David Cummings on Startups

Category: SaaS

  • 6 SaaS Product Management Tips

    Product management in a Software-as-a-Service (Saas) startup is one of the most important functions, and one of the most difficult — great product managers are hard to find. While product management is hard, there are a number of great resources online. Start with David Cancel’s blog (former head of product at HubSpot) and go from there. Here are six SaaS product management tips I’ve found valuable:

    1. Use dark features to roll functionality out to select accounts
    2. Develop a product management planning process
    3. Follow Covey’s four quadrants when thinking through functionality
    4. Find a daily, weekly, monthly, and quarterly product rhythm
    5. Eliminate the five mistakes first-time product managers make
    6. Perfect is the enemy of good for product management

    SaaS entrepreneurs would do well to embrace product management as a core function and follow these six tips.

    What else? What are some more SaaS product management tips you like?

  • If You Can Get 10 Happy Customers, You Can Get 100

    When talking to entrepreneurs building a new B2B SaaS product, I constantly reiterate that the first major milestone is 10 unaffiliated customers that love the product (see SaaStr on 10 Unaffiliated Customers). Today, it’s easy to put a working product together (minimum viable product or even a minimum respectable product) due to the advances in open source software, cloud computing, and more. It’s always been about building something people want, and it’s even more so now that the technology challenge has been minimized.

    If you can get 10 happy unaffiliated customers, you can get 100. Here’s why:

    • Every new customer represents more testimonials and social proof that can be leveraged to attract more customers
    • 10 customers is enough to find common use cases and patterns that can be codified into a cohesive marketing message that targets similar companies
    • There aren’t 10 completely unique companies in the world — every business has other businesses like it and they are findable
    • The same lead generation process that lead to the first 10 customers — cold calling, PPC, social, etc. — will lead to 10 more and on and on
    • Customers that truly love a product tell their friends and help spread the message through word of mouth

    Getting 10 unaffiliated customers that are passionate about a product is incredibly hard. Once achieved, entrepreneurs have a strong foundation in place and can get to 100 customers using the lessons learned and momentum — that’s part of the beauty of B2B SaaS.

    What else? What are some more thoughts on the idea that if you can get 10 happy customers, you can get to 100?

  • SalesLoft Rainmaker 2016 Conference

    SalesLoft, which has an great platform for increasing qualified appointments and raised a $10M Series A last year, is putting on a conference March 7-9 at the Westin in Atlanta (Disclaimer: I’m an investor). I’ve talked before about the rise of the sales development platform and I’m a big believer in using technology to improve sales and marketing (see Pardot).

    Here are a few details on the Rainmaker 2016 conference:

    • 400+ modern revenue leaders (demand gen, sales development, inside sales)
    • 15+ Partners (6 being announced as part of the sales development cloud ecosystem)
    • Amazing speakers and content
    • Gary Vaynerchuk is the keynote speaker!

    If you’re interested in sales or sales technologies, it’s a can’t-miss event. I hope to see you in Atlanta in March at SalesLoft’s Rainmaker 2016 conference.

  • Arriving at the Pardot Acquisition Price

    One of the more popular questions I get from entrepreneurs that are curious about selling a company is how we arrived at the Pardot acquisition price. My normal response is that we had $10 million in trailing twelve months (TTM) revenue at time of sale and we got 9.5x TTM. Well, since we’re more than three years out from the deal (see 3 Year Anniversary of the Pardot Exit), there’s actually much more to how we arrived at the acquisition price.

    And, as you might expect, arriving at the price of a fast-growing SaaS startup isn’t as logical as you might think.

    The original offer came in at $60 million. Looking at our growth rate (100%/year) and our run-rate ($13M ARR), we said we could wait 12 months, get to $20 million TTM, and then sell for 5-7x. We countered asking for $140 million.

    Not knowing what would happen, but confident we were in a great place in a great market, we felt good about our counter.

    48 hours later they came back and offered us $70 million. Time to play ball. We countered at $120 million.

    48 hours later they came back and offered us $80 million. We countered at $110 million.

    48 hours later they came back and offered us $90 million. We countered at $100 million.

    48 hours later they came back and offered us $95 million. We said no. $100 million is our final offer.

    Then, the final wrinkle emerged: they couldn’t pay $100 million. Even with $210 million in cash on the balance sheet at the time, they had already filed paperwork with the SEC to do a secondary offering, and based on rules as a public company, they’d have to withdraw the offering if they acquired a company for more than a certain percentage of assets. Well, $95 million was the max they could do if we wanted to do a deal now.

    $95 million — take it or leave it.

    We said yes. The deal closed 42 days later.

    Not all acquisition prices are logical. Our deal was driven partly by our revenue, market multiples, market opportunity, and SEC rules. Go figure.

  • Why No Universal API Middleware

    Recently I was talking to an entrepreneur about APIs (ways for apps to communicate with other apps automatically) as he was looking for a way to connect his app, and corresponding customers, with a number of other apps. Only, he couldn’t find anything on the market. Successful startups like MuleSoft and Zapier have numerous integrations but require going through their respective apps to make the connectors work — you can’t readily whitelabel them or use their APIs to connect to other APIs.

    Why hasn’t a universal API middleware emerged? Here are a few ideas:

    • APIs constantly change. Facebook was notorious about constantly breaking their API, yet their motto at the time (“move fast and break things”) made their priority clear. As a vendor connecting to another vendor’s API, it takes on-going resources and money to keep APIs working, which is more expensive than it looks.
    • APIs aren’t as strategic as expected for most cloud-based apps. While companies like Salesforce have amazing APIs, many cloud-based apps don’t prioritize their APIs and thus the API doesn’t have parity with the user interface and bugs don’t get fixed quickly.
    • The long tail is really long. While there are 25-50 apps in the mainstream category (> $100MM ARR), there are hundreds and hundreds more in the near-mainstream category (> $25MM ARR), not counting the thousands more that have at least some scale (> $10M ARR). Outside of the mainstream apps, the next tier of apps, while having a large number of customers, doesn’t have enough overlapping customers with any other non-mainstream apps, making for a limiting number of useful integrations.
    • APIs constantly have problems. Whether it’s an API going down, user authentication expiring, or invalid data with limited error codes, APIs constantly have challenges. This makes for a less-than-ideal end user experience and a challenge to support a large number of APIs at scale.

    Bottom line: APIs are much more complicated than they seem and only a handful are needed to make most customers happy, so vendors just write their own hand-crafted integrations. It doesn’t fulfill the ideals of a universal API middleware platform but it’s good enough for most apps.

    What else? What are some more thoughts on why a universal API middleware hasn’t emerged?

  • Growth Benchmarks for SaaS Startups in the Early Days

    For Software-as-a-Service (SaaS) entrepreneurs in the early days of the multi-year journey, one common question is “are we growing fast enough?” Fast enough is a relative term but there’s been enough success stories to know when something is doing well. At Pardot, year one was building the product (2007), year two we ended at ~$600,000 ARR, year three we ended at ~$2M ARR, year four we ended at ~$4M ARR, and year five we ended at ~$8.5M ARR growing super fast (more Pardot early years revenue info).

    Here are a few growth benchmarks for SaaS startups early on:

    Looking at these, Pardot didn’t meet any of these (high) growth benchmarks. Two big differences: the SaaS markets are much bigger now and these growth benchmarks come from investors with the assumption that startups hitting these numbers will have raised outside capital. Regardless, to build a really big business, serious growth is needed, even in the early days.

    What else? What are some other growth benchmarks for SaaS startups in the early days?

  • Critical Metrics for SaaS Companies

    Ali Rahimtula has a great post up titled Fundraise Like a Pro Using this Internal SaaS Metrics Playbook. As expected, Software-as-a-Service (SaaS) startups have a number of common financial characteristics that make it fairly straightforward to analyze how well the business is doing. At their core, SaaS companies are desirable due to the recurring revenue, high gross margin, and general predictability of the model. Each of these components is reflected in the metrics.

    Here are some of the critical metrics for SaaS companies from the article:

    • MRR over time
      • Beginning of period MRR
      • + New customer MRR
      • + Existing customer expansion MRR
      • – Churned MRR
      • – Downgraded MRR
      • = End of period MRR
      • Growth
    • Customer counts
      • Customers add
      • Customers lost
      • End of period customers
    • Quick ratio
      • (new MRR + expansion MRR) / (cancelled MRR + downgraded MRR)
    • Churn
      • Gross MRR churn (inc. downgrades) ($)
      • Gross MRR churn / previous period MRR (%)
      • Logo churn (#)
      • Logo churn / previous period logo count (%)
      • Net MRR expansion (%)
      • Net MRR churn (%)
      • MRR retention (%)
      • Customer renewal rate (%)
      • Dollar renewal rate (%)
    • Cohort analysis
      • Average revenue per account
      • Price per seat
      • LTV
      • Conversion to paid rate
      • Average contract length
      • Months paid upfront
      • Engagement metrics
      • Customer conversion
      • Sales cycle time

    SaaS entrepreneurs would do well to read Fundraise Like a Pro Using this Internal SaaS Metrics Playbook and get a more detailed understanding of their metrics.

    What else? What are some other critical metrics for SaaS companies?

  • Must-Have vs Nice-to-Have SaaS Products

    One of the biggest considerations in the early days of a new Software-as-a-Service (SaaS) product is the must-have vs nice-to-have question. A must-have product fundamentally alters the way work gets done — either changing existing processes to be 10x better or unlocking new value that wasn’t previously achievable — and once used, companies will never go back. A nice-to-have product provides some value — perhaps being twice as good as doing it by hand or with spreadsheets — yet isn’t valuable enough to compel a critical mass of adopters, and won’t be successful.

    Here are a few thoughts on must-have vs nice-to-have SaaS products:

    • Every spreadsheet is another SaaS app, but every SaaS app isn’t a must-have
    • Apps that unequivocally help companies make more money, like marketing automation, are a must-have
    • Apps that improve productivity must be 10x better than the manual process, not 2x, which results in a nice-to-have
    • Note: this is for products in new categories and greenfield opportunities, not new products in existing categories

    As an entrepreneur, the next time you evaluate an opportunity, consider the must-have vs nice-to-have question — it’s a big one.

    What else? What are some more thoughts on must-have vs nice-to-have SaaS products?

  • Applied Analytics with Business Processes + Big Data + Information Rights

    Georgian Partners has codified an interesting set of ideas around applied analytics as part of their core investing thesis. Generally, the idea is that B2B tech companies that provide a core business process (e.g. CRM, help desk, etc.), with the permission of their users to anonymize the data (information rights), can apply big data analysis to come up with meaningful insights to help customers get more value than they otherwise would from a basic tool. Meaning, the more customers that use a given application, the more valuable the app is to those customers because it can provide insights from across the customer base to any given customer.

    Here are the 11 principles from the applied analytics theory:

    1. Understand the entire process
    2. Identify and prioritize the most valuable insights
    3. Create a dataset that is unique and broad
    4. Raw data is of little or no value
    5. Insights are more valuable the closer they are to being actionable
    6. Leverage the shortage of data scientists to your advantage
    7. Separate analytical insight from how it’s consumed
    8. Inject insights into business processes at the moments of highest impact
    9. It’s not about ‘owning’ the data
    10. Governance and compliance is a foundational discipline
    11. Lead by example

    As a simple example, imagine an email marketing company with 50,000 customers. Using the dataset, the application can proactively notify users when they use words that are likely to trigger spam filters or provide a visual analysis of email open and delivery rates compared to similar customers. By proactively helping customers be more effective in an automated fashion, the company is actually creating a moat around the business that new upstarts will have a hard time duplicating (you can’t duplicate it unless you have a critical mass of customers, and it’s incredibly difficult to achieve that scale).

    For entrepreneurs in B2B tech, they’d do well to read the applied analytics theory.

    What else? What are some more thoughts on applied analytics with business processes, big data, and information rights?

  • 8 Metrics Questions to Raise a Series A

    Glenn Solomon has a good piece up on TechCrunch titled Series B Fundraising For Your Enterprise Startup. Now, outside the venture money centers, the title of the post if more aptly labelled for Series A fundraising than Series B, but the content and metrics are spot on. Here are the eight metrics questions that need to have solid answers to raise a Series A:

    1. What lead volumes are you driving?
    2. How much are you paying for qualified leads?
    3. What’s the cost to acquire a customer?
    4. How long is the sales cycle?
    5. What’s the average selling price of an initial deal?
    6. Do you have evidence of high customer retention and/or account expansion?
    7. How long does it take a sales person to ramp?
    8. What percent are hitting/exceeding quota?

    During the seed stage and beginning part of the early stage, these metrics don’t paint the whole picture due to a lack of sufficient data. As the startup grows, and more customers are signed, these become critical metrics post product/market fit to raise a Series A.

    What else? What are some other metrics questions that need solid answers to raise a Series A?