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Tell me three numbers and I can estimate the amount of capital your startup will need to raise. Which figures are those? The startups’ revenue target, the average revenue per customer and the average cost of customer acquisition.

For example, I’d like to estimate the cost for my SaaS startup to reach $100M in annual recurring revenue (ARR). My typical customer pays $25k average contract value (ACV) and my cost of customer acquisition (CAC) is $29k. I estimate a 14 month payback, which is the average according to the 2016 PacCrest survey. To calculate CAC, we take the 14 months of payback divide by 12 months and multiply by the ACV. To reach $100M requires 4,000 customers. Each of the 4,000 customers cost on average $29k. This math implies spending $116M to acquire those customers.

During every person’s working life, there comes a time when you have a question that could be answered by having access to the right data. Unfortunately, the time and effort required to find that data, package it the right way, and send it to an analytics or business intelligence tool present a formidable obstacle to answering the question. Two years ago, Redpoint partnered with Dremio to solve this problem. This morning, after an enormous amount of hard work from the team, the company has made its product publicly available.

Bloomberg published a post this weekend called San Francisco’s VC Boom is Over. The article pointed to the seeming collapse in the amount of venture capital raised by San Francisco startups relative to other regions. The slowing of venture investment more broadly across the US serves as a backdrop to San Francisco’s particularly strong correction. I was curious about the drivers of these trends, so I ran my own analysis.

I’ve asked many VPs of Sales the same question. Which is the best book on the fundamentals of selling? Almost unequivocally, they respond, “Miller-Heiman.” The New Strategic Selling is an updated version of the original Strategic Selling, which was published in 1988, and describes the key activities of successful sales people. I resonated with two concepts in the book: the 4 Seller Response Modes and the authors’ recommendations on how to prioritize a salesperson’s time.

At some point in the life of your company, you may consider selling the business. Every acquisition process might run a little bit differently, but these are some of the patterns that I have observed after about nine years in the venture business, and also having evaluated a handful of acquisitions when I was at Google.

There are two key constituencies within the buyer: the business owner and corporate development. Corporate development is often the first point of contact, and while they are a critical component of executing the transaction, it is ultimately the business owner who will champion the acquisition through the approval process.

Michael Porter wrote the seminal book on strategy in the early 1980s. Called Competitive Strategy, I think it should be required for anyone starting a company. Strategy is a seemingly murky amorphous intangible concept, but Porter brilliantly prescribes the five questions strategy should answer. What are the answers for your business?

What is your distinctive value proposition? This distinctive value proposition comprises three key parts. Which customers will you serve? Which needs of those customers will you fulfill better than the competition? How will you position and price your proposition (premium/commodity)? This can be best answered by relative pricing. Amazon’s consumer value proposition is simple: the most selection at the best prices delivered fastest to all internet consumers in the US.

A friend died this week. It’s the first time I’ve lost a friend of a similar age. I don’t often see the fragility of life first hand, but this is one of those moments.

I’ve felt many different emotions after I received the news: despair, grief, fear. The one I’m currently experiencing, though, is gratitude. And I hope that’s the feeling that persists. You will be missed, my friend.

One typical Friday morning in 2004, I walked into a government building and headed to work. I was a junior Java engineer and part of a hired team building an internal system for a government agency. We were a few days behind on schedule, and a technical issue arose. During the morning team meeting, we made a plan to refactor a small key part of the codebase - an effort that should have taken just the morning. And I made a classic mistake.

In the Wide Lens, Dartmouth Entrepreneurship professor Ron Adner explores the risks associated with innovation. Execution risk is the obvious one. Then there’s co-innovation risk, what might be called chained technology risk. For example, to build a new ML focused microchip, a startup relies on the chip fabrication plant to develop 7nm equipment. But the most interesting of the three is Adoption Chain Risk.

Adoption Chain Risk is “the extent to which partners will need to adopt your innovation before end consumers have a chance to assess the full value proposition.” Adoption Chain Risk applies the idea of a supply chain to innovation.

In software, we’ve moved from a world where a customer buys a piece of software to run on their own infrastructure, to a world where a customer pays a vendor to run software on the vendor’s infrastructure. With machine learning, we may see another evolution of this. Machine learning startups create models based on data provided by customers. Should customers be compensated for their contribution?

Unlike the first wave of SaaS software, machine learning startups benefit from the data their customers share with them. Many times, machine learning startups create one global machine learning model that is used across the customer base. Each marginal customer provides additional data that refines the model.