Julia's Journey – Notes from My Transition

What Is Digital Analytics –Really?

When I first came across the term digital analytics, I pictured something dry and technical: dashboards full of metrics, maybe some code in the background, and very little space for human judgment. But as I began learning more, I discovered something that surprised me: digital analytics isn’t just about numbers. It’s about behavior. Interpretation. Patterns. And stories.

At its core, digital analytics is the practice of understanding what people do in digital environments—and why. Whether it’s a user clicking on a link, abandoning a cart, or spending three seconds on a page and then leaving—it’s all a signal. A fragment of behavior. A clue.

For me, that was the moment it clicked. This isn’t so far from the work I’ve always done.

In sinology and musicology, I learned to interpret silence, structure, context. I studied texts that were never straightforward, and music that had meaning beyond the notes. In digital analytics, I found a new kind of text—a behavioral one.

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From Pageviews to Patterns: How I Think About Digital Data

When I look at a web analytics report today—say, from Google Analytics or Matomo—I don’t just see numbers. I see questions:

• Why are users bouncing from this page so quickly?
• Why do mobile users behave differently than desktop users?
• Why does traffic from one campaign lead to conversions, while another doesn’t?

These are not technical puzzles. They’re interpretive challenges. They require context, hypotheses, and sensitivity to the bigger picture.

In fact, one of the most powerful things I’ve learned is that the data never speaks for itself. It has to be asked. Framed. Read. Just like a historical source, or a philosophical text.

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Not Just for Techies—Digital Analysis Needs Humanists

The misconception that digital analytics is only for developers or marketers is still strong. But the more time I spend in this field, the more I see how crucial the humanities mindset is.

Here’s how I experience it:

• Close reading turns into close data inspection. I look for outliers, patterns, contradictions.
• Historical thinking reminds me that context matters—why a spike happened is more important than that it happened.
• Interpretation helps when metrics conflict, or when user behavior resists simple explanation.
• Narrative is key—because every dashboard needs a story to be understood.

In other words, I approach digital analytics as someone trained to ask not just what, but why—and what else might be going on here?

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Tools Are Learnable—But Meaning Takes Practice

Of course, digital analytics involves tools. But they’re exactly that—tools. They help you observe, measure, organize, and visualize. They don’t generate insight by themselves.

• Google Analytics 4 (GA4) is where I start: it shows how users interact with a website—what pages they visit, where they come from, where they drop off.
• Google Tag Manager helps track specific actions (so-called “events”) like clicking a button or submitting a form, without constantly changing the site’s code.
• Looker Studio (formerly Data Studio) allows you to create interactive dashboards to visualize data—so it can be understood at a glance and shared with others.
• Hotjar gives qualitative insight: it records user sessions or gathers feedback, so you can see how people move through a site, not just where.
• And then there’s SQL, for querying data directly from a database, or basic JavaScript, which sometimes helps when customizing tracking setups.

I’m learning them step by step. And yes, sometimes it’s technical—but never more than I can handle.

The real challenge? It’s not the tools. It’s knowing what you’re looking for—and being honest when the numbers don’t actually answer your question. In that sense, my background in the humanities has given me a head start. I’ve been trained to deal with ambiguity, to resist easy conclusions, and to keep asking better questions.

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A Human Example: Behavior ≠ Intention, But It Still Speaks

Imagine this: A nonprofit launches a new landing page to promote a donation campaign. They get 1,000 visitors in a week—but only five donations. A failure?

Not necessarily.

Look deeper, and you find that 700 of those visitors came from a social media post offering “free downloads.” That post linked to the donation page—but the message didn’t match. Users didn’t come with the intent to donate.

That’s a disconnect between expectation and experience—and digital analytics reveals it. But only if someone is curious enough to ask.

That’s what I love about this field: it’s not just about measuring. It’s about interpreting human behavior in digital space. And the skills I bring from the humanities—context, nuance, critical reading—turn out to be central.

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What’s Next?

In my next post, I’ll share what it’s like to learn these tools from scratch, namely Google Analytics 4.

At the end of the day, I’m not trying to become a web developer. I’m trying to become someone who reads digital behavior—with the same care I once gave to classical texts and musical scores.