Everything you never knew about the making of money
Mechanics of Revenue is a master class that runs alongside the news cycle. There’s a RevOps lens, but most of what we write starts with something we’ve been observing, sometimes a specific business decision getting attention, sometimes a broader pattern in how a market or an industry is behaving, then we explain the revenue mechanics at play.
After years of building and operating revenue systems across many businesses, we can usually recognize what a company is doing and why, even when the company itself describes the move differently. The same penchant for observation and connection applies to wider economic signals, where the story being told about an industry diverts attention from the incentives actually shaping it. This more straightforward read on cause and effect is the kind of insight that isn’t widely circulated on today’s tailored platforms.
Our article on Clay’s pricing change is a good example. Most of the commentary came from the customer’s perspective: the new model is confusing, it costs more, here’s how it affects my team. We explained the decision from Clay’s side. They had just raised another round of funding, which meant the product had to start monetizing at a much higher rate, so they restructured pricing to extract more value from each customer. Facebook made a similar decision years ago when it replaced the chronological timeline with an algorithmic feed. The change frustrated users, but controlling what people see is what allows Facebook to serve ads and decide what spreads, and the business got more profitable because of it. Decisions like these look arbitrary or even hostile from the outside but they make sense once you can see the revenue model underneath.
Other pieces widen the aperture. The Attribution Casino is about an entire category of marketing software, and why fifteen years of attribution tools have left advertisers more confused than ever. Basically the platforms reporting the data also sell the advertising. Clean attribution would help you spend less money with them, so the fog isn’t a flaw in the system, it’s the product the system is built to sell.
Anti-Anti-AI is about the AI discourse and why the loudest voices cluster at the poles, while the people actually using these tools every day, and getting practical value out of them, get drowned out by a format that rewards conflict over nuance.
Both pieces examine the forces underneath what’s visible and once you understand those, the moves and countermoves on the surface make a lot more sense.
The news tells you what a company did and what its communications team wants you to think about it. We explain why the company did it, what it expects to gain, and over what time frame. Reading enough of these explanations changes how you see business decisions in general, including your own. Our hope is that the newsletter builds your awareness of how revenue actually gets produced, so you can look at your own company and see the same mechanics at work.
