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Recently, I met an exceptional marketer. She described the purpose, strategy and tactics of a marketing department remarkably succinctly. Marketing’s methods can seem intangible. But she explained them simply and elegantly. I drew the chart above based on her vision of marketing’s roadmap.

At the highest level, marketing articulates a compelling narrative. This is step 1.The narrative brings the market forward by contrasting the current state of affairs with a persuasive view of the future. This is a Gap Analysis - a comparison of the current state of affairs to the desired potential.

Founded in 2007, Dropbox epitomizes the freemium go-to-market. Dropbox has grown from 0 to 500 million users over that time period. 2% of those users convert to paid and pay an average of $9.33 per month. 90% of revenue originates through self serve channels - an astounding figure for company that generated more than $1B in revenue last year.

What should be the return on investment of a startup’s cash burn? Fred Wilson posed this question last year in his post Some Thoughts on Burn Rates. In that post, he suggests, and I agree, that a 5x ROI on cash burn is a good target.

How does one calculate ROI? It’s a simple formula:

Cash_Burn_ROI = Revenue_Multiple/Revenue_Pay_Back_in_Years¹

If a business is worth 7x revenues and revenue payback is 14 months, the burn ROI is 6x or 7 / 1.2. If a business is worth 5x revenues and revenue payback is 18 months, the ROI is 3x. Note, I’m using revenue payback, not gross margin payback here.

You’re two or three years into your startup. You have hired a great team and want to retain them. It’s time to consider refreshing their stock options to motivate them to stay longer. How many options should you grant to each employee?

Startups should pay key people market rate to retain them. Otherwise, they may leave the business, lured by the promise of greater compensation elsewhere. Let’s walk through an example.

How should you think about designing your startup’s logo? The mark symbolizes your business. It’s destined to be ubiquitous. Business cards, ads, hoodies, mobile apps, water bottles, even custom sneakers may bear the logo.

In the most recent episode of 99% Invisible, Tom Geismar relates the creation story of the Chase logo. The Chase logo was one of the first abstract corporate marks, one without text. Since then, Geismar has created many iconic marks including Xerox, PBS, Mobil.

20 years ago, a newly minted billionaire worked in his office. Fluorescent lights, a dingy purple carpet, and a CRT monitor resting on a door. Not a desk - those were too expensive - a door supported by 4x4s, brackets and wood screws. In his 60 Minutes profile, he drives around in a Honda Civic. His rationale? “It’s a perfectly good car.”

Much of the conversation today about crypto is about Bitcoin and currency. But that’s myopic. Soon, we will be talking about how crypto will change the software world. In fact, many founders have already started that pursuit. More than 30% of the initial coin offerings (ICO) in 2017 target developers and businesspeople with their products.

When a startup takes form, the first weeks and months and years are spent furiously. The team assembles itself. The lightbulb illuminates. It is formed and reformed again and again as customers supply feedback. Eventually the team hews the right product. The startup raises capital. Then the team returns focus to hiring, evolving the product, and closing customers. However, continuing this way isn’t the path to huge scale. There’s a critical step missing.

This is one of the best pieces of advice I’ve collected about writing.
Put each sentence on a separate line when you write.

When we read, we hear a rhythm.
There is a rhythm to the words.

And when we read, we look to find that rhythm, which pushes us through the end of a sentence, so if I write a really long sentence, and the reader isn’t expecting it – like this one – the reader will find it really hard to follow and understand where I am going.
And if I keep writing really long sentences, I’m going to exhaust the reader, because there’s no place to stop and take a breath and think about what it is that I have written.
Whew!

In SaaS, machine learning has become an essential component to many different products. Whether it’s automating responses to inbound sales queries, identifying expense reports for audit, or surfacing anomalies in data, machine learning improves workflow software. To date, most software imbued with machine learning reduces costs rather than increase revenues.

Why is this the case? Because machine learning is focused on efficiency gains.

First, to train a machine learning model requires large amounts of data. Repetitive workflow processes produce this data. With enough data, a machine learning model can be applied to automate the workflow. For example, it’s straightforward to build machine learning models to automatically answer password reset questions.