Product leaders are expected to have ready answers to tough questions:
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- “Are users achieving the full value potential of the product?”
- “How’s the adoption of our newest feature?”
- “Where should we focus our development work and roadmap?”
These questions highlight the massive scope of product management. Product managers have to consider the past, present, and future in order to effectively measure success and fuel iteration and innovation.
Today, answering these questions accurately requires new ways of measuring and analyzing data. Thankfully, AI-assisted analysis gives product teams even more insights to work with.
In order to properly reflect the current product management landscape, we’ve updated our guide, 10 KPIs every product leader needs to know, for 2025. The e-book explores new KPIs, how to measure them, and how they work with legacy metrics. You’ll also find examples of how product leaders are using these new KPIs in the real world.
Here’s a quick preview of three key metrics for product managers.
Predictive customer lifetime value (CLTV): Know where to invest
Traditional CLTV models are calculated using historical averages. As such, it’s a trailing indicator rather than a leading one. Predictive CLTV employs AI to analyze patterns, trends, and behavioral signals to forecast future value.
Predictive CLTV can help you zero in on promising segments of your customer base, allocate resources, and tailor experiences to maximize retention and expansion.
Predictive churn rate: Stop churn before it starts
A churn report tells you who has already left. Predictive churn focuses on finding those likely to churn before they’ve hit the door. AI tools can analyze massive amounts of data—like engagement trends, usage drop-offs, and sentiment data—to create more accurate models of at-risk users.
Predictive churn scoring makes it possible to intervene earlier, prevent attrition, and protect revenue.
Time to value: Turn first-time customers into long-term loyalists
When do your customers have their first moment of delight—or satisfaction, at the very least—with your product? Is it only after an arduous onboarding process? Is it minutes, days, or months?
This KPI is essential for reducing abandonment, improving your onboarding process, and differentiating from your competitors. The faster your product sparks an “aha!” moment, the more likely new customers are to stay with you.
Measure what matters in 2025
Legacy KPIs like Net Promoter Score certainly have their place in product management—but product leaders need to expand their repertoire. This way, teams can better understand past behavior, get a holistic look at present activity, and use data to create accurate models of the future.
10 KPIs every product leader needs to know in 2025 can help teams update—and uplevel—their measurement practices. You’ll find new AI-powered metrics like those detailed above, as well as metrics that measure the impact of AI features on your customer base.
Get the guide to learn about these metrics, along with:
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- Practical definitions and formulas
- The role of legacy metrics in modern analytics
- Real-world examples
- Insights to help you prioritize what matters most
Get your copy of the guide here.
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