I Spent Three Weeks Obsessing When, In Fact, I Was Measuring the Wrong Thing

I swear the dashboard was mocking me. We started strong, and now here was a big fat ZERO for signups. My stomach dropped every time I refreshed it.

I'd wake up at 3 am doing mental math. If we get five signups next week, could we hit our quarterly target? What if we optimized the landing page? Should I spend my weekend writing SEO content?

The spiral was real. And completely pointless.

The Breaking Point

I was in yet another strategy session with my AI co-pilot (yes, I talk to Claude like a trusted advisor). I'd been asking the same question in different ways for weeks, "What metrics should I track to prove this is working?"

Then Claude asked me, "What decision will this metric help you make?"

I stared at the screen. Signups? I couldn't control signups. Our marketing budget is small. We have limited distribution channels. We are aware that the website is confusing people, and we are working as quickly as possible to address this issue. I'd already had the "we need resources" conversation, and for now, it just isn't going to change. Often, this is the reality of product management, even if we don't discuss it openly.

I was tracking a number that only showed me what I already knew. We have a distribution problem I can't solve.

Since Claude doesn't tire of me, it continued to push and ask questions I might have been avoiding: "Can you actually influence this number with available resources?"

The answer is no.

"Then why are you measuring it?" came next.

Because... leadership wants to see growth? Because that's what product managers *do*? Because I felt like I should be able to solve this somehow?

None of those were good reasons. They were just anxiety dressed up as product management. There are two completely different types of metrics to consider, and I'd been treating them like they were the same thing.

Performance Metrics: What you report to leadership

• Usually about growth, revenue, scale
• Prove the initiative is "working" by traditional standards
• Often tied to resources you don't control

Decision Metrics: What helps you do better work

• About quality, velocity, and learning
• Help you make tomorrow better than today
• Directly tied to things you can actually change

I'd been letting performance metrics (that I couldn't influence) create anxiety while ignoring decision metrics (that could actually help me).

The Reframe

Instead of tracking signups I couldn't generate, I started tracking:

Product Quality

• Are we maintaining uptime across regions?
• How fast are we resolving issues?
• Are users who DO show up having a good experience?

Team Velocity

• Are we shipping what we commit to?
• How long from idea to production?
• Are blockers getting resolved quickly?

Customer Understanding

• What are we learning from the users we have?
• Are we building the right things?
• What patterns are emerging?

These weren't vanity metrics. These were questions that helped me decide what to do next Monday.

The AI Part (As a Tool, Not the Hype)

I know "AI co-pilot" sounds like buzzword bingo. Having my co-pilot set up to understand me and my goals meant it didn't provide answers like those found in every blog post you encounter on frameworks. Instead, it challenged my own assumptions. Every time I said, "But I should be tracking..." it asked, "Why?" Eventually, I ran out of "shoulds" and had to face reality. So now I track two separate things.

For leadership reports:

Simple, combined numbers that show we're keeping the lights on and learning. Active users across products. API usage. Infrastructure costs. Pilots in pipeline. Features shipped.

That's it. One slide. No drama.

For my own decision-making:

Things that help me be a better PM tomorrow than I am today. Cycle velocity. Support ticket patterns. Feature adoption. Customer feedback themes. Team morale signals.

These inform what I work on, not how I feel about myself.

If you're stressing about metrics you can't influence with your current resources, you're not failing at product management. You're just measuring the wrong things.

Ask yourself:

• What decision will this metric help me make?
• Can I actually influence this number?
• Is this measuring my work or circumstances beyond my control?
• What story am I trying to tell, and to whom?

Sometimes, the most brilliant move is admitting certain metrics don't matter with your current constraints.

Performance metrics and decision metrics are often inversely correlated. The numbers that make you *look* busy are rarely the ones that make you *actually* effective.

And that's okay.

Your job isn't to manufacture growth out of thin air. It's about doing excellent work with the resources you have, learning quickly, and making clear-eyed decisions about what's possible.

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