In this post, you will learn what metrics are, why to use them for your product, the difference between useful and useless metrics, and the three features each metric must have to help you make decisions.
This is the first of a series of posts that will help you understand the importance of product metrics and give you practical examples of how to set them correctly and get the most out of their use.
What are metrics?
A metric is nothing more than a number. It can be in absolute value or %. This number helps you understand how your business/product is performing.
Why set up metrics?
If you don’t measure, you don’t know. All the rest are assumptions and opinions.
You need to set up metrics to understand:
– how your business is performing
– where you need to act to improve the outcomes
– if the actions you have taken to improve the outcomes have an impact
In short, if you are developing a product, metrics are everything. You need them for (almost) any decisions you must make during your product’s entire lifecycle.
To make it even simpler: imagine your metrics as a map to use in a city, you don’t know.
Without the map, finding places you want to visit is more challenging; it takes longer and costs you more.
With the map, everything is easier – you know where to go, how to get there, and where not to go. However, much of the result depends on how you use the map.
Metrics are the map to guide you through the endless decisions you need to make for your products.
The two types of metrics
The useless metrics (also called Vanity Metrics) allow you to be cool with friends. You know those charts that always grow from a point on the bottom left to a point on the top right? Or those that measure the product trend with the number of monthly subscribers? Well, these are useless metrics.
The useful metrics let you know how the product is performing and can be used to track improvements or worsening.
We are only interested in useful metrics. Among the various frameworks you can use, you can take a look at Eric Ries’ 3 A, which outlines three fundamental features for a metric to be useful:
A metric must be Actionable; i.e., it must prove a clear cause-and-effect relationship. If x is growing, then we are approaching the goal y.
A metric must be Accessible. Metrics represent people’s behaviours, so we can’t just group a bunch of numbers, but we must ask ourselves what story that number tells us. Moreover, data must be accessible to everyone in your team.
A metric must be Auditable; i.e., it must use “good” data. It must be credible and reliable. We must always be sure that the data represents real people’s behaviours. We must never mistake taking data on trust without checking if it reflects the real user experience.
A general criterion is that of good sense: a metric must help you make a decision. It must demonstrate a clear cause-and-effect relationship, measure something that keeps always happening equal, must be (almost) always a ratio or a %, never a sum of things that happen.
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