25 product management metrics you should be tracking
Drive product success with essential metrics every product manager needs. Track and leverage data-driven insights to improve acquisition, conversion, engagement, retention, and revenue.
In product management, data is king. It's what turns good products into great ones. But with a sea of metrics out there, which ones should you really be keeping an eye on?
Let’s dive into 25 essential metrics that can light the path toward your product success.
We'll kick things off with a category that's close to every product manager's heart: Acquisition. These metrics are all about understanding how effectively you're attracting and engaging new users.
Acquisition metrics
1. Cost per acquisition (CPA)
CPA is the average cost of acquiring a new potential customer. This could be a lead generated from a webinar, a free trial signup, or any other action that indicates interest in your product.
Why it matters
CPA is your financial compass for customer acquisition. By tracking it, you can see which marketing channels, campaigns, or strategies are the most cost-effective. This helps you make smart decisions about where to invest your money.
How to calculate it
CPA = (Total cost of sales and marketing) / (Number of new customers acquired)
Key takeaway: A rising CPA could signal a need to adjust your marketing tactics or re-evaluate your product's appeal.
2. Customer acquisition cost (CAC)
CAC is a product management metric that takes a broader view than CPA. It includes all the costs associated with acquiring a new paying customer — marketing, sales, and any other related expenses.
Why it matters
CAC is essential for understanding your overall profitability. If your CAC is too high compared to the revenue a customer generates (their lifetime value), you'll need to rethink your acquisition strategies or pricing.
How to calculate it
CAC = (Total sales and marketing costs) / (Number of new paying customers)
Key takeaway: An ideal CAC-to-LTV (Lifetime Value) ratio is 3:1. This means the revenue a customer generates should be three times the cost of acquiring them.
3. Bounce rate
Bounce rate is the percentage of users who land on your website or app and then leave without taking any further action (like clicking a link or visiting another page).
Why it matters
A high bounce rate can be a red flag. It might mean your landing pages aren't engaging, your website isn't user-friendly, or your content isn't resonating with visitors.
How to calculate it
Bounce rate = (Single-page visits) / (Total visits to your website or app)
Key takeaway: Keep a close eye on your bounce rate, especially after making changes to your website or app. A sudden increase could indicate a problem that needs your attention.
Conversion metrics
These metrics help you understand how effectively you're converting visitors into paying customers. They shine a light on the areas where you can improve your product and make it more appealing to your target audience.
4. Conversion rate (CVR)
CVR is the percentage of visitors who take a desired action, such as signing up for a free trial, purchasing a product, or downloading a white paper.
Why it matters
CVR is a crucial product management metric for measuring the effectiveness of your marketing and sales efforts. It helps you identify which channels, campaigns, and content are most successful at driving conversions.
How to calculate it
CVR = (Number of conversions) / (Total number of visitors)
Key takeaway: A rising CVR is a positive sign, indicating that your product is resonating with your target audience.
5. Time to first value (TTFV)
TTFV is a product management metric that shows the average amount of time it takes for a new user to experience your product's value. This could be the time it takes to complete a specific task, achieve a certain milestone, or simply start using the product regularly.
Why it matters
TTFV is a great indicator of how quickly your product is delivering value to users. A shorter TTFV is typically associated with higher user engagement and retention.
How to calculate it
While not a simple formula, here's how to approach TTFV measurement:
- Identify the "aha moment": Determine the specific action or event that signifies a user has experienced the core value of your product. This could be making their first purchase, inviting a friend, or creating their first project.
- Track key onboarding steps: Monitor how users progress through your onboarding process, noting which steps they complete and how long it takes.
- Record time to first value: Use product analytics tools to record when users achieve the defined "aha moment."
- Calculate the average: Calculate the average time it takes for users to reach this milestone from the moment they sign up or start using your product.
Key takeaway: A long TTFV could be a sign that your onboarding process is confusing or that your product is not intuitive enough.
6. Conversion funnel drop-off rate
The conversion funnel drop-off rate measures the percentage of users who abandon your funnel at each stage.
This could be the percentage of visitors who leave your website after signing up for a free trial, or the percentage of trial users who cancel before converting to paying customers.
Why it matters
By analyzing your conversion funnel drop-off rate, you can identify the specific points where users are getting lost or frustrated. This information can help you make targeted improvements to your funnel and increase your overall conversion rate.
How to calculate it
Conversion funnel drop-off rate = (Number of users who leave at a specific stage) / (Number of users who enter the stage)
Key takeaway: A high drop-off rate at a particular stage indicates that there's a problem that needs to be addressed.
Engagement metrics
Conversions are great, but what happens after users sign up? That's where engagement metrics come in. These metrics provide valuable insights into how users interact with your product, revealing what keeps them coming back for more.
7. Daily active users (DAU)
DAU is the number of unique users who interact with your product daily.
Why it matters
DAU is a vital sign of your product's health. It shows how many users are finding enough value in your product to use it regularly.
How to calculate it
DAU = (Number of unique users who interact with your product in a day)
Key takeaway: A rising DAU is a positive sign of growing user engagement.
8. Monthly active users (MAU)
MAU is similar to DAU, but it measures the number of unique users who interact with your product in a month.
Why it matters
MAU provides a broader perspective on user engagement than DAU. It can help you identify trends and patterns in user behavior over a longer period.
How to calculate it
MAU = (Number of unique users who interact with your product in a month)
Key takeaway: Together, DAU and MAU provide a more refined view of your product's user base and engagement.
9. Session duration
Session duration is the average amount of time a user spends interacting with your product during a single session.
Why it matters
Session duration is a key indicator of user engagement. Longer sessions typically indicate that users are finding your product valuable and engaging.
How to calculate it
Session duration = (Total time spent by all users in a given period) / (Total number of sessions in that period)
Key takeaway: If your session duration is short, it might be a sign that users are not finding what they are looking for or that your product is not easy to use.
10. Session frequency
Session frequency measures how often users return to your product within a given timeframe.
Why it matters
Session frequency reveals how habitual your product is for users. A higher session frequency indicates that users are finding your product valuable enough to use repeatedly.
How to calculate it
Session frequency = (Total number of sessions) / (Number of unique users)
Key takeaway: A low session frequency could indicate that your product lacks stickiness or that there are barriers to repeat usage.
11. Feature adoption rate
Feature adoption rate measures the percentage of users who adopt a new feature within a certain time frame after its release.
Why it matters
Feature adoption rate is one of the product management metrics that helps you gauge the success of new features. It tells you which features are resonating with users and which ones need further refinement.
How to calculate it
Feature adoption rate = (Number of users who adopt a new feature) / (Total number of users)
Key takeaway: A low feature adoption rate could indicate that the feature is not well-designed, not marketed effectively, or not relevant to your users' needs.
12. User retention rate
User retention rate is the percentage of users who continue to use your product over a given period of time.
Why it matters
User retention is critical for the long-term success of your product. It's much more cost-effective to retain existing users than to acquire new ones.
How to calculate it
User retention rate = ((Number of users at the end of a period - Number of new users acquired during that period) / Number of users at the start of the period)) * 100
Key takeaway: A high retention rate is a sign that your product is delivering ongoing value to your users.
13. Churn rate
Churn rate is the percentage of users who stop using your product over a given period of time.
Why it matters
Churn rate is the opposite of retention rate, and it's equally important to track. A high churn rate can be a red flag, indicating that users are not satisfied with your product or that they are finding better alternatives.
How to calculate it:
Churn rate = (Number of users who churned in a given period) / (Number of users at the start of the period)
Key takeaway: A high churn rate requires immediate attention. You need to identify the reasons behind the churn and take steps to address them.
Retention metrics
Acquiring customers is only half the battle; keeping them engaged and loyal is the true test of product success. That's where retention metrics shine. They provide invaluable insights into how satisfied customers are with your product and how likely they are to stick around.
14. Customer retention rate (CRR)
CRR measures the percentage of customers who remain loyal to your product over a specific period. It's a vital indicator of customer satisfaction and the value your product delivers over time.
Why it matters
CRR is a cornerstone of sustainable growth. Retaining customers is often more cost-effective than acquiring new ones, and loyal customers can become brand advocates, attracting new users through word-of-mouth.
How to calculate it
CRR = ((Number of customers at end of period - Number of new customers acquired during period) / Number of customers at start of period) x 100
Key takeaway: A high CRR is a strong indicator of product-market fit and a loyal customer base.
15. Net promoter score (NPS)
NPS measures customer loyalty and satisfaction by asking a simple question:
"On a scale of 0-10, how likely are you to recommend our product to a friend or colleague?"
Customers are then categorized as Promoters (9-10), Passives (7-8), or Detractors (0-6).
Why it matters
NPS provides a snapshot of customer sentiment and can help you identify areas for improvement. Promoters are your biggest fans and can drive organic growth through referrals. Detractors, on the other hand, can highlight areas where your product is falling short.
How to calculate it
NPS = (Percentage of promoters) - (Percentage of detractors)
Key takeaway: Aim for a high NPS, as it's a strong predictor of customer loyalty and future growth.
16. Customer satisfaction score (CSAT)
CSAT measures customer satisfaction with a specific interaction or experience, such as a customer support interaction or a product purchase.
Why it matters
CSAT provides targeted feedback on specific aspects of the customer experience. It helps you pinpoint areas where you can improve and enhance customer satisfaction.
How to calculate it
CSAT = (Number of satisfied customers) / (Total number of customers surveyed)
Key takeaway: Use CSAT to gather feedback on specific interactions and make targeted improvements to the customer experience.
17. Customer effort score (CES)
CES measures the amount of effort a customer has to expend to achieve a goal with your product. It's based on the premise that customers are more likely to remain loyal if their interactions are effortless.
Why it matters
CES helps you identify friction points in the customer journey. By reducing customer effort, you can increase satisfaction, loyalty, and, ultimately, revenue.
How to calculate it
CES = (Sum of effort scores) / (Number of respondents)
Key takeaway: Aim for a low CES, as it indicates a smooth and user-friendly experience for your customers.
Revenue metrics
Engaged users are fantastic, but a product needs to generate revenue to thrive. That's where revenue metrics step into the spotlight. These financial measures offer insights into your product's profitability and help you make informed decisions about pricing, marketing, and growth strategies.
Let's take a closer look at four essential revenue metrics:
18. Lifetime value (LTV)
LTV, also known as customer lifetime value (CLV), is the average amount of revenue you can expect to generate from a single customer throughout their entire relationship with your product.
Why it matters
LTV is a north star metric for many businesses. It helps you understand the long-term value of your customers and make informed decisions about how much to invest in acquiring and retaining them. A high LTV indicates a healthy customer base and a sustainable business model.
How to calculate it
LTV = (Average purchase value) x (Average purchase frequency rate) x (Average customer lifespan)
Key takeaway: Knowing your LTV can help you identify your most valuable customer segments and tailor your marketing efforts accordingly.
19. Monthly recurring revenue (MRR)
MRR is the predictable revenue a (usually subscription-based) business can expect each month. It includes recurring charges from subscriptions, upgrades, and add-ons, but excludes one-time fees.
Why it matters
MRR is a vital metric for subscription businesses, as it provides a snapshot of their financial health and growth trajectory. It helps you forecast future revenue and make informed decisions about pricing, marketing, and resource allocation.
How to calculate it
MRR = (Number of customers) x (Average revenue per customer per month)
Key takeaway: A steady increase in MRR is a positive sign of business growth and customer satisfaction.
20. Annual recurring revenue (ARR)
ARR is similar to MRR but measures the predictable revenue over a year. It's particularly useful for understanding the long-term financial stability of a subscription business.
Why it matters
ARR is a valuable metric for investors and stakeholders, as it provides a clear picture of a company's financial performance and potential for growth. It can also be used to benchmark against competitors and industry averages.
How to calculate it
ARR = MRR x 12
Key takeaway: A healthy ARR is essential for attracting investment and ensuring long-term sustainability.
21. Average revenue per user (ARPU)
ARPU is the average revenue generated per user within a specific time period, usually a month or a year.
Why it matters
ARPU is a useful metric for understanding the revenue contribution of each user. It can be used to assess the effectiveness of pricing strategies, identify high-value customer segments, and track changes in user behavior.
How to calculate it
ARPU = (Total revenue) / (Number of users)
Key takeaway: Increasing your ARPU can be achieved by upselling, cross-selling, or improving customer retention.
Feedback and optimization metrics
Numbers tell a story, but the most compelling narratives come directly from your customers.
Feedback and optimization metrics give you a direct line to your users' thoughts, feelings, and experiences. By listening to their voices, you can uncover hidden opportunities for improvement and create a product that truly resonates.
22. Feature request tracking
Feature request tracking involves collecting, organizing, and analyzing user requests for new features or improvements.
Why it matters
Feature requests are a direct reflection of your users’ needs and desires. By tracking these requests, you can identify recurring themes, prioritize development efforts, and build features that users truly want and need.
How to track it
There's no single formula for feature request tracking, but it often involves using tools like feedback forms, surveys, or dedicated feature request platforms to collect and analyze user feedback.
Key takeaway: Don't just collect feature requests; analyze them to uncover patterns and prioritize features that align with your product vision.
23. User feedback volume
User feedback volume measures the total amount of feedback you receive from users through various channels, such as surveys, emails, social media, or customer support interactions.
Why it matters
User feedback volume is a powerful indicator of customer engagement and satisfaction. A high volume of feedback suggests that users are actively involved with your product and care enough to share their thoughts.
How to track it
Monitor the number of feedback submissions you receive across all channels over a specific period.
Key takeaway: A sudden drop in feedback volume could indicate that users are losing interest in your product or encountering barriers to providing feedback.
24. Customer sentiment score
Customer sentiment score aggregates positive, neutral, and negative feedback to provide an overall measure of customer satisfaction and perception of your product.
Why it matters
Customer sentiment is a key indicator of brand health and loyalty. By understanding how customers feel about your product, you can make informed decisions about how to improve their experience and build long-term relationships.
How to calculate it
Customer sentiment scores can be calculated using various methods, including manual analysis of feedback, sentiment analysis tools, or surveys that ask customers to rate their satisfaction on a scale.
Key takeaway: A positive customer sentiment score is a good sign that your product is meeting customer needs and expectations.
25. Escalation rate
Escalation rate measures the percentage of customer support issues that are escalated to a higher level of support or management.
Why it matters
A high escalation rate could indicate that your front-line customer support team is unable to resolve issues effectively or that there are underlying problems with your product or service.
How to calculate it
Escalation rate = (Number of escalated issues) / (Total number of support issues)
Key takeaway: Monitor your escalation rate to identify areas where your customer support process needs improvement and to prevent minor issues from escalating into major problems.
Next steps
Knowing the numbers is just the first step. The results truly start to show when you turn that data into actionable strategies that drive product growth.
Enter Eppo, the platform for experiment-driven product development.
Sitting directly on top of your data warehouse, Eppo centralizes all your key metrics in one accessible location. No more juggling multiple platforms or struggling with fragmented data. With Eppo, you get a crystal-clear view of your product's performance.
But Eppo goes beyond mere tracking. It empowers you to run rigorous experiments to accurately tend to your key business metrics. With features like:
- Randomized assignments: Ensure unbiased results, eliminating the risk of misleading conclusions.
- CUPED++ acceleration: Reach statistically significant results faster, accelerating your experimentation cycles and freeing up resources.
- Continuous monitoring: Receive automated alerts for data quality issues, traffic imbalances, and other potential problems, ensuring the reliability of your experiments.
Eppo helps turn your product management metrics into momentum and equips you with the tools to test, learn, and iterate your way to product success.
Drive product success with essential metrics every product manager needs. Track and leverage data-driven insights to improve acquisition, conversion, engagement, retention, and revenue.
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