Metric Trees for Digital Analysts

Content in digital analytics tends to be pretty predictable. Juliana pointed this out a while ago - most content in our field focuses on implementation, rarely touching on actual data analysis or how to work with data meaningfully. I see similar patterns.

If you look at what people publish or check out talks at typical conferences, it's heavily weighted toward implementation topics and technical hacks. These days, you'll see tons of content about working with GA4 data in BigQuery - it's the hot new thing, but again, just another implementation topic. On the other end of the spectrum, you get these philosophical, high-level wisdom "let me tell you how the world works" kind of talks of industry veterans.

But there's this huge gap in the middle: how do we actually apply analytics in practice? I understand why this gap exists. It's challenging to write about real analytics work for two main reasons.

First, when you're doing actual analytical work for your company or clients, you usually can't just share it openly. Sure, you can do those high-level celebration case studies (though we all know real projects never work out that neatly). But you can't really dig in and say "here's the specific problem my client faced, here's how we dug through different datasets, here's what we found" - you don't want to put your company or client in an awkward position.

The second reason, I think, is that it's just genuinely difficult. Implementation is essentially an engineering problem - predictable and solvable with enough debugging time. Once you figure it out, you can share the solution and others can apply it. But applying data to business outcomes is significantly harder, unless you're approaching it from that high-level philosophical view where people can interpret it like a horoscope and take what they want from it.

I don't have an easy answer for this problem. However, I've found something interesting in the broader data space - where data engineers and analytics engineers hang out - that might help bridge this gap. Something that could help us bring a better business perspective to our work.

We need to talk about metrics.

Why metric matters. Really matters

I have a complicated history with metrics. They've always made sense to me - kind of like how breathing air makes sense, but not something I spent much time thinking about. I used to try to ignore them, or at least avoid them. When clients would ask "what metrics should we track?", I'd give them the standard list of e-commerce metrics. But I was never really comfortable with that approach.