David Cummings on Startups

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  • Monthly Sales Quotas

    Historically, sales reps were assigned quarterly quotas and expected to hit their number. Only, as inside sales and web-based sales have grown in popularity, the quota time frame hasn’t changed with it. Today, high velocity sales reps need monthly, not quarterly, quotas.

    Here are a few benefits of monthly sales quotas:

    • Monthly quotas keep the focus on a steady stream of deals, not the more common lumping of deals at the end of the quarter
    • Monthly quotas keep the activity volume high as there’s a need to ensure open opportunities at all stages of the funnel
    • Monthly quotas make it clear where every rep stands, every week, with regard to deals won, not just weighted pipeline, resulting in a more predictable revenue stream

    Entrepreneurs would do well to implement monthly sales quotas and develop a modern sales team.

    What else? What are some more thoughts on monthly sales quotas?

  • 3 Quick Ways to Value SaaS Startups

    Recently an entrepreneur was asking about SaaS valuations for startups. Valuations, especially in startups, are often all over the place as there isn’t a liquid market and the value is generally whatever the most someone is willing to pay. With that said, here are three quick ways to gauge the value of a SaaS startup:

    • 3 – 5x Annual Run Rate – Assume that the terminal valuation for a SaaS company is a multiple of cash flows, and that a true SaaS company can have 50% net margins if sales and marketing were significantly cut, resulting in this simple valuation range.
    • 3 – 5x Annual Run Rate in 12 Months – For startups growing > 50% per year, there’s a big premium and the common way to do it is based on a multiple of the expected run rate 12 months from now (by being forward looking, it takes into account the growth rate).
    • Typical Investor Check Size Times 4 – When raising a round, take the size of check the investor typically writes — say $3 million — and multiple it by four resulting in a post-money valuation of $12 million, reflecting the investor owning 25% of the business. Early institutional investors typically target an ownership of 20 – 30%, so that valuation is driven more so by the check size and target ownership rather than a multiple of run rate.

    Valuations rarely go lower than this and sometimes go much higher for unique circumstances. Valuations, especially in startups, are much less scientific than it appears.

    What else? What are some quick ways to value a SaaS startup?

  • Local, Fast-Growing Million Dollar Revenue SaaS Startups

    Earlier today I was talking with an entrepreneur and the topic of the $1 Million Annual Recurring Revenue Milestone came up. After thinking about it more, I realized I could name 10 Atlanta B2B SaaS startups that had hit this milestone in the last 18 months, and every one is still growing fast. As a community, this bodes well for several reasons:

    • Some small percentage of these startups are going to scale and turn into large companies (hopefully, even an anchor technology company)
    • Look for some really nice exits from this group over the next 3 – 5 years creating more success stories and local wealth
    • More successful startups will train more of the next generation of entrepreneurs contributing to the virtuous cycle
    • More institutional capital will come to the region since traction is one of the key elements for this type of investor

    There’s a great class of local, fast-growing million dollar revenue SaaS startups that are going to make a real impact on the Atlanta startup community — I’m excited for the future.

    What else? What are some more thoughts on the benefits of fast-growing million dollar revenue SaaS startups on a local community?

  • Predictive Sales and Marketing Data Sources

    Continuing with yesterday’s post on Predictive Sales and Marketing Technologies, one of the areas to go deeper is the sources of data that can be used for scoring lead/contacts as well as building out the lookalike companies for targeting. One of the reasons predictive sales and marketing technologies are so good now is that number of quality data sources available is much larger than 10 years ago.

    Here are a few of the predictive sales and marketing data sources:

    • Demographic – Different personas with attributes like job title are valuable when building predictive models
    • Firmographic – Characteristics of the company like size, industry, and location are key data points
    • Social – Significant amounts of publicly available information on social media include location, frequency, interests, and more
    • Technographic – Technologies implemented in a company and on their website (e.g. web server, CMS, marketing automation vendor, etc.) provide a unique profile of the business
    • Digital Behavior – Marketing automation tracks page views, email opens, ebook downloads, and every other digital fingerprint — all useful for understanding the ideal buyer

    Modern data sources combined with machine learning make predictive sales and marketing possible. Look for the quality and quantity of data sources to grow making predictive technologies that much better.

    What else? What are some more data sources for predictive sales and marketing technologies?

  • Predictive Sales and Marketing Technologies

    One of the sales and marketing technologies I’m most excited about (along with account-based sales and marketing) is the whole predictive area. At a simple level, predictive takes existing contacts and opportunities and scores them against a dynamic model based on other contacts and opportunities that became customers. Put another way: find great-fit companies that look like our existing customers so we can target them.

    Account-based sales and marketing platforms (see SalesLoft and Terminus) solve the major problem of running programs in a scalable manner against hundreds (or thousands) of target accounts. Traditional marketing, and sales as the opportunity progresses through the funnel, casts a net, sees what is caught, and then works the qualified leads. Now, as a more modern approach, account-based sales and marketing goes spear fishing and proactively seeks out best-fit accounts based on a number of dimensions. Only, there’s often not an easy way to find and refine best-fit accounts — enter predictive technologies.

    Here are a few thoughts on predictive sales and marketing technologies:

    • As more companies implement account-based sales and marketing platforms, predictive systems become more important to find and analyze best-fit accounts.
    • Predictive sales and marketing systems are clearly in the path of revenue.
    • Machine learning, a subset of artificial intelligence, is now more accessible with the advent of systems like AWS Machine Learning, making predictive systems more powerful.
    • Finding lookalike companies requires technology. Combing through billions of records by hand simply isn’t possible.

    Look for the category of predictive sales and marketing systems to grow fast as the technology crosses the chasm and becomes more well known.

    What else? What are some more thoughts on predictive sales and marketing technologies?

  • Video of the Week: Marc Andreessen on Change, Constraints, and Curiosity

    Last month Stanford GSB hosted Marc Andreessen to talk about Change, Constraints, and Curiosity. Marc is one of my favorite thinkers in the tech and startup world. Enjoy!

    From YouTube: If you want to be successful as a venture capitalist, you need to be ruthlessly open-minded, constantly re-examining your assumptions, shared Andreessen Horowitz Cofounder and Partner Marc Andreessen. Read more leadership lessons from his Stanford GSB View From The Top talk on Tuesday, November 8, 2016: stanford.io/22fGCxZ

  • Inconsistent Lead Flow from Marketing

    One of the challenges I’ve heard multiple times from entrepreneurs is around inconsistent lead flow from marketing. Marketing is running the standard playbook — SEO, PPC, webinars, events, email drips, social — and it’s working with demonstrable value. Only, it’s inconsistent. One month is great and the next month is weak, yet it’s hard to discern why.

    What’s a high performing startup to do about inconsistent lead flow from marketing? Here are a few thoughts:

    • Ask the five whys. Drill down and look for patterns or trends that aren’t visible from the surface. Look for seasonality, major events like an industry tradeshow, or other major influences.
    • Track everything. Implement Pardot and a marketing attribution engine. Track everything that can be tracked.
    • Run an account-based marketing process. Identify best-fit targets. Build a playbook. Execute the process. Iterate.

    Inconsistent lead flow is normal. The key is continuous improvement and refinement.

    What else? What are some more thoughts on inconsistent lead flow from marketing?

  • You Can Never Over Invest in Product

    One of the phrases I’ve heard a couple times in the past week is “you can never over invest in product.” The idea is that once you have product/market fit and a repeatable customer acquisition model, sales and marketing is always out in front of product development. There’s a natural tension between the go to market teams and the product/engineering teams, but often there’s an imbalance. Product development and engineering have nearly infinite economies of scale when combined with a great market.

    Here are a few reasons why you can never over invest in product:

    • Finding great software engineers, UI/UX professionals, and product managers is really hard. No matter how fast you’d like to hire, it always takes longer than expected.
    • Software products have almost no marginal cost and great economies of scale making each incremental prospect signed and customer renewed that much more valuable. Better products make for happier customers.
    • Market opportunities come and go. If there’s a really special opportunity at hand, the opportunity cost of not winning the market is enormous.

    Once entrepreneurs are in the growth stage of the business, you can never over invest in product. An amazing product has so many benefits, and opportunities.

    What else? What are some more thoughts on the idea that you can never over invest in product?

  • Successful Startups Average At Least One Pivot

    Recently I was talking to an entrepreneur about his startup and he lamented that they’re now on their third idea. Idea one failed. Idea two failed. Now, after another pivot, they’re excited about idea three. I paused, looked up, and shared that almost every successful startup I know wasn’t successful with their original idea.

    I’d bet that successful startups average at least one pivot. One of the hottest startups in town is on their third product after two pivots and a tremendous amount of iterating.

    Here are a few ideas why pivots are so common:

    • Unvalidated Ideas – Most entrepreneurs start with an idea and then go looking for a market. Unfortunately, the initial idea is almost always not viable (see customer discovery).
    • Lack of Market Understanding – After jumping into a market with an initial idea, more opportunities start appearing, often related, and it becomes clear there’s a better direction. Time for a pivot.
    • Poor Unit Economics – Many times a product is working and a handful of customers like it. Only, the cost of customer acquisition relative to the price the market will bear don’t match up. Meaning, if it costs thousands of dollars to sign up a customer, and the customer is only willing pay to $50/month, the business model doesn’t work.

    Entrepreneurs would do well to recognize that most successful startups go through a pivot and that it takes time to find an idea that works.

    What else? What are some more thoughts on the idea that successful startups average at least one pivot?

  • Atlanta Startup Village #43

    Tonight is Atlanta Startup Village #43 at the Atlanta Tech Village. The Atlanta Startup Village is the largest monthly gathering of entrepreneurs in the Southeast with 400+ attendees. The cost is free and the energy is high.

    Every month entrepreneurs show their product and ask for help. Here are tonight’s presenters:

    • Partnr: A collaboration platform for the new age of creatives and businesses
    • Unbrokerage – The easiest way to buy business insurance.
    • TrustStamp – Be Known – Be Safe – Be Trusted.
    • YayStack – The best finds from your best friends.
    • ShoutyApp – Create, post, and view streamed events happening anywhere around the world.

    Come see the Tech Village, network with other people in the startup community, and hear entrepreneurs tell their story.