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Earlier this year, I read Algorithms to Live By, a book that explains how to use insights from computer science in daily life. One of the rules is the 37% rule. It’s an important rule because it’s broadly applicable. But I had forgotten about it until I listened to the author on the Software Engineering Daily podcast.

The 37% rule says that if you have a decision to make, you should spend 37% of the amount of time you have. This is called exploration period. Seek advice, learn about demands of the role, and meet some candidates.

If you must choose a long term headquarters for your startup, call an executive recruiter who focuses in that city. Ask her about each of the key roles your company will need to hire in the next 2 to 3 years. VP Engineering, VP Product, VP Sales, VP Customer Success, VP Marketing, or VP Operations.

How large is the candidate pool for each search? Which are the hardest searches to complete in this geography? Where are the best talent pools to sift through?

My perception of books was shattered in first grade. A friend and I were arguing about the extinction of dinosaurs. “It’s right here!” I yelled pointing to the book in my hand.“A meteor crashed, cooled the earth, and killed all the dinosaurs.“

My friend countered with a book of his own. Volcanic eruptions had blackened the sky with ash and cooled the earth, he recited. Locked in stalemate, we appealed to a higher authority. Our science teacher told us that the books were just one person’s opinion. No one knows why the dinosaurs died but other species lived. Each of our books were speculation. To this day, scientists still don’t have a unified view.

A little while ago, we were lucky to host Guillaume Cabane at Office Hours in a new format: 30 minute 1-on-1s with a few companies. It was a huge success and a format that we will continue because of all the learning. Guillaume was kind to share some takeaways from the event below.

1. If you’re in B2B SaaS, you most likely have a finite TAM. For the love of ARR, please get the exact list of all accounts in your TAM (at least US). Do some simple math to output a predicted value per account. Then decide which accounts you want to go after, with which channels, at what cost. Start charting your TAM penetration (in volume & separately in value)
2. When doing outbound, lead with value. Never send an email where you focus on you or your product. If your contact to demo rate is below 1%, you’re burning your TAM inefficiently. Top companies with a strong brand, leading with value in an email, often get >10% demo rate on cold emails.
3. Differentiate yourself. Think of your marketing like your product. Would you create the same features as your competitors? Of course not. Your marketing can be a defensible moat: use different words, leverage different channels. In essence, try to be memorable. If you’ve scored your TAM, you now know how much you can invest for each potential account. Be smart about it, maximize the effectiveness of that spend to create an experience unlike your competitor. And if you love your VC, don’t compete head on with paid channels. Paid is an OK channel at best, great if you can get a CAC/LTV < 1 (rare in SaaS).

Guillaume has an exquisitely tuned acumen for how to build scalable marketing systems. Watching him advise startups on how to build their machines, I noticed how much of an innovative thinker he is. The notes above echo it.

I’ve written before about the Jacob’s Ladder of Fundraising. The Jacob’s Ladder is a children’s toy that flips over, and it’s a great metaphor for the seed market. Seed rounds are rapidly approaching and now often equal to the sizes of Series As just five years ago. The chart above shows the mean round size in the US across.

As the Jacob’s Ladder flips, a series of important strategic questions arise in the market.

At Saastr, Jason and I discussed the role of private equity in SaaS on stage as a potential acquisition path for SaaS startups. Private equity hasn’t been a common exit route for venture backed startups in the past. But that’s changing.

The chart above depicts the total disclosed value of US venture-backed SaaS startups which have been acquired by PE firms since 2010. The aggregate value has grown from zero to about $13B over that time period.

Wing.vc published the Enterprise Tech 30 last week. It’s a coaches poll of the top enterprise startups broken into early, mid and growth stage. Congratulations to all the companies and in particular, the 8 Redpoint companies on the list: Mattermost, Cockroach Labs, LaunchDarkly, Tray.io, AppZen, Snowflake, Hashicorp and Stripe.

Coaches polls are fun because they provide a different perspective on the market. I analyzed the data set and added a few columns to it to see if there are any trends.

In Rethinking Customer Churn Rate & LTV/CAC, Thibaud Clement illuminates a counter-intuitive concept about churn. The faster you increase your growth rate (acceleration rate), the higher the churn rate.

Consider the same startup under two scenarios: one in which the acceleration rate is 50% and one in which the acceleration rate is 0%. In the 50% scenario, churn will be 67% higher. A surprising result.

Why does this happen? Because the odds of churn decrease with time, particularly for products with monthly billing. If a business acquires many customers in one month, a big chunk of the customer base is at the point of highest churn risk.

When I shared the Redpoint SaaS Metrics Template, I wrote about the difficulty I had identifying key engineering metrics. I was grateful for all the responses from leaders at many startups to share their expertise. I’ve updated the template with a few metrics.

Reliability - percent of application requests that load. 1 minus reliability is the percentage downtime. This measures the durability of the application.

Availability - percent of application requests that load within a certain latency. 99% uptime means for 99% of seconds within a month, the application responded to requests within 5 seconds. Each company should define the acceptable latency. This measures the responsiveness of the application.

When we published the results of the freemium survey earlier this year, we noticed respondents targeting the enterprise observed higher net dollar retention and lower churn than those startups targeting other segments. I wondered if we could observe any other patterns about enterprise businesses, so I produced this analysis of public companies with ACVs (annual contract values) of $100k or greater.

In the series of charts that follow, the red bars indicate the value of the metric during the year of IPO. And the blue dashed line is the median.