Who This Helps
Hey Junior Analyst. If you're staring at 20 different charts and can't decide what to focus on next, this is for you. The Metrics & Dashboards Basics course shows you how to cut through the noise. Your job is to ship clean analysis with clear recommendations, not to drown in updates.
Mini Case
Maya's team tracked 20 different numbers. Every weekly sync was a debate about which metric mattered. She built a weekly scoreboard focusing on just one primary metric and three supporting ones. In 30 days, her team's decision speed increased by 40% because everyone was looking at the same, clear priorities. No more rabbit holes.
Do This Now (5 Steps)
- Pick Your North Star. From all the numbers you track, choose the single metric that best shows if you're winning. Is it user activation? Revenue? Pick one.
- Define Three Supporting Metrics. These are the key drivers of your North Star. For activation, that could be sign-ups, tutorial completion, and first key action.
- Set Realistic Weekly Targets. Give each supporting metric a simple goal. Aim for a 5% weekly increase in sign-ups, for example.
- Build Your Scoreboard Layout. Dedicate one clear section of your dashboard to just these four metrics and their weekly targets. Keep everything else separate.
- Run Your First Review. This Friday, present only this scoreboard. Ask: "Are we hitting our supporting targets to move the North Star?"
Avoid These Traps
- Don't try to track everything. A dashboard with 20 charts is a decision-making trap, not a tool.
- Don't use vague metrics. "User engagement" is not a clear metric. "Weekly active users" is.
- Don't skip setting weekly targets. A metric without a goal is just a trivia fact.
- Don't bury your scoreboard. It should be the first thing you and your team see.
- Don't change your core metrics every week. Give your priorities at least a month to show results.
Your Win by Friday
Your win is simple: one calm meeting. You'll walk into your weekly sync with a single dashboard view that shows your team's priority, the three things driving it, and whether you're on track. You'll lead the discussion from confusion to a clear, focused recommendation for the next experiment. That's how you go from reporting data to driving decisions. You've got this.