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19 product monitoring metrics every PM should track
Building a product that people love starts with identifying a real human need. But once your solution is up and running, how do you make sure it continues to provide long-term customer and business value?
Monitoring product metrics—like monthly active users and product adoption rate—ensures that the product you think your customers want is actually something they can’t live without.
Last updated30 Nov 2022
Reading time19 min
Measuring the right metrics helps you identify opportunities to improve the product experience (PX) and create customer delight.
In this article, we share some of the most powerful product metrics and KPIs (key performance indicators) for product teams to keep an eye on, including:
The list of potential ways to measure product success is long. The good news: you don’t need to track every metric, and in fact you probably shouldn’t.
We’ll explain that further below as we dive into the product metrics that product managers swear by, along with how to calculate and interpret them.
But first, we need to clear up an important distinction that’s often misunderstood.
Product KPIs vs. metrics: what’s the difference?
Product metrics measure the activity or behavior of users as they interact with your website or app. This includes things like the number of visitors to your site, the time people spend in your app, or how often people return to your product.
KPIs—key performance indicators—are metrics that reflect a specific objective or outcome you’re trying to reach.
Basically, all KPIs are metrics, but not all metrics are KPIs.
How you determine your product KPIs depends on your business objectives, and they help guide your product decision-making.
For example, a startup aiming for growth might use the number of monthly active users as a KPI, while also keeping an eye on metrics like usage frequency and session duration.
Or a company might track several customer satisfaction metrics, but use Net Promoter Score® as their primary KPI for tracking customer loyalty.
We cover all of these metrics below, but let’s start with some of the most common product usage metrics to help you gauge when, how, and how often users interact with your product.
Product adoption and activation metrics
Product adoption and activation are about turning potential customers and site visitors into active users of your product.
Monitoring product adoption helps you understand how well you’re converting people who sign up for your product into successful users. It’s an indicator of the quality of new users, and the effectiveness of your onboarding flows.
Adoption metrics apply to your product in general, and can be used for specific features within your product. Here are some of the most popular product adoption metrics for product teams:
1. Activation rate
Activation rate measures the percentage of users who complete a specific milestone early in their product adoption, typically during the onboarding process. This might be when people log in to their account three times in a week, or when they generate their first report.
The specific milestone depends on your product and business goals. Ultimately, you want to select a milestone related to long-term product use.
🧮 How to calculate activation rate:
Activation rate = (Number of users who complete the milestone / Total number of users who signed up) × 100
If your activation rate is consistently low, it may mean your marketing and sales efforts aren’t attracting the right audience, or it could be a sign that you need to simplify your onboarding flow. Use a product analytics tool like Mixpanel to identify where people are dropping out after they begin using your product.
Explore other common customer activation metrics here.
Time-to-activate tells you how long it takes users to hit the value-indicating milestone—or ‘aha! moment’—you’ve defined for your activation rate. For example: a specific number of product logins, generating a first report, or sharing a project with a coworker.
🧮 How to calculate time-to-activate:
To measure time-to-activate, count the number of days between signup and activation.
The quicker you can get people from signup to activation, the more likely you are to retain new users. And more active users means faster growth.
Think of time-to-activate as a benchmark to constantly improve. Designing a smoother onboarding process and improving product UX can improve activation time by reducing friction and directing users to the features and functions they care about. Use continuous discovery methods to frequently identify new problems your customers have, and prioritize the solutions they need.
3. Feature adoption rate
Feature adoption rate looks at the number of users who actively use a specific feature of your product.
🧮 How to calculate feature adoption rate:
Feature Adoption Rate = (Number of feature users / Total active product users) x 100
Note: you should only consider the number of active users in this calculation, not people who’ve signed up for your product but haven’t become active users.
For example, if you have 8,000 active users and 400 use your ‘Upload custom logo’ feature, that’s a feature adoption rate of 5%.
A high feature adoption rate indicates a popular feature, and one you should make sure provides a great user experience.
A 5% adoption rate, like in our example above, indicates low user engagement—but it doesn’t tell you why users aren't engaging. It might not be a useful product feature; it could be a useful idea but a poorly executed design; or maybe users simply can’t find the feature in your product, or don’t know it exists. Using a combination of user recordings and live feedback can help answer this question.
Time-to-first-action (TFA) measures the time it takes for new users to perform a particular action you’ve defined as important. For a blogging site, it might be ‘Published first post’. For an analytics platform, it could be ‘Generated first report’.
🧮 How to calculate time-to-first-action:
To calculate time-to-first-action, measure the days between when someone became a customer, and when they first performed the target action(s).
Time-to-first-action is an indicator of how well you’re onboarding new customers, and shows you what features customers care most about. A long TFA could indicate a confusing onboarding process, complicated menus or product UX, or a lack of interest in the target action. Tools like session recordings and surveys help identify bugs and confusing areas in your product, which you can improve to speed up time-to-first-action.
5. Product usage frequency
Usage frequency measures how often customers use your product.
🧮 How to calculate product usage frequency:
To calculate product usage frequency, select a period of interest—i.e. a day, a week, a month—and count the number of times a user engages with your product in that period.
Monitoring usage frequency gives you a benchmark of how often the average user needs your product, helping you identify people who engage with your product less than average, so you can follow up to find out why.
The metric also indicates trends in individual user activity. If a user is active daily when they first start using your product, but slips to weekly or monthly down the road, you can reach out to find out what’s changed, and how you can better support them.
Tip: launch a product-market fit survey to learn why usage frequency drops off, and what you can do to improve adoption.
6. Onboarding completion rate
Onboarding completion rate is the percentage of people who finish your onboarding process out of those who start.
🧮 How to calculate onboarding completion rate:
Onboarding completion rate = (Number of users who completed onboarding / Total number of users who started onboarding) x 100
For example, if 200 users signed up and started onboarding this month, but only 180 made it to the end, that’s an onboarding completion rate of 90%.
A low completion rate could indicate friction in your onboarding flow, like complicated menus or poorly written copy. In this case, reducing steps and reviewing copy could be obvious fixes. Low completion could also stem from marketing and sales efforts that are targeting the wrong audience. In this case, work with those teams to refine your target audience.
If someone doesn’t complete your onboarding, they’re unlikely to become 'sticky' users—users who regularly return to your product—so it’s important to understand why people drop out. Set up events in product analytics tools like Mixpanel and Amplitude to monitor product onboarding success. Adding tools like surveys and session recordings from Hotjar (that's us!) can give you additional insights into why users aren’t completing your onboarding flow.
Website and product engagement metrics
Measuring engagement helps you understand the value people get from your product, and reveals things like how long users stay in the product, how many pages and features they use, and how often they return.
Digital products can be browser-based, app-based, or both. The following metrics apply to websites and apps, so we use the terms ‘website engagement’ and ‘product engagement’ interchangeably.
Here are the website engagement metrics product managers need to keep an eye on:
7. Monthly active users (MAU)
Monthly active users (MAU) is the number of people who engage with your product or website each month.
For many teams, active users is the top growth KPI for measuring the health of a SaaS product. This can be done on a daily (DAU) or weekly (WAU) basis, but tracking monthly active users (MAU) is the most common.
How you define ‘active’ depends on your product.
For some companies, ‘active' means ‘have logged into their account this month’, while other companies may be more specific. For example, for a streaming platform, ‘active’ might mean ‘have watched a video for 10+ minutes’, and for an analytics program, it could mean ‘generated at least one report’.
🧮 How to calculate monthly active users:
Define ‘active’ for your product
Measure the number of users that meet that definition in a given month
Increasing MAUs can be a good indicator that users find regular value in your product. A drop in MAUs signals less product activity, and can be an early sign of churn (more on that later).
8. Pageviews and average time-on-page
Pageviews tell you how many users visit a particular page on your website. Average time-on-page tells you how long people spend on each page.
In general, you want more pageviews and higher time-on-page—but keep in mind that time-on-page is also relevant to a page’s length and objective. For example, you should expect a 2,000-word blog post to keep more attention than a landing page with an attractive CTA above the fold.
🧮 How to calculate pageviews and average time-on-page:
You can track pageviews and time-on-page with traditional website analytics tools like Google Analytics.
When tracked over time, trends can reveal important changes to campaign effectiveness and other technical issues, like slow page speeds and other website performance metrics. For example:
A drop in pageviews might reveal that a campaign has become less effective, or that there’s been a drop in that page’s SEO value
A drop in average time-on-page might be a sign that a new campaign is attracting the wrong audience, or that your page load times have increased
Check recent changes to marketing activities and watch session recordings to understand why people spend less time on your site.
9. Average session duration
Session duration is the amount of time a user spends on a website or in an app from the time they open it until they leave. In other words, it measures the continuous duration of a single visit.
🧮 How to calculate average session duration:
Session duration = Time user leaves the app or website - Time the app or website was launched
For example, if a user opens your app at 11:15am and leaves at 11:20am (= 5 minutes), and they come back at 3:30pm and stay until 3:50pm (= 20 minutes), that’s two sessions with an average duration of 12.5 minutes ([5 + 20] / 2).
Session duration is important because it gives you a baseline for product engagement. It’s also important to note that longer isn’t always better. For example, a language translation app might aim for shorter sessions, because that indicates users are quickly and easily getting the info they need.
If you use session duration as a KPI, use it as a benchmark to judge the effectiveness of product updates according to your product’s goals.
10. Bounce rate
Bounce rate is an important website engagement metric that tracks the percentage of people who visit a page and leave without taking another action—like playing a video or clicking through to another page. In general, if someone is on your page and they close the tab without doing anything, that’s a bounce.
🧮 How to calculate bounce rate:
Bounce rate = (Number of people who leave a page without taking an action / Number of people who arrive on a page) x 100
A high bounce rate can indicate that the content on your page isn’t relevant or engaging. It could also be a sign of UX bugs, intrusive pop-ups, or slow page load speeds.
An average ecommerce website bounce rate is between 20% and 45%, but this can vary widely for different industries and page types. Use your bounce rates as benchmarks to monitor and continuously improve.
Traditional analytics tools like Google Analytics (GA) provide page and site bounce rates by default, so you never have to calculate this on your own. But GA can’t tell you why people are leaving. Use Hotjar's feedback widget and on-site surveys to gain qualitative insights and understand why people bounce from your site.
11. Scroll depth
Scroll depth monitors how far down a page a visitor scrolls, and reveals the parts of your page they find engaging—or where they lose interest.
🧮 How to calculate scroll depth:
Simple tools like the Google Analytics Scroll Depth plugin can show the percentage of users who scroll through 25%, 50%, 75%, or 100% of your page depth. Advanced tools like Hotjar Heatmaps provide more precise insights into where page visitors fall off, click, move, and scroll on your site.
Analyze scroll heatmaps along with individual session recordings to identify—and then fix—bugs, poor UX, and confusing content in the areas where people stop scrolling.
12. Click-through rate (CTR)
Click-through rate is a conversion rate optimization metric that shows how well you're getting people to take a desired action—usually through an ad, button, or link click. Essentially, it measures the effectiveness of a call-to-action (CTA).
🧮 How to calculate click-through rate:
CTR = (Number of people who clicked / Number of people who saw the call-to-action) x 100
CTR is useful in a variety of contexts. For example, imagine you have an ad on Facebook that leads to a landing page, which leads to a signup form. At each stage (Facebook ad → landing page → signup form), a person must click a button or link. In this case, you’ll have a CTR from Facebook to your landing page, another one from your landing page to your signup form, and a final CTR for those who click 'submit' on your signup form.
Google Analytics is a good place to start monitoring click-through rates on a webpage—then, watch session recordings to discover why visitors don't click, and use this insight to improve buggy UX, broken UI, and confusing copy.
Retention metrics to monitor business and product health
The above metrics give you insight into your product usage—from adoption to engagement. The following metrics reveal the health of your product and business.
A healthy product solves a real user need, over and over again. Here are some top metrics for gauging healthy product growth—from customer retention and satisfaction, to product stickiness:
13. Customer retention rate (CRR)
Customer retention rate is the percentage of customers who continue to use your product over a given period. Here we focus on monthly retention, the most common customer retention metric.
🧮 How to calculate monthly customer retention rate:
Retention rate = [(Total customers at the end of the month - New customers acquired this month) / Total customers at the start of this month] x 100
For example, if you start the month with 5,000 customers, gain 500, then finish the month with 5,100 customers, you have a retention rate of 92% [(5,100 - 500) / 5,000] x 100.
A high retention rate is a strong indicator of customer loyalty—and since the cost of acquiring a new customer is much higher than retaining an existing one, improving retention is a key growth strategy. Retention is also a good indicator of product-market fit: you’re building a product that people actually want.
14. Customer churn rate
Customer churn rate is the percentage of customers lost in a given period—it’s the inverse of customer retention rate. For SaaS companies that charge a monthly subscription fee, it reflects customers who cancel their subscriptions.
🧮 How to calculate monthly customer churn rate:
Churn rate = (Number of customers lost this month / Total number of customers at the start of this month) x 100
Note: the period may vary depending on the specific industry or sales cycles, but monthly is a typical time frame.
For example, if you started April with 8,000 customers, and lost 200 that month, your churn rate would be: 200 / 8,000 = 2.5%
Measuring churn helps gauge how satisfied people are with your product, but it doesn't tell you why they leave. It might mean your product isn’t solving their needs or that it’s too expensive. Or maybe they love your product, but only needed it for a one-time project.
Tip: apart from tracking churn rate, it’s important to find out why people churn, which you can do with an exit-intent survey.
15. Customer lifetime value (CLV, LTV, CLTV)
Customer lifetime value (abbreviated as CLV, LTV, or CLTV) measures the total revenue you can expect from a customer over their lifespan with your company. There are various ways to calculate LTV for different businesses, but we’ll focus on the simplest method for most SaaS companies:
🧮 How to calculate customer lifetime value:
LTV = Average amount a user pays per month x Average length of a contract
For example, if the average customer pays $35 per month, and they stick around for 16 months, your customer lifetime value is $560.
A growing LTV means that, on average, each customer is paying you more: they’re sticking around for longer, they're paying you more each month, or, ideally, both.
The best ways to increase LTV are to upsell customers to larger plans, cross-sell them to other products, and monitor product usage and customer satisfaction to ensure long-term success.
16. Customer Satisfaction (CSAT)
Customer satisfaction (CSAT) measures how satisfied people are with your products or services. It’s often tracked at key moments in a customer's journey—like right after they complete onboarding, or following an interaction with your customer support team.
CSAT can also be tracked at regular intervals—like a monthly pulse check—to provide a regular way to monitor product success.
🧮 How to calculate CSAT:
CSAT is typically measured with a customer satisfaction (CSAT) survey that asks customers to rate their satisfaction with your product on a 5– or 7–point scale.
Monitoring CSAT helps you understand whether your product meets users' needs, track the impact of recent changes to your product, and identify issues that need immediate attention.
17. Net Promoter Score® (NPS)
NPS monitors long-term customer loyalty and the likelihood of users recommending your product to others.
🧮 How to calculate NPS:
Net Promoter Score® is measured with a two-part survey, asking users one quantitative and one qualitative question:
On a scale of 1–10, how likely are you to recommend us to a friend or colleague?
What’s the reason for your score?
From the first question, subtract your percentage of detractors (0–6 answers) from your percentage of promoters (9–10 answers). For example, if 15% are detractors and 55% are promoters, your NPS is 40.
The second, qualitative question uncovers the reasons and motivations of your raving fans, and your strongest critics.
To get the full strength of the measure, repeat your NPS survey regularly. It can also be a great way to find power users for case studies.
18. Customer growth rate
Your customer growth rate refers to how fast you gain new customers over a given period (usually monthly).
🧮 How to calculate monthly customer growth rate:
Customer growth rate = (New customers this month / Total customers last month) x 100
Customer growth rate reveals how quickly your product attracts new paying customers. A low customer growth rate can indicate you haven’t yet reached product-market fit.
A related measure often assessed by VC firms is revenue growth rate, which is calculated the same way, but substitutes ‘revenue’ for ‘customers’ in the equation.
To improve customer growth rate, ensure that marketing and sales teams target the right customers. Then optimize your website using qualitative analytics, feedback tools, and CTA best practices.
Product 'stickiness' refers to how often people engage with your product. To know how sticky your product is, look at the ratio of daily active users (DAU) to monthly active users (MAU).
🧮 How to calculate product stickiness:
Stickiness = daily active users / monthly active users
For example, a DAU/MAU of 0.4 means 40% of people who use your product on a monthly basis are using your product every day. The higher the rate, the stickier the product.
According to VC firm Sequoia Capital, a good DAU/MAU can vary from 10–70% depending on the product:
Note: not all products are built for daily use. For example, Airbnb is a great product that many users might turn to only once or twice a year. Make sure you consider how often you expect people to use your product before selecting stickiness as a relevant KPI.
The metrics that matter to you
Monitoring product metrics is one of the best ways to know whether you’re truly building a product that people need and love.
But you don’t need to measure everything: metrics are about decision-making. They help guide your next actions by pointing out things that are working, and things that need improvement.
Start with your goals, then define one or two actionable metrics—your KPIs—that signal progress toward those goals, and focus on those. You can always add supporting metrics later for additional insights.
And remember that most metrics can tell you what is happening with your product or business, but they can’t always tell you why it’s happening. To really understand what your users think, compliment your quantitative metrics with qualitative insights.