When you're working on product as part of a small, closely-knit team, there are always a million things you could be doing better. But your advantage as a startup is the ability to move quickly to validate your hypotheses with results. One of the most powerful ways to accomplish this is simply by limiting the amount of data your team looks at.

"All product initiatives need a single metric and a target goal."
- Steve Cox, former VP of Product KISSmetrics

The idea here breaks down to something pretty basic: As a team, your success is rooted in everyone knowing why they're working on what they're working on, and what they're trying to accomplish. Any time you add a feature or try to improve your product, you need to be able to know what success would look like.

Let's say you're building in-app notifications for your B2B SaaS product. Maybe you want to cut churn. More users or less churn would make your boss happy, but if you can't justify the feature for any better reason, then the motivation and focus of your team are completely out of sync. Success in this context means trying to reduce churn to make your boss happy.

A better way to approach this is to say, we want our 90-day retention rate to go from 28% to 40%. We think by building a notifications feature, we'll be able to hit this target, because we noticed that users who turn their email notifications on during Week 1 are 40% more likely to hit the 90-day mark.

Uniting everyone on product behind a single metric is critical for creating a stickier product. If you've thought deeply about the problem, and justified your hypothesis from the jobs-to-be-done perspective, you can align your team towards working at a singular goal, with a clear reason why.

This idea applies to everything, from optimization projects like increasing landing page sign-ups, to building an entirely new functionality for your product.

Data doesn't make decisions for you. Data informs your decision making.