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At SaaStr earlier this year, I spoke about the huge potential of machine learning in SaaS. In that talk, I broke down some of the advances in ML that might be useful for software companies. In the discussion that ensued, I stressed the importance of not letting the technology obfuscate the value proposition of the software. Yes, ML is a huge step forward, but it’s not enough by itself. In fact, it likely isn’t the most challenging part of building a disruptive product.

After a startup establishes product market fit, scaling demand generation becomes the the next major challenge. Doubling or tripling ARR each year for several consecutive years is not easy. The best marketers create a demand generation portfolio. There are four axes to measure this portfolio: scale of investment, sophistication, breadth and potential.

At the outset, a startup may rely on a single channel of customer acquisition. But over time, in order to achieve larger and larger bookings, the company must diversify. Diversification prevents channel saturation risk. As spend in one channel grows, the cost of customer acquisition rises to untenable rates. Diversification also mitigates channel concentration risk. A change in terms of service of a dominant distribution platform might challenge the business’ existence.

A friend recently asked, “Which path is better for SaaS startups? SMB to mid-market to enterprise or straight to enterprise?” It’s a key strategic question for many founders building software companies.

Startups that initially target small to medium businesses benefit from several key advantages. First, these businesses are faster to revenue. Simpler products satisfy SMBs, so startups can begin to charge smaller customers much sooner than enterprise customers in a product development lifecycle.

At a recent board meeting, a CEO said, “This experiment will cost $250,000 to run. After three months, we will know whether our new go-to-market strategy is viable.” There’s a brilliance this type of framing. By quantifying the cost of the experiment, the CEO frames company prioritization as asset allocation.

What is asset allocation? Asset allocation is a strategy that aims to balance risk and reward by apportioning a startup’s assets according to a company’s goals and risk tolerance. (I’m borrowing heavily from Investopedia, and recasting the definition for startups).

Intel’s Business Plan

Every once in a while, I receive a FedEx from an entrepreneur I haven’t met. Inevitably, this mail contains a modern rarity - a business plan. Ten to twenty pages describing the idea, the genesis, the business model, the team and its structure, customer acquisition strategy, sales model and other key details of the business. A plan for how to start a company, and a defense of the idea.

There’s no quicker way to lose a user or buyer of your software than to lose their trust. The software didn’t save my data. The database suffered corruption. The website is down frequently. Data integrity is a challenge every company storing data faces. Machine learning SaaS startups face another trust risk – one introduced by probability.

When Nate Silver forecasted the successful election of Barack Obama in 2008 with nearly 100% accuracy across districts, probability theory shined. The real world matched the likely predictions. Fast forward to eight years later, and the new President wasn’t the projected winner.

Cloudera is the second of the Hadoop players to go public. Last week, the company filed their S-1 and revealed a massive business. Cloudera generated $261M in revenue, counts 500 clients and grows those accounts by 43% annually. 18% of their customers run Cloudera software in the cloud, a surprisingly large number.

Hortonworks is Cloudera’s chief competitor. In the following charts, we’ll compare the two businesses. These analyses compare the two companies based on the year they went public, marked 0 in the charts. Negative years are years before IPO.

The most satisfying compliment the reader can pay this to tell me they feel personally addressed. Think of your favorite authors and see if that isn’t precisely one of the things that engages you, and often at first without noticing it. A good conversation is the only human equivalent.

Christopher Hitchens, a famous journalist, wrote this in his book Mortality. After writing nearly 1000 blog posts, I have to agree.

Over the last year in particular, Revenue Ops is a term that’s gaining some mindshare in the SaaS world. Revenue operations teams combine marketing operations and sales operations into one team. Yesterday, I heard time a further refinement of this idea: Customer Operations.

As one SaaS executive described to me, marketing operations teams are the engines of the marketing team. The creative marketing functions produce the fuel – the campaigns, the positioning, the art. The engine, marketing ops teams disseminate these assets. They measure their performance and optimize customer acquisition to maximize return on investment.

When I first met Jen Grant, Looker’s CMO, she told me a story from early days of Box, where she was SVP of Marketing. Jen spoke about the importance of creating tension in the marketing message.

Aaron Levie, Box’s CEO and founder, spoke at conferences about the future of collaboration. His message: Box will transform the way employees work. But if you had visited www.box.net, you would have found another positioning for the company. A very simple one. Box replaces FTP.