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15 essential metrics for product success

You’ve got ambitious goals for your digital product—but how do you know if you’re getting closer to them or not? The answers are in your data. In this article, we’ll explore the 15 most essential metrics to track when you want to build better products.

Key takeaways

Your customers are the core of your business. But it’s not always easy to know if they’re happy or where they’re experiencing friction in your product.

Thankfully, product analytics tools let you gather data you can use to understand them. By measuring user behavior, you can uncover important clues about what users need—and get a heads-up when there’s a problem.

However, the challenge with analytics is that there’s an ocean of data you could be looking at—so where do you even start?

By tracking the 15 essential metrics we cover in this article, you can:

  • Use product metrics to track all five stages of the customer journey

  • See how you’re moving towards key business goals

  • Cross-reference your product metrics with qualitative data and customer feedback to learn the reasons behind behavior trends

With the insights you find in your metrics, you’ll be well-informed when it comes to making important product development decisions. Let’s dive in!

What are product metrics?

Product metrics are numerical indicators of how users are interacting with your app or website. They let you measure user actions—like how many users access your app each day—so you can track growth, identify issues and measure the impact of changes.

Without product metrics, you’d have no reliable way to find out how well your product is performing. Sure, you could survey customers—but this would be extremely time-consuming and totally impractical for day-to-day research.

Product metrics allow you to:

  • Make data-driven decisions on which aspects of the app you should improve next

  • Optimize your marketing campaigns to attract audience segments who spend most in your product

  • Get an edge on the competition while improving your own processes

Why are product metrics important?

In order to make decisions about your product, you need to answer questions about how it’s performing. For example:

  • Is your user base increasing or decreasing over time?

  • How much does it cost to acquire a paying customer?

  • Which features are most helpful to users?

Product metrics allow you to answer these questions (and more) so you can make informed decisions about where to focus resources.

They also help you understand how users interact with product features, so you can improve the user experience and develop new revenue generation strategies.

Finally, product metrics can inform your marketing strategies. For example, by understanding usage patterns, you can appeal to different audiences by building marketing campaigns around the features that appeal to them the most.

Product metrics vs. key performance indicators

Are product metrics and KPIs the same thing? Not exactly.

Product metrics provide data about what’s happening inside your digital product, such as how customers interact with it and their feedback. For example, the number of active users, engagement metrics, retention rate and churn are all product metrics. These metrics can be leveraged to make data-driven decisions specifically related to your product or to better understand changes made to the product, such as a new feature release.

Are product metrics and KPIs the same thing? Not exactly. They’re closely related, with one major difference:

Key performance metrics are used to assess a business’s performance across a range of departments. They could include, for example, the number of clicks your ads get (a marketing metric), company profits (a financial metric) or the number of people using your app each day (a product management KPI).

With this in mind, product metrics can be just one of many KPIs your company uses to assess its performance.

Leveraging product metrics to make data-driven decisions

Product metrics can help you make countless important decisions. Common ones include:

  • Which features do we develop next? Most product teams have a long list of potential features they could potentially develop. By learning what features users interact with most, they can decide which feature additions or updates would make more impact.

  • Which accounts need more support? Product metrics can reveal which users are showing signs of frustration or using the product less frequently. Customer success teams can then reach out to those accounts offering support.

  • How to improve retention? Product metrics can reveal how often users churn, which audience segments churn more and when trends change. With these insights, companies can develop strategies to improve retention, then track their impact.

  • Which parts of the funnel should we improve? By performing a funnel analysis, you can identify at which step users commonly drop off on the way to a conversion. You can then focus UX design and conversion optimization resources on improving that step of the funnel.

  • What audiences should we target? Product metrics can reveal which audiences spend more or stay subscribed for longer, so you can build strategies to attract similar customers.

Examples: Making data-driven decisions with product metrics

Using product metrics to make informed decisions helps teams drive better outcomes for the business. Here are a few examples of how to leverage product metrics for a positive business impact:

  • Deciding which features to remove or change. Your product is cluttered, and user feedback suggests it’s becoming hard to navigate. But which features should you remove or relocate? By checking feature usage metrics, you can identify the least popular features and make an informed decision about removing them.

  • Deciding which audience segments to focus on. Your product caters to a wide range of audience groups with diverse needs. So how do you decide which ones to prioritize? By calculating the customer lifetime value (LTV) of each segment, you can determine which audience segment is more profitable. From there, you can make an informed decision about whether to prioritize or target that audience more.

Categories of product metrics

Product metrics can be organized into five categories:

  1. Business metrics are concerned with revenue generation. For example, they might track the average purchase value of customers using an e-commerce app.

  2. Acquisition metrics focus on how the company acquires users and customers. For example, the amount of traffic a website receives.
  3. Activation metrics measure how many visitors become paying customers, for example by upgrading from a free plan to a paid one.
  4. Engagement and adoption metrics measure how users engage with the product. For example, how often they use a specific feature after its launch.
  5. Retention metrics track how long customers stay with the company before leaving. This is particularly useful for businesses that generate revenue through a subscription pricing model.

The 15 product metrics every product manager should consider tracking in 2023

There are many product metrics you could be tracking, which is why we compiled a list of the top 15 we think are the most important to consider.

The list below goes into detail about what each metric is and how to calculate it. It’s important to note that the metrics you track depend on what type of information is most relevant to understanding the performance of your product.

Business metrics

1. Average revenue per customer (ARPC)

ARPC shows you how much each individual customer spends on average. This is a useful metric to track when you’re trying to:

  • Measure the impact of introducing add-ons, upgrades and one-off purchases

  • Decide whether you should focus on selling to smaller numbers of higher-paying customers

  • Compare the revenue generated by different customer segments

  • Calculate what impact a change in churn rate would have on revenue generation

How to measure ARPC

You measure ARPC by dividing the total amount of revenue you generate over a set time period (e.g a month or year) by the number of customers* you have on paid subscriptions.

ARPC = total revenue / total number of users

*For B2B situations where there is one customer but multiple users, you might track the number of users on paid subscriptions to calculate average revenue per user.

2. Monthly recurring revenue (MRR)

For companies who charge via subscription, tracking the revenue generated each month helps spot trends and measure growth. You can also use MRR to make predictions about annual revenue and profits.

How to calculate MRR

Calculate MRR by adding up the total number of customers and multiplying it by your average revenue per customer.

This gets a little complex if you have multiple pricing tiers. In this case, it usually makes sense to calculate the MRR for each tier separately, then add the figures together to get your total MRR.

MRR = total users x average revenue per user

3. Customer lifespan

Customer lifespan is the average length of time that a customer continues doing business with you.

This is a helpful metric for predicting growth and revenue and understanding how satisfied customers are with your service.

How to calculate customer lifespan

You calculate customer lifespan by taking the total length of time customers stay active/subscribed, then divide it by the total number of customers. So if you have 10 customers and they stay a total of 200 months, your average customer lifespan is 10 months.

Customer lifespan = total of customer lifespans / number of customers

4. Customer lifetime value (LTV)

LTV measures how much revenue, on average, each customer brings to your company before they eventually stop using your service.

This is a useful metric for calculating which audience segments are most profitable to target. For example:

  • Users from target audience A have a cost per acquisition of $200 and their LTV is $1,000

  • Users from target audience B have a cost per acquisition of $400 and their LTV is $2,000

Even though target audience B costs more to market to, they bring in much more revenue over their “lifetime” as a customer.

How to calculate LTV

There are a few different formulas for calculating LTV. The most straightforward way is to multiply the average revenue per customer by the average customer lifetime:

LTV = average revenue per customer x average customer lifetime

Acquisition metrics

5. Cost per acquisition (CPA)

Cost per acquisition measures the amount you have to spend to acquire a single customer. It typically measures how much companies spend via marketing and sales campaigns.

By comparing CPA with average lifetime value (LTV), you can quickly see how profitable a company is. For example, if your CPA is $60 and your LTV is $70, you make $10 profit per customer.

How to measure CPA

To measure CPA, you divide your total marketing spend by the number of customers achieved (over a set time period).

CPA = total cost of marketing / total number of customers acquired

6. New signups

This metric measures the number of people who create an account with your product. Depending on your business model, they may not be a paying customer yet—but they’ve taken an important step toward becoming one.

Tracking new signups can help you assess the efficiency of your marketing campaigns and funnels. It also helps you predict how your revenue would change if you were to convert more users to paying customers.

How to measure new signups

There’s no math equation here—new signups is a figure you’ll get from your product analytics tool for a set time period.

When extracting these metrics from your tool, you might find it helpful to get new signup figures for each acquisition channel. You can then compare them to determine which channel is the most effective.

Activation metrics

7. Activation rate

Activation rate measures the amount of people who have signed up to your app that become active users. It’s helpful when you want to measure the effectiveness of your onboarding process.

However, it’s up to you to define what “activation action” makes someone an active user. For many companies, it’s a user who has interacted with a core feature of the product—but you will define your own “activation action.”

How to calculate activation rate

Activation rate is shown as a percentage, and it’s calculated by dividing active users by the total number of users that signed up.

Activation rate = (active users / total signups) x 100

8. Time to activate (TTA)

Time to activate shows how long on average it takes newly signed-up users to perform your chosen “activation action.”

This is important to measure because it shows how effectively your onboarding process drives new users toward activation.

How to calculate time to activate

Time to activate is calculated by your product analytics tool. It looks at how long all users take to perform your key “activation action” after signing up, then calculates the average time.

Time to activate = total time taken to activate all users / Total number of active users

9. Signup-to-subscriber rate

Signup-to-subscriber rate measures the percentage of signed-up users who become paid subscribers.

It's a helpful metric for determining your free trial's effectiveness at convincing users to sign up. If your signup-to-subscriber rate is low, you may need to do more to demonstrate the value of your app.

How to calculate signup-to-subscriber rate

Signup-to-subscriber rate is shown as a percentage, and it’s calculated by dividing your paid subscribers by the total number of users that signed up.

Signup-to-subscriber rate = (paid subscribers / total signups) x 100

Product engagement and adoption metrics

10. Feature adoption rate

Feature adoption rate measures what percentage of your active users are interacting with a specific feature.

Tracking this metric can help you discover whether a new or existing feature is important to users. The more popular a feature is, the more it can help you drive strategies for acquisition, retention and revenue generation.

How to calculate feature adoption rate

To calculate feature adoption, you need to setup an interaction with the feature as an event in your product analytics tool.

Feature adoption rate = (number of users interacting with the feature / total number of active users) x 100

11. Daily active users (DAU)

DAU shows you how many active users you have each day. What defines an “active user” is up to you—it could mean a user logging in, playing a game for five minutes or using a specific feature.

Tracking DAU helps you understand the product’s overall popularity and user engagement. You can also track weekly active users (WAU) and monthly active users (MAU) to see engagement over a longer time period.

How to calculate DAU

To calculate DAU, you need to set your product analytics tool to track a specific event that makes someone an active user. Your tool will then track how many users complete the action each day.

12. Stickiness (DAU/MAU)

Stickiness calculates what ratio of your users return to the app regularly. If an app is “sticky,” it offers regular value or enjoyment to users, enough to become part of their habits.

This is particularly important if your app is designed to get regular engagement from users—for example, a gaming app that offers in-game purchases.

How to calculate stickiness

You calculate stickiness by dividing your DAU by your MAU. The higher the percentage, the stickier your product is— 100% means your users visit every day, while 50% means they visit half of the days of each month.

Stickiness = (daily active users / monthly active users) x 100

13. Net Promoter Score (NPS)

Your NPS is an indirect metric—it’s not measured by the customer’s actions, but by asking them a question: “How likely from 1-10 would you be to recommend [the product] to a friend or colleague?”

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Tracking NPS scores can show how customer sentiment changes over time, across different parts of your product, or between audience segments.

How to track NPS

You’ll need a voice of the customer (VoC) tool or a platform that’s capable of presenting users with surveys. Set your tool to present the survey at key touchpoints in your product, then analyze the aggregated scores later.

Retention metrics

14. Churn rate

Churn rate is a measure of how many users leave your product over a set time period. In industries like SaaS, churn is the biggest threat to a business’s success—so it’s vital to keep an eye on it.

The tricky question here is what counts as users leaving. If you operate with a paid monthly subscription, it’s easiest to define churn based on users who cancel their subscriptions.

How to calculate churn rate

Let’s imagine you want to know your churn rate over the last month.

Start with the number of users you had at the start of the month and subtract the numbers you had at the end of the month. Take the result and divide it by the number of users you had at the start of the month. The end result is the percentage of customers who churned.

Churn = (users at start of month – users at end of month) / users at start of month x 100

15. Retention rate

Retention rate is the direct inverse of churn rate; it’s a measure of how good your app is at keeping customers over a set period.

It’s shown as a percentage that represents how many of your subscribers or active users stick around.

How to calculate retention rate

Take the number of subscribed users* you had at the end of the time period and divide it by the number of subscribed users you had at the start. Multiply the result by 100.

Retention rate = (subscribers at end of period / subscribers at the start) x 100

*If you don’t have paid subscriptions, substitute this for active users.

How to choose the right product metrics

With so many different product metrics, it’s hard to identify which ones you should be tracking. Use the four steps below for guidance when choosing which product management KPIs to track.

1. Set goals

Identify your most important business goals. The most important goal will be different for every business—for example, a SaaS business might decide that its goal is to increase customer satisfaction.

2. Consider what signals would measure progress

Your next step is to reverse engineer how you would see progress toward your objectives. How might success or failure manifest itself in user behavior or attitudes?

Signals can be anything from user actions (e.g., clicking on a button, submitting a form) to market indicators (e.g., sales numbers, customer satisfaction ratings).

For example, if your goal were to increase customer satisfaction, this might be signaled by:

  • Customers leaving positive feedback on review websites

  • Customers recommending the product to friends

  • Customers staying subscribed for a long time

  • Customers/users engaging with the product more

  • Customers willing to pay more for the product

3. Choose metrics that align with these signals

While some of the signals above can’t be measured in the product, others would be reflected in product metrics.

For example, customer satisfaction could be measured directly by surveying customers in the app using VoC tools.

The company could also measure indirect signals of customer satisfaction by tracking:

  • Retention + churn rates — an increase in customer satisfaction will usually mean customers stay subscribed longer

  • Referral rates — if the company has a referral program, it will see higher numbers of referrals from satisfied customers

  • Stickiness — if active users return to the product more regularly, this suggests increased customer satisfaction.

4. Choose metrics that track the results of your initiatives

In trying to pursue a primary goal—like increasing customer satisfaction—the company would launch initiatives to help drive results.

The company could track metrics to measure the impact of these campaigns. For example:

  • Tracking new customer acquisitions. By better targeting best-fit audiences, the company could bring in customers who are more likely to be satisfied by the product. Here the company might measure acquisition and adoption rates from key audience segments.

  • Creating and promoting product tutorials. Helping users learn to use the product could improve customer satisfaction. In this case, the company could track feature usage rates for its tutorials and support materials.

Which product metrics should you avoid?

First and foremost, don’t try to track every vaguely relevant metric. You’ll end up drowning in data when it comes to analysis.

To stick with a manageable load of metrics, make sure the ones you do follow are actionable, useful and relevant to your goals. Don’t fall into the trap of following metrics that simply make you feel good—otherwise known as “vanity metrics.”

Avoid vanity metrics

Vanity metrics seem impressive but don’t necessarily impact meaningful goals in any way.

For example, tracking the total number of users signed up for an app can potentially give you some impressive figures. But this figure can be misleading because many users signup for an app and never use it again.

Other common product metrics that are often considered vanity metrics include:

  • App downloads. Getting high numbers of app downloads sounds great—but it doesn’t mean much if users aren’t actually installing and using your app. Instead, look at the signup rate and signup-to-subscriber rate.

  • Page views. This figure can be misleading because web pages with high views can still be unsuccessful at converting visitors or keeping them engaged. Get more context on page views by viewing time on page and page conversions.

Product metrics framework for growth

Product teams often use one of several frameworks to choose which metrics they track:

1. The HEART framework focuses on metrics that track the user’s experience and overall happiness, rather than the sales funnel performance.

Created by Google’s UX team, it divides business goals into five categories that can be tracked via metrics: happiness, engagement, adaption, retention and task completion.

2. GAME is a framework for identifying and evaluating metrics to track. It suggests following a four-step process:

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  • Identify business and user GOALS

  • Create a list of user ACTIONS

  • Convert the list into quantifiable METRICS

  • EVALUATE each metric

3. AARRR or Pirate Metrics is a framework commonly used by startups and product-focused businesses. We’ll take a closer look at this one below.

AARRR Pirate metrics framework: What it is and how it works

Pirate Metrics is a set of essential metrics for tracking growth. It was developed by Dave McClure in 2007 to help business owners optimize their sales funnels.

🏴‍☠️Obviously, “AARRR” is the noise that pirates make—but it also represents each key stage of the customer journey:

  • Acquisition

  • Activation

  • Retention

  • Referral

  • Revenue

Most of these metrics can be tracked directly with product analytics (arguably with the exception of referrals, which are more complex to track).

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Who is the AARRR pirate metrics framework for?

The pirate metrics framework is ideal for startups and businesses that serve customers through the internet and digital products. This includes:

  • Software as a Service (SaaS) businesses

  • E-commerce

  • Mobile gaming

  • Mobile apps

The pirate metrics framework works well for digital-focused businesses because they can (theoretically) track every interaction that customers have with their businesses.

In comparison, a physical shop can’t track how long every customer spends in their shop or what products they look at.

How does the pirate metrics framework work?

The AARRR pirate metrics framework allows you to take a customer-centric approach to assess and improve your business. Rather than simply looking at expenses, revenue and profit, AARRR lets you track how customers progress through the journey you have built for them.

For example, let’s say your company is seeing a drop in profits. This could happen for several reasons:

  • Not enough new customers are finding your company (an acquisition problem)

  • Lots of people are finding your company, but they aren’t becoming paid customers (an activation problem)

  • You have lots of paid customers, but they don’t stay customers for long (a retention problem)

By looking at pirate metrics, you can easily find areas for improvement and track the impact of changes to your product or strategy.


RARRA is a re-imagining of the original pirate metrics framework. It uses the same metrics but changes the order in which businesses should prioritize them.

The RARRA framework was created with mobile apps in mind and outlines the key goals that mobile app creators should remember:

  • Retention: Create an app that users want to keep returning to

  • Activation: Help users see the value of your app quickly

  • Referral: Encourage users to tell friends about your app

  • Revenue: Look for ways to monetize the app

  • Acquisition: Invest in marketing and acquisition campaigns to scale up your user base

The idea is that app owners should only scale up their acquisition once the app is generating revenue. In highly competitive markets, acquisition is expensive—so spending money to bring users to an app that doesn’t make money is a bad strategy.

Framework considerations for product-led growth (PLG)

Product-led growth (PLG) is an approach to business that puts the product itself at the heart of the company.

Instead of relying on the sales team to make sales and the support team to drive customer satisfaction (for example), the product itself is the primary driver of these growth activities.

PLG companies generally focus on the metrics we listed in this article, with a couple of important additions:

  • North star metric. Many companies focus on a single metric that most strongly represents growth. For example, a free mobile gaming app that makes money from in-app purchases might focus on customer LTV as its north star metric.

  • Time to value. PLG companies are often operating in highly competitive spaces, so they need users to adopt their product quickly. Time to value (TTV) measures how quickly users complete a key action that convinces them the product is useful or enjoyable.

How to calculate time to value

To calculate TTV, you have to decide on an action that, when a user completes it, will show the user the value of the product.

This action, or sequence of actions, will be different for every product. But they usually represent the moment that the user solves a problem for the first time. Generally speaking, your goal is to make TTV as short as possible.

Once you have established these critical actions, use your product analytics tool to track how long users take to complete them (on average) after signup.

Time-to-value = total time taken by all users to complete critical action / number of users

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Frequently asked questions

1. What are product metrics?

Product metrics are ways to measure how users interact with your product. They are forms of quantitative data that reveal customer satisfaction and help track growth. For example, monthly recurring revenue (MRR) tracks how much money a product generates each month through subscriptions.

2. How do product metrics help businesses?

Product metrics help you understand how users interact with your mobile app or website. This allows you to:

  • Take a customer-centric approach to business by continually optimizing your product around user needs

  • Identify issues in your product or user experience that might otherwise go unnoticed

  • Track the impact of important initiatives, such as a new marketing campaign or feature update

3. How can businesses improve their product metrics?

Product metrics largely reflect the product itself—so to improve your metrics, improve your product and service!

Some of the best ways to do this include:

  • Catch bugs and issues quickly. Use a product analytics tool that alerts you to errors and check your churn rate regularly.

  • Get feedback from your users. Product metrics can only tell you half the story. Carry out a company-wide VoC program to learn about user pain points and needs.

  • Carry out A/B testing. If you have enough traffic, create hypotheses for how you could improve key touchpoints and use A/B testing to optimize them.

  • Make data-driven decisions about what to prioritize. There’s no point in improving your referral programs if customer satisfaction with your product is low. Look at your metrics to find out where the biggest “leaks” in the customer journey are and make it your priority to address those first.

4. What are some common challenges with product metrics?

Products are complex, so understanding and applying metrics measured in them can be difficult. Common challenges include:

  • Choosing the right metrics. Companies must choose metrics that align with their goals in advance. Without this, they may struggle to perform effective analyses later.

  • Measuring metrics correctly. For example, many startups want to track how many active users they have—but what defines an “active user” is up to the company.

  • Understanding trends. Metrics can show when user behaviors change, for example when there is a sudden spike in churn rates. However, it’s not always obvious why a particular user behavior is occurring.

5. How do you define success metrics for a product?

Follow these four steps to define product success metrics:

1. Determine goals. Your business should have a clear objective in mind, like improving customer satisfaction or increasing profits.

2. Consider what signals would show movement towards those goals. Some signs might be external (such as your market share or product reviews), but some may be reflected in user behavior or attitudes that could be measured in your product.

3. Choose metrics that align with those signals. Ensure you choose metrics that are actionable, useful and relevant to your overall goals.

4. Avoid vanity metrics. Be careful not to focus on metrics that are impressive but contribute little to your actual goals (for example, page views when analyzed without further context from other metrics).

6. How do you choose the right UX metrics for your product?

Follow these three steps to choose the right UX metrics:

1. Determine goals. Get clear on your goals for UX (which may be different or more design-focused than the goals other departments have).

2. Categorize goals using the HEART framework. Do your goals relate to happiness, engagement, adoption, retention or task success?

3. Map out success signals and relevant metrics for each goal. Reverse engineer what signals of success or failure would be for each goal. Identify which of these could be tracked with product analytics metrics.