Interpreting User Data the Right Way 🧐

Hi there, it’s Aneesha here 🔥!

How are you doing?

I am going to talk about a specific subject in Product Analytics today — interpreting user data. And no, this isn't even about making the right decisions just yet – that's a whole other conversation. 🙅🏻‍♂️

The interpretation part in itself is something to focus on keenly and work on.

Talking to several aspiring PMs and folks at entry-level roles in product management, I have found that data interpretation is something almost 95% of them struggle with.

Of those, most found it difficult to interpret user data. They’d always say there’s only so much I can see, having left so many inferences behind 🤷.

So, what exactly is this user data? 🤔

Think of it as any information about how people interact with your product, website, or app.

For example, website clicks, how often people buy things, or how many times they open your app. This data might be right there in tools like Google Analytics or Firebase, or it might require some digging and cleaning from a bigger data set.

Either way, once you have it, you need to interpret it. This basically means taking all that raw information and turning it into something useful – like finding patterns in what users are doing.

Why are they clicking that button? Why aren't they using a certain feature? And most importantly, how do their actions impact your product?

When I started out, I’d make the silliest findings 💀. I'd go like, “Oh yeah, there are most opens in the evening!” 🤦🏼‍♀️. Makes me realize, now that I look back, how much practicing this skill is so important. You should too!

Define your Mission 🎯 

You’re now probably wondering “So how do I get this right, Aneesha?”