The Setup
Every company I worked at had the same problem: marketing dashboards that nobody looked at.
They’d exist in some corner of Google Analytics or a Looker Studio report that was built by an analyst who left 6 months ago. Leadership would ask “is marketing working?” and the marketing team would scramble to pull numbers that told a story. The real problem wasn’t the data — the data existed. The problem was translation.
Marketing tracked impressions, clicks, engagement rates. Leadership wanted to know: are we making money? The two groups were speaking different languages, and the dashboard was supposed to be the translator. It never was.
The Build
I started with the question, not the data.
I’d sit with the founder or VP and ask: “What decisions do you make based on marketing data?” Not “what do you want to track” — that produces wishlists. “What decisions do you make” — that produces the 4–5 numbers that actually matter.
Then I’d build backward from those decisions to the metrics that inform them.
A typical dashboard had three layers:
The leadership view (one page). Revenue attributed to marketing. Cost per acquisition. Pipeline value. Email list growth rate. That’s it. 30 seconds and you’re done.
The marketing team view (page two). Campaign performance. Content metrics. Channel comparisons. The stuff that helps the team understand what’s working.
The diagnostic view (hidden by default). The detailed stuff you only dig into when something’s broken. Attribution models. Cohort analysis. The things that make analysts feel important.
Most dashboards try to show everything on one screen. My approach: show leadership what they need in 30 seconds. Let marketing dig deeper on page 2. Hide the diagnostic layer until someone needs to troubleshoot.
The Mess
The hardest part was getting people to agree on what revenue means.
At a SaaS company with a freemium model, is a free-to-paid conversion a marketing win or a product win? When someone finds you through SEO, downloads the free version, uses it for 6 months, then upgrades after a feature email — who gets credit?
The attribution arguments were endless.
I learned to sidestep them: “It doesn’t matter who gets credit. It matters whether the number is going up.”
I built dashboards that tracked trends, not attribution. Leadership could see: email list is growing, free-to-paid rate is increasing, cost per acquisition is decreasing. That was enough to make decisions. The attribution nerds could argue in their own spreadsheets.
The Result
The dashboards I built at StellarWP became the standard reporting format for the entire marketing org.
The leadership team went from asking “what’s marketing doing?” to opening the dashboard themselves on Monday morning. The marketing team went from dreading monthly reports to feeling confident that their work was visible.
The most satisfying metric: dashboard open rate. If leadership opens the dashboard voluntarily, it’s working. If they only look when you force them into a meeting, it’s not.
The Takeaway
A dashboard nobody looks at is worse than no dashboard at all. It creates the illusion of measurement while hiding the fact that nobody’s actually using data to decide anything.
The dashboard isn’t about collecting data. It’s about translating what you know into what matters. Every metric on that page should answer one question: “Does this help me make a better decision?”
How It’s Built
Google Looker Studio (formerly Data Studio), connected to Google Analytics, CRM data, and email platform APIs. Some builds used Notion dashboards for smaller teams.
Cost: $0 (all free tools). The expensive part is thinking, not tooling.
Playbook: Website Audit Checklist | Playbook: 90-Day Marketing Roadmap Generator