39+ key product metrics for B2B SaaS companies
Learn why product metrics matter, which ones to track, and how to track them.
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Authors of this article
Manav is a lead data analysts at Atlassian, credited with discovering important product insights that have led to singificant additional revenue for Atlassian.
Mikhiel is the COO of Signal, a product that creates data-powered territory plans for sales reps. He and the Signal team work with large enterprises on their product analytics tracking plans.
Chase founded Flywheel after creating and launching Jira Work Management at Atlassian. He has executed product-led growth across multiple verticals and companies, ranging from SaaS to e-commerce.
What are product metrics? What is their purpose?
Product metrics are the quantitative measurements used to analyze a product or service. These metrics help product managers, GTM leaders, and other stakeholders understand product adoption, user growth, and retention. Moreover, product metrics help product teams identify patterns in user behavior, helping inform the feature roadmap.
Product metrics are also used as a proxy for user interviews and other non-scalable, non-real-time ways of gathering information. They act as a vital source of information for product-led growth (PLG) companies, which rely on the product itself as the primary driver of customer acquisition, expansion, and retention. It's no exaggeration to say that choosing the right product metrics to track is often the deciding factor between a successful or stagnant product.
How to identify which key product metrics to track
To start, pinpoint the Key Performance Indicators (KPIs) that are most relevant to your product's success and strategic goals. For example, if your goal is to increase user retention, prioritize metrics like churn rate, user engagement, and customer lifetime value.
On the other hand, if your goal is to acquire new users, focus on metrics like acquisition cost, conversion rate, and organic growth. This should involve input from different departments within your organization, such as:
Product Management — To identify features which drive user satisfaction and retention.
Sales and Marketing — To determine which marketing channels are most effective in attracting new users and converting leads.
Customer Success — To understand the factors that contribute to user satisfaction and long-term customer loyalty.
Engineering — To identify areas for improvement in performance, stability, and reliability.
You'll also want to make sure your company is tracking at least one KPI from each stage of the user lifecycle. Focusing only on growth metrics might result in a higher churn rate than expected. Here are some examples within each category of Acquisition, Activation, Retention, and Referrals.
Acquisition Metrics
Track the effectiveness of your marketing efforts by monitoring metrics like cost per acquisition (CPA), organic vs. paid users, and conversion rates.
Activation Metrics
Gauge how well your product is resonating with new users by tracking metrics like time to first value, feature adoption, and onboarding completion rates.
Retention Metrics
Assess how well you're retaining customers by monitoring metrics like churn rate, user engagement, and customer lifetime value (CLTV).
Expansion Metrics
Measure the long-term health of your product by tracking metrics such as upgrade rates and expansion MRR.
Tools and approaches to tracking product metrics
There are three main approaches to data-tracking systems: CDPs (Customer Data Platforms) and analytics point-solutions (Flywheel, Amplitude, Pendo, etc).
CDPs overview
CDPs track events and specialize in sending that event data to other tools. For example, incorporating event-based triggers in an email automation software is best done by connecting a CDP to the email provider. The downside of a CDP is that the tool itself offers little few analytics capabilities, so they're really just a way to pass data back and forth. Additionally, they're quite expensive. If your company uses many tools that rely on event data, a CDP is likely a good option — but might cost more than your other software subscriptions combined.
Some of the top CDPs are Segment, mParticle, and Lytics.
Analytics solutions overview
If you're looking to analyze product metrics (or, in Flywheel's case, both marketing and product metrics), we recommend starting with an analytics solution that offers a tracking script. There are two types of tracking scripts: Auto-track and Manual tracking.
We discuss these two approaches in more depth in our product analytics guide. In short, however:
Auto-tracking: Also called autocapture, simply installing the script onto your website or in your product will automatically track all page views, click events, and other interactions. This approach is best for companies that want to collect as much data as possible. It's a very fast process to get started — usually less than 3-5 minutes. Learn more about installing our version, Flywheel.js, as an example.
Here are some companies that offer auto-tracking:
Flywheel (can choose between auto-track or manual tracking)
Pendo
Heap
PostHog
Manual tracking: After installing the script, someone (generally an engineer) will add a few lines of code for every event that you want to track. This approach is best for companies that want consistent, very clean data. It's a slower process that will need constant maintenance as the product evolves, but manual tracking is highly reliable and consistent. We estimate planning which events to track will take ~3-4 hours and implementation ~1-2 hours.
Companies that offer manual tracking scripts:
Flywheel
Amplitude
Mixpanel
Google Analytics
10 fundamental B2B SaaS metrics to track
Originally defined as part of the Segment B2B SaaS spec, we recommend every company implement these events — even if you're auto-tracking the rest of your events. For Flywheel.js, install the tracking script to track event automatically, then layer these events on top.
These events are such an industry standard that a number of Flywheel features use these events to complete calculations. The best practice is to fire these events directly from your backend. This gets a bit technical, so work with an engineer to get started.
Account Created: This event should be sent when a new account is created.
Account Deleted: This event should be sent when an account is deleted.
Signed Up: This event should be sent when a user signs up for your product.
Signed In: This event should be sent when a user signs in to your product.
Signed Out: This event should be sent when a user signs out of your product.
Invite Sent: This event should be sent when a user invites another user.
Account Added User: This event should be sent when a user is added to an existing instance of your product.
Account Removed User: This event should be sent when a user is removed from an existing instance of your product.
Trial Started: This event should be sent when a trial is started. Freemium products can disregard.
Trial Ended: This event should be sent when a trial has ended. Freemium products can disregard.
29 examples of key product metrics for PLG
We've split these metrics into the four categories of Adoption, Activation, Retention, and Expansion. While some may need to be modified for your exact use case, this is a great place to start thinking about which metrics are most relevant for your product.
Adoption metrics
Active User Count:
Active users are customers who actively use your product within a given period. This metric helps you understand the level of engagement with your product. Flywheel uses a 30 day calculation.
Calculation: Count of users who performed a specific action or multiple actions within a given period.
Department: Product Management
Feature Adoption Rate:
Feature adoption rate is the percentage of users who adopt a new feature within a given period. It helps you understand the effectiveness of your product updates and feature releases.
Calculation: (Number of users who adopted the feature / Total users) * 100.
Department: Product Management
Feature Retention Rate:
Feature retention rate is the percentage of users who continue to use a specific feature after a given period. It helps you understand which features maintain user engagement and prioritize product enhancements.
Calculation: (Number of users still using the feature after a specific period / Total users who initially adopted the feature) * 100.
Department: Product Management
User Stickiness:
User stickiness is the ratio of daily active users to monthly active users. It helps you understand how often users return to your product and their level of engagement.
Calculation: (Daily active users / Monthly active users) * 100.
Department: Product Management
Activation
Time to First Value (TTFV):
TTFV measures the time it takes for a new user to achieve their first meaningful outcome with your product. It helps assess your onboarding process and product usability.
Calculation: Time from the user's sign-up to their first meaningful action.
Department: Product Management
Product-Qualified Leads (PQLs):
PQLs are potential customers who have demonstrated high engagement and usage of your product, making them more likely to convert to paying customers. This metric helps you identify highly qualified leads for your sales team to target.
Calculation: Count of users who meet specific product usage and engagement criteria.
Department: Sales and Marketing
Activation Rate:
Activation rate is the percentage of users who achieve a predefined success milestone, indicating they have become active users of your product. It helps you understand the effectiveness of your onboarding process and early user experience.
Calculation: (Number of users who reached the success milestone / Total new users) * 100.
Department: Product Management
Reactivation Rate:
Reactivation rate is the percentage of inactive or churned users who become active again within a given period. It helps you understand the effectiveness of your re-engagement strategies and win-back campaigns.
Calculation: (Number of users reactivated / Total inactive or churned users) * 100.
Department: Sales and Marketing
Onboarding Completion Rate:
Onboarding completion rate is the percentage of new users who complete the onboarding process. It helps you assess the effectiveness of your onboarding and user education efforts.
Calculation: (Number of users who completed onboarding / Total new users) * 100.
Department: Product Management
Monthly Recurring Revenue (MRR):
MRR is the total revenue generated by your customers on a monthly basis. It helps you understand the overall health and growth of your SaaS business.
Calculation: Sum of all monthly subscription fees.
Department: Finance
Annual Recurring Revenue (ARR):
ARR measures the yearly revenue generated by your customers. It provides a snapshot of your SaaS business's long-term revenue potential.
Calculation: Sum of all annual subscription fees.
Department: Finance
Customer Acquisition Cost (CAC):
CAC is the average cost to acquire a new customer. It helps you understand the effectiveness of your sales and marketing efforts.
Calculation: Total sales and marketing expenses / Number of new customers acquired.
Department: Marketing
Retention metrics
Customer Satisfaction Score (CSAT):
CSAT measures customers' satisfaction with your product or service on a scale. It helps you understand the overall satisfaction and identify areas for improvement.
Calculation: (Number of satisfied customers / Total survey respondents) * 100.
Department: Customer Success
Net Promoter Score (NPS):
NPS measures customer loyalty by asking if they would recommend your product to others. It helps you understand customer advocacy and potential for organic growth.
Calculation: % of promoters - % of detractors.
Department: Customer Success
User Retention Rate:
User retention rate is the percentage of users who continue to use your product after a specific time period. It helps you understand how well your product retains users and informs strategies to improve engagement.
Calculation: (Number of users retained after a specific period / Total users at the beginning of the period) * 100.
Department: Product Management
NPS Detractor Recovery Rate:
This metric measures the percentage of detractors (customers who give a low Net Promoter Score) who are successfully converted into promoters or passives after targeted interventions. It helps you understand the effectiveness of your customer recovery efforts.
Calculation: (Number of detractors converted to promoters or passives / Total detractors) * 100.
Department: Customer Success
Lifetime Value (LTV):
LTV represents the total revenue generated by a customer during their relationship with your company. It helps you understand the long-term profitability of your customers.
Calculation: Average revenue per customer * Customer lifetime.
Department: Finance
LTV:CAC Ratio:
This metric compares the lifetime value of a customer to the cost of acquiring them. It helps you determine if your customer acquisition efforts are sustainable and profitable.
Calculation: Lifetime Value / Customer Acquisition Cost.
Department: Finance
Churn Rate:
Churn rate measures the percentage of customers who cancel their subscription within a given period. It helps you understand how well you're retaining customers.
Calculation: (Number of customers lost during a period / Total customers at the beginning of the period) * 100.
Department: Customer Success
Customer Renewal Rate:
Customer renewal rate is the percentage of customers who renew their subscription after it expires. It helps you understand the long-term value of your customers and the effectiveness of your retention strategies.
Calculation: (Number of customers who renewed their subscription / Total customers with expiring subscriptions) * 100.
Department: Customer Success
Freemium Conversion Rate:
Freemium conversion rate is the percentage of free users who convert to paying customers. It helps you assess the effectiveness of your freemium model and identify opportunities for growth.
Calculation: (Number of free users who converted to paying customers / Total free users) * 100.
Department: Sales and Marketing
Expansion metrics
Expansion MRR:
Expansion MRR is the additional monthly recurring revenue generated from existing customers through upsells, cross-sells, and add-ons. It helps you understand the potential for growth within your existing customer base.
Calculation: Sum of all additional monthly subscription fees from existing customers.
Department: Finance
Net Revenue Retention (NRR):
NRR measures the percentage of recurring revenue retained from existing customers, considering expansion, contraction, and churn. It helps assess customer satisfaction and loyalty.
Calculation: (Revenue at the end of a period - New customer revenue) / Revenue at the beginning of the period * 100.
Department: Customer Success
Cross-Sell Conversion Rate:
Cross-sell conversion rate is the percentage of existing customers who purchase additional products or services. It helps you understand the effectiveness of your cross-selling efforts and identify opportunities for expansion within your customer base.
Calculation: (Number of customers who purchased additional products or services / Total customers) * 100.
Department: Sales and Marketing
Upgrade Conversion Rate:
Upgrade conversion rate is the percentage of users who upgrade from a lower-tier plan to a higher-tier plan within a given period. It helps you understand the effectiveness of your product's value proposition and expansion efforts.
Calculation: (Number of users who upgraded / Total users on lower-tier plans) * 100.
Department: Sales and Marketing
Downgrade Conversion Rate:
Downgrade conversion rate is the percentage of users who downgrade from a higher-tier plan to a lower-tier plan within a given period. It helps you understand potential issues with your pricing strategy or customer satisfaction.
Calculation: (Number of users who downgraded / Total users on higher-tier plans) * 100.
Department: Sales and Marketing
Referral Conversion Rate:
Referral conversion rate is the percentage of referred users who become paying customers. It helps you understand the effectiveness of your referral program and word-of-mouth marketing.
Calculation: (Number of referred users who became paying customers / Total referred users) * 100.
Department: Marketing
Viral Coefficient:
The viral coefficient measures the rate at which users invite others to use your product. It helps you understand the organic growth potential of your product and the effectiveness of your referral or invite system.
Calculation: Number of invites sent per user * Conversion rate of invites to new users.
Department: Marketing
Customer Retention Cost (CRC):
CRC is the cost associated with retaining customers, including customer support, success, and account management expenses. It helps you understand the efficiency of your customer retention efforts.
Calculation: Total retention expenses / Number of customers retained.
Department: Customer Success
Topline metrics vs. product health metrics
Topline metrics, sometimes referred to as vanity metrics, provide a high-level overview of your product's performance. These metrics, such as the total number of users or page views, can provide a sense of scale but may not offer actionable insights for improving your product. They can sometimes be misleading and may not correlate with the actual success of your product.
On the other hand, product health metrics are more focused on the specific aspects of your product that contribute to its success. These metrics, such as user engagement, feature usage, and retention rates, provide deeper insights into how users interact with your product and can help identify areas for improvement. Product health metrics are more actionable and can guide your product development efforts to drive better results.
Examples of companies and the primary metrics they track
Successful product-led companies often focus on a few key product metrics that align with their business objectives. Here are some examples of companies and the primary metrics they track:
Slack: Slack, a popular team collaboration platform, tracks metrics such as daily active users (DAUs), the number of messages sent, and the number of active teams. These metrics help Slack understand user engagement and identify opportunities for product improvement.
Dropbox: Dropbox, a cloud storage and file-sharing service, focuses on metrics such as the number of active users, the amount of storage used, and the number of files shared. These metrics enable Dropbox to assess user engagement and drive growth.
Atlassian: Atlassian, the parent company of products like Jira and Trello, tracks product metrics specific to each product. When looking across products, though, they measure W2WAI (Week 2 Weekly Active Instances), organic traffic, free signups, and freemium conversion rate. These metrics help Atlassian understand product activation make data-driven decisions about their content strategy.
Keeping metrics accurate and reliable
Product metrics are useless if they're not accurate and reliable. Here are some tips to help ensure the accuracy and reliability of your metrics:
Establish consistent measurement methodologies: Getting your company aligned on metric definitions is very important. We recommend having some single source of truth where anyone in the company can learn how each metric is calculated. Define the methodologies and data sources that will be used for each metric and ensure that they are consistently followed.
Implement data validation processes: Implement processes and checks to validate the data used in your metrics. This may include data cleansing, data transformation, and data reconciliation processes. This is an advanced practice and likely isn't necessary until there are multiple analysts at a company.
Use reliable data sources: Ensure that the data you use to calculate your metrics comes from reliable sources. Tools that track events directly, like Flywheel, provide metadata for every event to help with troubleshooting.
Regularly audit your metrics: Perform regular audits of your metrics to identify any inconsistencies, errors, or gaps in your data. Address any issues identified during the audit to maintain the accuracy and reliability of your metrics. We recommend setting up event alerts to help recognize issues early.
Monitor and maintain your data infrastructure: Ensure that your data infrastructure, such as databases and data pipelines, are properly maintained and monitored to prevent data loss or corruption.
Fin
At this point, you've learned the basics of product analytics and key product metrics for PLG and B2B SaaS. Next, we'll walk through how to visualize and monitor these metrics with product analytics dashboards.
Published on
May 10, 2023
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