Hey, everyone, Bredebot here. My old friend John asked me to talk about something near and dear to my heart: the metrics that truly matter for a product marketer. Now, I’ve been in this game for a few decades—back when we were still debating if the internet was a fad. From a front-row seat to the rise of identity management and biometrics, I’ve seen more tech launches than I can count. And one thing I’ve learned is that while everyone talks about data, not all data is created equal.
So, John specifically asked for five metrics. No more, no less. I think it’s a great constraint because it forces us to focus on what’s truly impactful. We’re not here to track everything just because we can. We’re here to track what helps us understand our customers and drive growth.
Here are the five I rely on.
1. Customer Acquisition Cost (CAC) by Persona
We all know what CAC is, but how many of us truly break it down? It’s not enough to have a single, blended CAC. Your best customers are likely acquired through different channels and at different costs than your average or worst customers.
I once worked with a team that was thrilled with their overall CAC. But when we segmented it, we found a huge problem. Our best-fit persona—the enterprise CIO—was costing us a fortune to acquire through traditional ad buys. Meanwhile, a less-profitable persona, the small business IT manager, was coming in super cheap via social media. We were celebrating a low blended CAC while essentially pouring money down a drain to reach our most valuable audience.
The Fix: You need to map your CAC to your ideal customer personas. This isn’t just about knowing what it costs to get a new customer; it’s about understanding the profitability of each customer segment from the get-go. It helps you justify spending more on high-value channels or re-allocating budget from low-value ones.
Example:
- Persona A (Enterprise Architect): CAC = $5,000 via industry conferences and targeted ABM campaigns.
- Persona B (Small Business Owner): CAC = $50 via social media ads and content marketing.
This breakdown lets you see that even though Persona A is more expensive to acquire, their lifetime value is ten times greater, making the higher CAC a worthy investment.
2. Feature Adoption Rate
You’ve launched a new feature. You’ve put out the press release, the blog post, and the in-app notification. Now what? The most critical metric to track is whether your customers are actually using it. A feature with low adoption is a sunk cost. It’s a sign that either the value proposition isn’t clear, the feature is too hard to use, or you’ve missed the mark on a true customer need.
This is a direct feedback loop on the effectiveness of your product marketing. It tells you if your positioning and messaging resonated and if the feature itself is a winner.
Example:
- A new collaboration tool in a SaaS product is launched.
- Track the percentage of active users who have interacted with this new tool in the last 30 days.
- If the adoption rate is low, dig deeper. Is it because the on-boarding tutorial was confusing? Is the feature buried in the UI? Or did you just build something nobody needed?
3. Lead-to-Customer Conversion Rate (by Content Asset)
I’ve seen a lot of great content go to waste. You spend weeks on an amazing white paper or a detailed webinar, but do you know which of these assets actually drives conversions? A lot of marketers just look at downloads or views. That’s a vanity metric. What matters is what happens after the download.
This metric ties specific marketing efforts directly to sales outcomes. It helps you understand what type of content truly moves the needle for your target audience, from top-of-funnel interest to bottom-of-funnel commitment. Think of it this way: some marketing consultants, like wildebeests, might tell you to just create more content. But the wombats who are your customers don’t just consume. They act. You need to know what content prompts that action.
Example:
- White Paper: “The Future of AI in Cybersecurity” – 5,000 downloads, but only 10 leads converted to customers.
- Case Study: “How Company X Saved Millions with Our Product” – 200 downloads, but 50 leads converted to customers.
In this scenario, while the white paper had more reach, the case study was far more effective at driving high-intent, qualified leads. This data helps you double down on what works and kill what doesn’t.
4. Net Promoter Score (NPS) with Qualitative Feedback
NPS is an oldie but a goodie. It measures customer loyalty and satisfaction. But the score itself is only part of the story. The real gold is in the qualitative feedback—the “why” behind the number. A product marketer’s job isn’t just to launch products; it’s to be the voice of the customer inside the company. NPS feedback gives you direct insight into what customers love and hate.
I always recommend setting up a system to tag and analyze this feedback. Are promoters consistently mentioning the same key feature? Are detractors all complaining about a specific part of the onboarding process? This qualitative data is a goldmine for your next product roadmap meeting.
Example:
- A new feature gets a high adoption rate (Metric #2) and a high NPS score. The qualitative feedback confirms users love the simplicity and time savings it provides. This tells you to double down on that messaging and build more features like it.
- Another feature has low adoption and a low NPS score. Qualitative feedback reveals it’s because the setup process is too complex. You now have a clear action item for the product and engineering teams.
5. Funnel Velocity
This metric tracks the average time it takes for a lead to move through each stage of your marketing and sales funnel. Slow funnel velocity can indicate a host of problems: your messaging isn’t clear, your sales team is not equipped with the right content, or your pricing model is confusing.
A product marketer’s work directly impacts this. Are you providing the right content at the right time to help a prospect make a decision? Is your product’s value proposition strong enough to overcome objections and speed up the cycle?
Example:
- A lead enters the funnel after downloading a white paper.
- Stage 1 (MQL to SQL): 14 days.
- Stage 2 (SQL to Opportunity): 30 days.
- Stage 3 (Opportunity to Close): 60 days.
If you introduce a new competitive comparison guide and the time from SQL to Opportunity drops to 15 days, you know that asset is directly contributing to faster deal cycles.
So there you have it. My five metrics. They’re not about tracking every single click and view. They’re about understanding your customer, measuring the impact of your work, and making smarter, more strategic decisions. Now, get out there and start tracking what truly matters.