)
    • Repeatable customer acquisition at a reasonable cost is always the limiting factor (best practices are that the cost of customer acquisition should be equal to or less than the first year’s revenue e.g. spend $1,000 or less to acquire a customer that pays $1,000 per year — see Why Lead Velocity Rate is the Most Important Metric in SaaS)

    SaaS companies are extremely difficult to get off the ground. Once up-and-running with some modest scale (>$2 million in revenue) and modest burn rate, they are a thing of beauty and typically grow fast for several years.

    What else? What are some other thoughts on the difficulties of getting a SaaS company off the ground?

  • SaaS and Barriers to Entry

    Earlier today Zaid Farooqui tweeted that some of his hedge fund friends think Software-as-a-Service (SaaS) companies are over-valued due to low barriers to entry:

    While I agree that some SaaS companies are priced to perfection due the expectation of massive growth, I don’t believe low barriers to entry plays much of a role. Here are a few thoughts on SaaS and barriers to entry:

    • Once a software product works well, especially at a reasonable price, people are reluctant to switch (look at how many people are still using antiquated Microsoft software)
    • Set-it-and-forget-it SaaS apps are more commonplace than realized, such that credit cards keep getting billed and no one notices unless something goes wrong
    • App marketplaces, like Salesforce.com’s AppExchange, create a network effect of other products that integrate (products like the Kevy integration platform are working to decrease this network effect)
    • Achieving scale in a market results in significant sales and marketing resources that only grows as the company grows
    • If SaaS was susceptible to low barriers to entry, more upstarts would have to have successful businesses in the same market as category leaders

    The hedge fund partners would do well to talk to their B-school classmates that have started SaaS companies and hear first-hand just how difficult it is to get one off the ground.

    SaaS startups encounter a number of barriers to entry, especially in markets with dominate category leaders.

    What else? What are some other thoughts on SaaS and barriers to entry?

  • Gross Margin and SaaS

    One important aspect of Software-as-a-Service (SaaS) that isn’t well understood to first-time entrepreneurs is the role gross margin plays into the business. Gross margin is defined as the percent of revenue left over after the cost of servicing that revenue is taken into account (see SaaS cost of goods sold). For example, with a SaaS company, things like application hosting costs, customer on-boarding costs, customer service costs, and any third-party fees like software licenses or data fees that are required to use the product are included in the calculation.

    Gross margin is also a reflection of how valuable a dollar of revenue is to the business. If the company is an ecommerce business with 20% gross margins (commodity products) vs a SaaS business with 80% gross margins, every additional dollar of revenue for the SaaS business is equivalent to four dollars in the ecommerce business (due to the much higher contribution margin). Margin is one of the main reasons a $10 million revenue company can be more valuable than a $100 million revenue company.

    Early on, a startup shouldn’t worry too much about gross margin. It’s most important to find product/market fit and build a repeatable customer acquisition process. Over time, economies of scale will start to kick in and most SaaS companies will be able to achieve gross margins in the 70-80% range, if not higher. Gross margin, subscription revenue, and great growth opportunities all come together to drive high valuations for SaaS companies.

    Pay attention to gross margin in SaaS companies and understand why it is so important.

    What else? What are some more thoughts on gross margin and SaaS?

  • Notes from the HubSpot S-1 IPO Filing

    HubSpot just filed their S-1 to go public and I’m excited to dive into it. HubSpot has been in the B2B online marketing space slightly longer than Pardot and has awesome co-founders in Brian Halligan and Dharmesh Shah. Dharmesh is truly the king of content marketing with his excellent slide shows, best-selling book Inbound Marketing, and huge OnStartups.com community.

    HubSpot started out as a blogging platform before adding search engine optimization functionality and finally becoming a marketing automation platform. As HubSpot became more focused on marketing automation, Pardot and HubSpot started to see each other more often in the market and had a few partnership discussions before we ultimately decided we were heading down a path of direct competition.

    Here are notes from HubSpot’s S-1 IPO filing:

    • 11,624 customers and 1,900 marketing agency partners (pg. 1)
    • Focused on the mid-market (pg. 1 — this is a change from a few years ago when they were small business focused)
    • Revenue (pg. 2)
      2011 – $28.6 million
      2012 – $51.6 million
      2013 – $77.6 million
      2014 1H – $51.3 million
    • Losses (pg. 2)
      2011 – $24.4 million
      2012 – $18.8 million
      2013 – $34.3 million
      2014 1H – $17.7 million
    • Mid-market defined as companies between 10 and 2,000 employees (pg. 2 — this is a very broad definition of the mid-market)
    • Average revenue per customer is $8,823 per year (pg. 2)
    • 20% of customers outside the U.S. (pg. 4)
    • Professional services revenue (pg. 6)
      2011 – $2.8 million
      2012 – $5.7 million
      2013 – $6.8 million
      2014 1H – $4 million
    • One major risk factor is the inability of customers to create content to make blogging, social media, and inbound marketing in general worthwhile (pg. 10 — regularly writing good content is a serious effort)
    • 719 full-time employees as of June 30, 2014, up from 304 as of December 31, 2011 (pg. 12)
    • Accumulated deficit of $123 million (pg. 39)
    • More than 90,000 individuals with a free or paid Signals account used the Signals product during June 2014 (pg. 47)
    • 88.6% annualized subscription dollar retention rate (pg. 47)
    • $11,334 cost of customer acquisition (pg. 48 — it’s awesome that they are so transparent with their renewal rates and cost of customer acquisition)
    • $7.3 million in cash on hand and negative $22 million in working capital (pg. 60)
    • Great letter from the founders that describes the background of the business and the big vision (pg. 71)
    • Seven core principles of the HubSpot Culture Code (pg. 88)
      We are maniacal about our mission and our metrics.
      We empower every employee, at every level, to “Solve for the Customer”.
      We are radically transparent.
      We give ourselves the autonomy to be awesome.
      We are unreasonably picky about our peers.
      We invest in individual mastery and market value.
      We constantly question the status quo.
    • Venture capitalists own 66.3% (pg. 110)
    • Founders own 13.7% (pg. 110)
    • Co-founder/CEO owns 4.9% (pg. 110)
    • Note: The S-1 made no mention of competitors like Pardot and Marketo, which is unusual for this type of document.

    Overall, I expect this IPO to be very successful due to the excellent team, large market opportunity, current growth rate, and awareness of the company within the online marketing industry. Look for HubSpot to have a market capitalization in excess of $1 billion shortly.

    What else? What are some other thoughts on the HubSpot S-1 IPO filing?

  • Economics of Customer Onboarding Programs

    After talking about The Importance of a Customer Onboarding Program, it’s now time to talk about some of the economics of customer onboarding. Many Software-as-a-Service (SaaS) entrepreneurs don’t realize that customer onboarding costs have to be amortized over some period of time and that they affect the cost of goods sold (here’s a separate primer on SaaS cost of goods sold).

    Let’s say the customer onboarding costs are as follows:

    • 10 hours of manual labor and hand-holding, on average, for each new customer onboarding
    • $60 per hour fully burdened cost for the implementation team
    • $600 in total onboarding costs for each new customer
    • One year amortization period for the customer onboarding costs (this length of time is debatable)
    • $600 total cost, divided by 12 months, equals $50 per month for the first year in additional cost of goods sold

    So, if the SaaS service is $1,000 per month, the gross margin is reduced by 5% per month for the first year due to the onboarding program costs. Of course, customer success and happiness is much more important than gross margin, but it’s important to understand how onboarding programs play into the economics of the business.

    What else? What are some other thoughts on the economics of onboarding programs?