To Generate More Revenue, Start Generating More Data

Let’s talk about how we use data to make a better product, raise our margins, and generate more revenue.

Here’s the common knowledge: Our product needs an input cycle. We need to be collecting data on our product, analyzing that data, then acting on that data. This produces more data, and the cycle starts all over again.

Here’s the issue: In over 20 years building products and companies, as well as leading and advising others to do the same, I’m constantly running into three problems with that process.

1. We’ll build out part of the input cycle and stop there. Maybe we collect a bunch of data, look at it, get all happy or frustrated, and then forget about it.
2. We’ll build the input cycle with the wrong data, and assure ourselves with false positives that everything is awesome.
3. We’ll follow the input cycle all the way through, but then do the same thing over and over and expect different results.

First Let’s Build an Input Cycle

An input cycle is a little different than a feedback loop and, in fact, can include any and all feedback loops. What we want with our input cycle is to capture every lesson learned about our product at every point in the lifecycle.

That lifecycle starts with what we’re building, and ends a little bit beyond revenue, ideally at recurring revenue. In other words, the final question of this exercise is how do we get existing customers to spend more money on the existing product.

The lessons learned are high-level, and they can come from customer feedback, professional input (mentors, advisors, investors, partners), and most importantly, our day-to-day experience building the product and/or running the company.

Obviously, this works best for a product that already has revenue or at least revenue streams, because revenue is the penultimate metric. From that we can dial back to profit, margins, all the way back to market.

If we’re not at revenue yet, we can use other KPIs, but until we’re talking about actual dollars, any other metric could produce false signs of success. That’s the biggest mistake early startups usually make, and they wind up…