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A technology advantage isn’t enough to build an enduring enterprise SaaS company because at the core, all SaaS software share the same architecture. A relational database stores data and a web site presents the data. This is true for CRM (Salesforce), marketing automation (Marketo), email (Exchange), content management systems (Sharepoint) and so on.

Because SaaS apps use standard databases, engineers can easily transfer the data from one database to another. I’m greatly simplifying here because differences in architecture may exist, but in principle it’s simple to extract, transform and load data from one relational database into another. It may take time to complete the process and users may suffer during the transition, but nevertheless roughly 15%+ of every SaaS company’s customers leave each year to a competitor in this way. From Pardot to Eloqua to Marketo to Silverpop.

The single best content marketing channel is email subscriptions powered by Twitter/social media distribution.

Thirty days ago, I began an experiment with this blog to determine whether email, Twitter or RSS would be the better content marketing channel. My goals with RSS, Twitter and email are two: first to maintain a relationship with a reader longer than a single website visit by creating a communication channel and second to use that marketing channel to drive re-engagement.

The three words roll off the tongue: monthly recurring revenue (MRR). What’s not to love about subscription models? Negative working capital, predictable revenue growth and an average of 13x market cap to annual revenue in the public markets, with some darlings reaching 50x multiples. The list goes on.

But the words recurring revenue belies one small detail. These recurring customers must renew their subscriptions, at which point another three word phrase is uttered: revenue-at-risk, the amount of MRR that might be lost to customers who choose not to re-enlist.

During the past week, I’ve been tapping out letters on a 1921 Underwood portable typewriter that my wife gave me as a present. Sitting in front of it and watching the letter hammers pound ink onto paper reminded me that computer programming is still a very new field. Not 50 years ago, prehistoric programmers punched FORTRAN code on punch cards in this way.

In the past 10 to 15 years has computer programming entered mainstream culture and the number of developers has soared, popularized by the dot com era and the increasing prevalence of computers and mobile phones.

On the day of Android’s five year launch anniversary and my fifth consecutive year of using exclusively Android devices, I switched to a yellow iPhone 5c.

Like a well worn pair of jeans, it’s easy to grow accustomed to a mobile phone OS. Changing into a new pair is always a little uncomfortable at first. In that same way, migrating from Android to I iOS, I discovered the quirks and kinks of each OS:

I’ll never forget the first large tech conference I attended after joining Redpoint. Held in the movie theater in downtown Redwood City, the TechCrunch conference attracted several hundred entrepreneurs, investors and journalists. Not one of whom I knew.

After a handful of conferences and a few awkward quick-name-badge-glance-then-say-hello conversations, I started to recognize faces and became friendly with the conference regulars.

Walking into a room and working it by building a network person by person is an essential part of entrepreneurship (and venture capital). That room might be filled with potential customers to sell, investors to woo, candidates to hire, or in my case startups seeking capital. For many founders and VCs, these networking opportunities occur at least weekly if not almost daily.

In response to analyses published on this blog, a handful of readers have raised the idea of Simpson’s Paradox to me. Because I wasn’t familiar with it, I’ve been researching it and last week, I came across VUDLab’s beautiful website which uses a sexism-in-admission lawsuit against Berkeley to demonstrate the idea.

In 1973, the University of California-Berkeley was sued for sex discrimination. The numbers looked pretty incriminating: the graduate schools had just accepted 44% of male applicants but only 35% of female applicants. When researchers looked at the evidence, though, they uncovered something surprising:

If the data are properly pooled…there is a small but statistically significant bias in favor of women.

We know by heart that half of our marketing dollars are spent improperly. But what’s worse is most products waste half of their chances to deepen a relationship with their customers.

There are two different kinds of email within products: product marketing emails and transactional emails. The first of these marketers optimize continuously and the other is oft forgotten.

Product marketing emails include acquisition campaigns, lifecycle marketing, retention marketing, cross-selling, up-selling and content marketing. Tools like Marketo, Silverpop, MailChimp and others have solved this problem for marketing teams. After all, a startup measures its marketing team by their impact on customer engagement, retention and conversion using email metrics primarily. Consequently, marketers hone and refine and perfect these emails.

As a PM at Google, I carried a laptop to every meeting I went to. I typed notes, jotted down action items, and distributed the minutes of almost each one of my meetings. I stayed organized and tracked my teams’ progress this way.

But, as I learned when I starting working at Redpoint, outside the rainbow bubble of the Googleplex very few people take notes on laptops during meetings. It’s just impolite. People wonder if you’re typing emails (which I often was).

After I wrote a post on six important cohort reports, I received a handful of questions about how to interpret cohort charts effectively. When I review cohort data from companies I work with, I look into three different trends to evaluate a product’s performance.

This is a cohort chart of hypothetical product indicating percentage of monthly active users each week for 12 weeks. There’s great data here and but the amount of data can be overwhelming. Time flows down and right in the chart below.