How to avoid being mislead with your data-driven approach

How to avoid being mislead with your data-driven approach - Triple A rule

Data is crucial for any product development process that aim to be customer-centric and human-first data-driven process. Product managers and teams aim to acquire as much data as they can get to learn more about their customers behavior and hence improve the product key outcomes.

When it comes to data, many product teams struggle figuring out the best approach to be data-driven, and to best use their data pipelines and digital footprints. However, being data-driven isn't a simple thing, and require much effort from the team to understand where and how they can structure this data flow.

But, can data-driven be misleading sometimes? In this short article, I'm going to unleash 1 aspect that can be misleading sometimes for any product team and that can lead to false conclusions about product situation. Being falsely data-driven is more dangerous than being non data-driven at all!

Vanity metrics as an example

Every metric we choose to act upon can be a vanity metric, a term coined by Eric Ries, author of The Lean Startup, which means that there could be a metric that tells you nothing about the actual situation. It's not an actionable metric, you cannot take an action or decide major milestones by acting upon.

So, how to avoid misleading vanity metric while choosing the product metric you focus on?

Eric gave some simple steps that you may consider, in order for your metric to feed actual situation. Which I summarized in the term `Triple A rule`

Triple A Rule

The triple A rule is an abbreviation for: Actionable, Accessible, Auditable. We're going to investigate more about each aspect in the following lines.

Actionable

The metrics you decide to measure must have a clear cause-effect relationship. This will allow you to know exactly what to do to if you want to replicate or improve results. You can learn from every action you take.

Accessible

Metrics are nothing if they are not understood by the people whose decision they must influence. As a Product Manager, you need every team who you work with to understand what it means that the churn rate went from 5% to 10%. There are two options to make this happen. Either simplify the language with which you present your results, or train everyone in the technical terms that need to be used.

Auditable

Good metrics are unbiased. Anyone measuring them should be able to come to the same conclusion. This will allow you to build trust from the teams you work. Also, it will limit finger-pointing when things don’t go as expected. An auditable metric should be able to stand the test of real customer discussion: what your customers say validate what your reports do.

I hope that gives you a bit perspective on how to think about your product metric that you're going to act upon, and always aiming for your metrics to be Triple A compliant.

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