Posts

Numbers provide us a certain certainty. With their precision, they offer a sense of black and white, in or out. But, metrics alone aren’t enough. All the quantitative analysis in the world won’t lead me to the next great idea for startup. Those figures can’t create empathy, develop the right culture, or hire the right people. I’ve been thinking about this quite a bit because in both the recent Software Engineering Daily podcast I did with Jeff, and the presentation I gave at Launch Conference, the question of the limits of metrics surfaced.

At my first programming job, I met a colleague who took all his notes in XML. He liked the fact he could structure them well, create programs to search and process them, and display them in many different ways. Most importantly, he future-proofed his notes. Because they were structured, he could transform his notes into any new format. That was my first exposure into the world of productivity hacking.

Demand generation is a critical limiting factor to the growth of many startups. I had the opportunity to moderate a panel of demand generation experts recently at Heavybit, an incubator in San Francisco. I asked the panelists, how well understood is demand generation, considering it is one of the core elements of business needs to sustain its growth? Unanimously, the panel concluded it’s not very well understood.

Startups fail when they run out of money. Startups run out of money when they lack focus. Without a maniacal focus on serving customer needs in a unique way, startups can flounder amidst competition. Without product market fit, the business is challenged to generate strong metrics and faces fundraising challenges. That’s why it’s critical to identify and focus on your startup’s competitive advantage.

most of the time, start up competitive advantages fallen to five categories: product, cost, positioning, distribution and execution.

What is the optimal contract length with for your SaaS startup? Monthly, annual, multiyear? It’s common to see SaaS startups initially price their products on a monthly basis, then add an enterprise “Call Me” plan which hides behind it an annual contract. As the business increases its price point, it may eventually book contracts spanning two, three or even five years.

This pricing pattern has a certain rationale to it. It enables an early-stage software company to rapidly gather feedback. At the outset, when the business prices on a monthly basis, the startup is looking for as much information about the strength of their product market fit as possible.

Why is this ad appearing on this site? This was a frequent questions both advertisers and publishers asked of Google. Behind the scenes, machine learning models match the best ad to the best website, given a set of constraints including budget and the dynamics of the ad auction. To untangle the decision chain across the many different targeting systems to answer the question is a knotty task indeed.

In March, the head of Google research Peter Norvig spoke at MIT. One of the challenges facing computer scientists over the next decade, he said, is debugging the complex machine learning systems that power revolutionary products from photo recognition to speech recognition to machine translation.

2016 has been a volatile year. Major capital investments fell 55% in Q3. The IPO market is a tale of two cities with some companies able to go public and catapult their valuations, but the overall number remains in the single digits. Last, M&A activity seems quite brisk with more than 30 $1B+ billion acquisitions in the last nine months alone. How do all these factors commingle to influence today’s acquisition environment? And how does it compare historically?

Perfection is finally attained not when there is no longer anything to add, but when there is no longer anything to take away.

Antoine de St. Exupery

I remember launching a new filtering feature a Google within the AdSense product. At the time, we had hundreds of thousands of website publishers using our user-interface to accomplish many tasks. They might download reports of their revenue from running AdSense ads, configure ads to match their website’s style, and indicate their preferences for the content of the ads to be shown on their site.

What are the attributes of the ideal SMB SaaS company, an entrepreneur asked me recently. It’s a good question. There are product, marketing, and sales attributes to that ideal company that successful SaaS business have exemplified in the past.

Product

A beautifully designed, simple and elegant product is the first and most important thing.

The product satisfies the top three priority for the software buyer and consequently the software buyer uses a software very frequently. I believe that the next wave of SaaS companies will be centered around workflows, Event Driven SaaS, and this extends to SMB SaaS.

Recently, we examined the comparative efficiency of bottoms-up and top-down businesses. Today, we’ll dig into valuation metrics to see if there’s any systematic bias in the investor community for SMB, Mid-Market and Enterprise SaaS companies.

Using public data, I categorized the 50 or so public companies by ACV at IPO. SMB is less than $10k, Mid-Market is between $10k and $100k, and Enterprise is greater than $100k in average customer value.