Product Success: 13 Metrics That Measure What Matters

Success is easy to recognize, but harder to define. In product management, it’s tempting to measure success by the adoption rate or an increase in revenue. While those are great, they don’t always tell the full story.

Think of a movie that wins at the box office but fades from memory. Or a fitness app that gains users fast, only to lose them within months. These are products that succeeded briefly but failed to stick.

I like to think of product success as a pattern. It’s about delivering consistent value to users, adapting when things shift, and repeating the process. To get there, you need to track the right metrics, have a clear strategy, and understand what success really looks like.

In this article, I’ll go beyond standard product analytics to break down how to choose the right metrics to measure the success of a new product, the key elements that drive long-term success, and practical ways to measure what actually matters.

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What Is Product Success?

Product success is the outcome of a product consistently delivering value — to users, the business, and often the broader market. Although that is the part of the puzzle, it’s not just about shipping something on time or hitting short-term product goals. It’s about creating something that works, lasts, and evolves with its users.

At its core, performance criteria for a product answer one question: Did the product do what it was supposed to do for the people it was built for? As Mario Queiroz, the CPO at Hinge Health, says on The Product Podcast: 

“For the user, it's all about the outcomes. Are they relieving their pain? They pay for that.”

An example of product success

Consider Duolingo. It didn’t become the world’s most-used language learning app just by having a great product launch strategy or a fun UI. Its success came from a deep understanding of what makes people stick with learning: short lessons, gamified streaks, and push notifications that feel more like a friend’s nudge than an app reminder.

The product team behind it didn’t stop at downloads or signups. They optimized for long-term engagement, behavior change, and user delight because that’s what success meant for them.

How to evaluate product success

Product success can look different across industries or stages, but it usually involves:

• Clear and sustained product adoption and engagement

• Real impact on business goals like revenue growth, user retention, or market share

• Strong product-market fit and user satisfaction

• The ability to evolve without losing users along the way

• A well-aligned cross-functional team driving toward the North Star Metric

What makes this tricky is that success isn’t static. A metric that defined success last quarter might not be enough for the next quarterly roadmap. This is why teams need to define success clearly, revisit it often, and stay close to both data and real user behavior.

13 Product Success Metrics That Actually Matter

If you're wondering how to measure success of a new product — or how to measure product success over time — start with the right metrics. 

These 13 success metrics for a product go beyond surface-level indicators and help you understand how to evaluate product performance in real, meaningful terms. Whether you're optimizing onboarding, tracking growth, or aligning with business goals, these metrics give you a clear view of what’s working and what needs attention.

1. Time to first value (TTFV)

Time to First Value measures how quickly a user experiences the core value of your product after signing up. For example, if a user signs up at 2:00 PM and creates their first design at 2:15 PM, the TTFV is 15 minutes. You calculate it by subtracting the time of signup from the time of the first value event.

This metric is especially useful during onboarding improvements, early product launches, or when refining trial experiences. If users don’t reach value fast, they lose interest, even if the product is excellent. Shortening TTFV increases the likelihood of long-term engagement and decreases early drop-off.

2. Feature adoption depth

Not all feature usage is equal. This metric tracks how deeply users engage with high-value features, the ones that drive real outcomes. It’s calculated by dividing the number of users actively using key features by the total number of active users, and multiplying by 100.

For example, if only 25% of your users are using the reporting dashboard in a SaaS analytics tool, that tells a very different story than if 80% are. This metric helps you focus not just on adoption—but on meaningful, outcome-driven use. It’s especially relevant when launching new features, revisiting product-market fit, or refining your value proposition.

3. Retention by cohort

Cohort-based user retention looks at how long specific groups of users stay engaged with your product. 

A typical formula would be: (number of users retained in a given period / number of users in the cohort at start) × 100. For instance, if 100 users signed up in January and 30 are still active in April, your 3-month retention rate for that cohort is 30%.

It’s a powerful way to uncover what’s working and what’s not. You can break cohorts down by signup date, acquisition channel, onboarding path, or even plan type to see how different user groups behave. It’s most useful during growth, onboarding changes, or iterative testing with product pricing and packaging.

4. Customer expansion rate

Customer Expansion Rate tells you how much your existing customers grow over time in terms of revenue, usage, or both. It’s calculated by subtracting the revenue at the start of a period from the revenue at the end (for the same customer group), dividing by the starting revenue, and multiplying by 100.

Let’s say existing customers brought in $100K in January and $130K in March. The expansion rate is 30%. 

Tracking this helps you understand whether customers are finding more value and investing deeper into your product. It’s crucial for SaaS analytics, usage-based monetization models, or any product that benefits from upselling and cross-selling.

5. Product usage diversity

This metric looks at how broadly users are engaging with different parts of your product. It’s not just about how much they use it, but how many different use cases or modules they’re using. You might track the average number of features used per user or calculate the percentage of users engaging with three or more core features.

It’s especially helpful in mature products with multiple functionalities. If most users stick to one feature, you may be missing an opportunity to expand usage or improve discoverability. High diversity often correlates with greater product stickiness and lower churn risk.

6. North Star Metric (NSM)

Your North Star Metric is the one measure that best reflects the long-term value your product delivers to users. It’s not one-size-fits-all — it should be specific to your product vision and product strategy. For example, Spotify uses “minutes listened,” Airbnb tracks “nights booked,” and Slack looks at “messages sent per team.”

Unlike vanity metrics, your NSM aligns the entire product leadership on what success truly looks like. It gives direction to roadmap decisions, team priorities, and long-term strategy. Defining the right NSM is essential for any team looking to scale with clarity and purpose.

7. Adoption velocity

Adoption Velocity measures how quickly new features, modules, or product changes are picked up by users. While there’s no fixed formula, it usually involves tracking the percentage of active users engaging with a new feature over time — say, within 7, 14, or 30 days after launch.

This metric helps you understand whether your releases are resonating. If product adoption is slow, it could be a sign of poor discoverability, unclear value, or usability issues. It’s especially relevant for Agile product management teams that ship often and want to measure the actual impact of their releases.

8. Support ticket volume per active user

This metric tracks how many support requests are generated per active user in a given period. For example, if you receive 500 support tickets in a month from 5,000 active users, the ratio is 0.1 tickets per user.

It’s a useful counterbalance to engagement metrics. A high ticket volume per user can indicate friction points in the product experience — bugs, confusing workflows, or gaps in onboarding. A low number suggests the product is intuitive and self-serve, which is often a strong sign of success.

9. Referral rate

Referral Rate measures how often users actively refer your product to others. It’s typically calculated as the percentage of users who refer at least one new user over a set period. For instance, if 200 of 5,000 users refer someone in a month, the referral rate is 4%.

This metric signals genuine satisfaction and emotional investment. If people are recommending your product, they believe in it. It’s especially valuable in products that rely on network effects, community building, or organic growth loops.

10. Goal completion rate

This metric tracks how often users successfully complete the key actions your product is designed to help them achieve. For example, in a product management tool, that might mean creating and assigning a task. In a meditation app, it could be finishing a session.

You calculate it by dividing the number of successful completions by the number of users who attempted the task. A low completion rate can point to friction or unclear UX, while a high rate is a strong indicator that your product is delivering value as intended.

11. Active usage stickiness (DAU/MAU ratio)

Stickiness measures how often users return by comparing daily active users (DAU) to monthly active users (MAU). For example, if you have 6,000 DAUs and 24,000 MAUs, your stickiness is 25%.

This is a quick way to gauge how habit-forming your product is. A higher ratio means users come back regularly, suggesting strong engagement and value. This metric is especially important for products that rely on frequent interaction, like messaging apps, task managers, or social platforms.

12. Product-qualified leads (PQLs)

PQLs are users who’ve demonstrated enough engagement or value realization to be considered sales-ready. The exact criteria depend on your product, but often include things like completing onboarding, inviting team members, or integrating with other tools.

This metric is vital in product-led growth environments where user behavior drives the funnel. It connects product usage with business impact and helps align product, marketing, and Product-led Sales around a shared definition of a high-potential customer.

13. User sentiment by feature

Instead of collecting generic satisfaction scores, this key metric tracks how users feel about specific features or areas of the product. You can gather this through targeted surveys, feedback tagging, or analyzing qualitative responses.

Tracking sentiment at the feature level helps you identify which parts of the product users love, which they find frustrating, and where improvements could drive the biggest impact. It’s especially valuable for roadmap planning and product prioritization that deepen product success.

How to choose the right product success metrics

“The most important metrics are specific to your goals. For us, these include if our customers are successful with this product, are we driving value... How much faster can customers go through their workflows? How much time do they save?”

— Frank te Pas, Head of Product at Enterprise, on The Product Podcast

Choosing the right product success metrics is about choosing what to pay attention to. And in product work, what you pay attention to shapes everything. Roadmap decisions. Team focus. How you talk about progress. How you justify investment.

If you track the wrong things — like vanity metrics, irrelevant engagement stats, or outdated OKRs — you risk building a product that looks good on dashboards but underperforms in the real world. Worse, you mislead your product team into optimizing for something that doesn’t matter.

Here’s how to get it right.

How to define success metrics for a product

What success looks like in the first six months is very different from what it looks like two years in. Early on, you’re trying to prove value and find traction, so you’re focusing on product launch metrics. Later, you’re optimizing for retention, expansion, or strategic growth, so success metrics for a product look a bit different. It’s imperative that your success metrics align with where you are in the product lifecycle.

For early-stage products, prioritize:

• Time to First Value (TTFV)

• Goal Completion Rate

• Retention by Cohort

• North Star Metric

For growth-stage or maturing products, focus on:

• Customer Expansion Rate

• Product Usage Diversity

• Adoption Velocity

• Active Usage Stickiness

Avoid tracking too many metrics at once. It splits focus. Choose 3–5 metrics that reflect your current priorities and review them every quarter. Don’t be afraid to replace them as the product evolves.

Map metrics to business and team goals

Metrics shouldn’t live in isolation. Ask: What decisions will this metric help us make? If the answer isn’t clear, it probably doesn’t belong in your success tracking.

If your business is prioritizing expansion revenue, you need metrics like Customer Expansion Rate and PQLs. If your CEO is pushing user retention and loyalty, cohort analysis and user sentiment are far more useful than raw usage.

Involve your cross-functional team when selecting metrics. Product, design, engineering, and customer success all see different parts of the puzzle. The best success metrics are the ones that create shared focus, not siloed targets.

Don’t ignore qualitative data

Product success isn’t only about numbers. Pair your metrics with qualitative insight — interviews, open feedback, sales conversations. If a number moves, but you don’t understand why, you’re flying blind.

Tracking user sentiment by feature, for example, helps you interpret shifts in product adoption or usage patterns. High support ticket volume tells you where users struggle, but sentiment tells you how they feel about it.

Combining quantitative and qualitative data gives you a richer, more accurate picture of success.

Watch out for product management success metric traps

Here are some common mistakes product teams fall into when measuring success:

• Measuring activity instead of outcomes (e.g., number of clicks vs. task completion)

• Over-focusing on acquisition when churn is the real issue

• Relying too heavily on one metric, like DAU, without supporting context

• Setting metric targets without knowing what success should look like

A metric is only valuable if it helps you make better product decisions. If it’s not actionable, it’s noise.

What Makes a Product Successful: Beyond Metrics

Metrics are a mirror. They reflect what’s happening, but they don’t cause it. Product success is the result of systems, habits, and decisions that happen long before the dashboard lights up.

Here are a few foundations that matter just as much — if not more — than the metrics themselves.

Define success collaboratively and early

You can’t hit a target no one understands. Before you build, launch, or iterate, get clear on what success actually looks like — for users, the business, and the team. This isn’t just about setting OKRs. It’s about aligning on what matters most and saying it out loud.

Bring in cross-functional partners early. Engineers, designers, marketers, and customer-facing teams all shape the product. If they don’t know what success looks like, they’ll optimize for different things and that slows everything down.

Make space for real feedback (then act on it)

Successful products evolve in response to real-world signals. That means carving out space for qualitative feedback and treating it as seriously as you treat Product-led growth metrics. Pay attention to what users say, where they hesitate, and why they churn, even if the numbers still look good.

More importantly, build the habit of closing the feedback loop. When users take time to share feedback and nothing changes, trust erodes. When they see improvements based on their input, trust grows. And trust is what fuels retention, advocacy, and expansion.

Focus on momentum, not just milestones

It’s easy to obsess over the big win: the launch, the KPI spike, the funding round. But product success is often quiet. It’s found in small decisions, tight iterations, user stories, and habits that build momentum over time.

Create a cadence of learning. Run tight experiments. Celebrate small improvements. Teams that treat progress as a process—not a one-time achievement—tend to build more resilient, adaptive products.

Invest in team clarity and communication

Even great metrics won’t help if your team is confused, misaligned, or burned out. The best product outcomes come from teams that share context, make tradeoffs transparently, and feel ownership of the result.

This means clearly articulating the “why” behind decisions, looping people in early, and keeping communication open across functions. If people understand what they’re solving for (and why), it’s much easier to move in the same direction.

Rethinking Product Success: It’s More Than Just Metrics

Product success isn’t a dashboard. It’s an outcome, or multiple outcomes. It’s earned through clarity, alignment, and relentless focus on delivering real value. The best product teams create the conditions where those metrics mean something.

So define success on your own terms. Choose the metrics that matter now, but be ready to evolve them. Listen more than you assume. Build with purpose. And remember: the most successful products are trusted, loved, and built to last. That’s product success worth chasing.

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