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My first major negotiation was a potential advertising agreement between Google and Facebook. I was PM on the social advertising team at the time. There was a call scheduled at 2pm one afternoon, and I had been told that morning about it.

I’m wasn’t an experienced negotiator, so I panicked. I didn’t know how these conversations worked. I called some a few other product managers I knew inside Google, and asked their advice. I downloaded a few eBooks on negotiation and took notes. When 2pm came, I dialed into the call. I’m sure the Facebook team could hear my ragged nerves over the phone.

An entrepreneur last week asked me if bottoms up businesses are more efficient software companies than top down sales processes. Enabled by web and mobile app distribution, the bottoms up software business acquires individual users, small teams and eventually departments. The top down model sells to a C-level executive (CEO, CIO, CFO) and captures the relevant part of the organization through one sales process.

When I first started writing, I wondered how I could make charts like those in the Economist or in the New York Times, the beautifully formatted ones. After some research, I figured out how. And this post explains how you can do it, too.

Many data scientists use a free open-source language called R. It’s a great tool for processing data and I use R to process all the data for this blog. You can download it here. Alternatively, many people use RStudio, an editor which makes R much easier to use. To make these charts, I use a library written by Hadley Wickham called ggplot2. ggplot2 has all kinds of charts: area, line, bar, etc. You can see all of them here

Rumors swirled yesterday that Salesforce, the $40B SaaS behemoth, had been approached by an acquirer. Dan Primack speculated this morning that Oracle and Microsoft are the likely candidates. If Salesforce were to be acquired, the SaaS ecosystem would change substantially.

Looking at the market caps and the balance sheets of the major enterprise acquirers, Microsoft could certainly acquire Salesforce outright in cash. Oracle would likely acquire the business in a cash & stock transaction.

The first SaaS startup started as a packaged software company. After selling floppy disks and CD-ROMs of expense software in computer software stores, the company changed models for the first time, and sold software licenses directly to enterprises. The company went public on this model in 1998. But soon after the crash of 2001, the startup’s market cap totaled only $8M.

The Information reported last week that in 2014, only 11% of tech IPOs in 2014 were profitable when they became publicly traded companies, an all time low stretching back to 1980, when the figure was 88%. This raises the seemingly absurd question, how important is it to be profitable for a startup? After all, growth is the largest determinant of valuation at IPO, not profitability.

Yesterday, I met with a bright, young SaaS entrepreneur who asked me to clarify four key numbers for SaaS companies: bookings, monthly recurring revenue, recognized revenue and cash collections. These four numbers are critical to understanding the health of a SaaS startup, and they can be quite different, so it’s important to have a strong grasp on the distinctions between them.

Let’s consider a hypothetical SaaS startup called RedRocket, which sells software for $12k per year, and asks its customers to pay each quarter. On the 15th day of January, one customer agrees to pay RedRocket $12k for a one year contract. The startup doesn’t sell any more software for the next twelve months. The table above demonstrates the differences in bookings, MRR, revenue and cash.

“Is there a bubble?” is a question that seems to be asked every day. But it’s the wrong question - in fact, it’s an unimportant question. Maybe there is a bubble. Maybe there isn’t. Instead of asking the question, let’s just presume we are in a bubble.

Then, the far more important debate surfaces: given the bubble, how should a team manage a startup differently? If I were to survey entrepreneurs and board members, I presume I would hear something like this list:

In the Innovator’s Dilemma for SaaS Startups, I outlined the path of many software companies, which disrupt incumbents by first serving the small-to-medium business and then move up-market by transitioning to serve larger enterprises with outbound sales teams. I argued this transition is largely due to the more attractive characteristics of larger customers, namely higher sales efficiency and reduced churn rates. This is the “traditional” way of disrupting. But, as Kenny van Zant of Asana and Mike Cannon-Brookes of Atlassian told me, there’s another way, a novel way of building companies that still isn’t very well understood: the Flywheel SaaS Company.

Sales cycles, the time from acquiring a lead to closing an account, vary quite a bit by industry, product type, and price point. But universally speaking for startups, shorter sales cycles are better. Maintaining a short sales cycle is a competitive advantage for several important reasons.

First, faster sales cycles accelerate the discovery of a repeatable sales process. Different sales approaches must be tested: which role to sell to? which pitch (cost or value)? how to handle particular objections? A 45 day sales cycle will find those answers twice as fast as a 90 day sales cycle. Faster and more frequent sales cycles enable quicker experimentation and ultimately a more rapid discovery process to the right initial sales process.