Product adoption metrics tell you how well your platform is performing. By regularly tracking them, you can improve your in-app experience and drive higher feature adoption—which translates to more retention and customer loyalty.

In this article, we dived into 13 important adoption metrics to measure. You’ll see why they matter to your bottom line and the steps to start calculating them immediately.

TL;DR

• Product adoption occurs when new users understand the value of your product and begin using it as intended.
• Measuring your adoption rates will give you insights to boost free-to-paid conversion, retain more users, and turn customers into advocates.
• 13 product adoption metrics to measure:

1. Free-to-paid conversion rate
2. Time to value (TTV)
3. Activation rate
4. User onboarding completion rate
5. User engagement score
6. Feature adoption rate
7. Product stickiness
8. User retention rate
9. Customer churn rate
10. Net promoter score (NPS)
11. Customer satisfaction score (CSAT)
12. Expansion MRR rate
13. Customer lifetime value (CLV)

• Userpilot can help you understand in-app user behavior, track product usage data through feature tagging and heatmaps, and implement tactics to increase product adoption. Book a demo to learn more today!

What is product adoption?

Product adoption is the process by which new sign-ups become habitual users of a product and successfully use it to accomplish their goals.

Why should you measure product adoption?

Reaching product adoption is critical for subscription-based business models where revenue comes after the initial conversion.

Measuring your product adoption rate helps you identify and address loopholes to increase free-to-paid conversions and retain customers.

13 Key product adoption metrics and why they matter

You regularly need to track several metrics to get a holistic understanding of how users are interacting with and adopting your platform.

Below are 13 product adoption metrics and why they matter:

Free-to-paid conversion rate

This metric measures the percentage of free trial users who become paying customers. In other words, it tells you the number of users that consider your product valuable enough to pay for it.

Calculate your free-to-paid conversion rate by dividing the number of free trial users that converted over a specific period by the total number of free trial users in the same period.

Time to value (TTV)

TTV is the time it takes for a user to experience the true value of your product. Long TTV is one of the major causes of early churn.

There’s no universal formula for calculating time to value. To measure this metric, you must define which actions represent reaching value for your users and then count how long it should take to complete them.

Activation rate

The activation rate is the percentage of users that reach the activation point (experience value after engaging with your product) in their journey.

The activation point is different for each product and typically involves multiple actions. Another thing to know is that activation points can vary depending on the user persona and the job to be done.

For example, for an email marketing tool the activation point for a persona just starting out would be when they successfully created an account, added a contact list, wrote one email, and set an automation. They won’t see the value of the tool without completing these steps.

Calculate your activation rate by dividing the number of users who reached your activation milestone by the number that signed up within that period. Multiply by 100 to get the percentage.

User onboarding completion rate

Onboarding is critical to customer success and adoption. The more instructive and engaging your onboarding process, the higher your adoption rates.

One important thing to keep in mind is that user onboarding isn’t limited to new sign-ups. That’s just primary onboarding. There’s also secondary and tertiary onboarding to provide extra guidance to existing customers.

There are several ways to measure onboarding engagement:

User engagement score

High engagement is a sign that customers are happy with your product. By analyzing your highly engaged user groups, you can uncover the reason behind their deep engagement levels and replicate it on the least engaged cohorts.

You need to string together a series of key engagement events to get a correct customer engagement score. Do this by taking an overview of customer behavior on your app. Note all the steps/actions customers have to take at every key touchpoint to experience value.

Examples of events to track:

• Feature usage frequency
• Accounts added (or another related key action)
• Support tickets opened by a user
• Account upgrades and renewals

The idea is to note all events critical to a user’s success on your platform and assign values to each based on how important that event is.

For example, for an enterprise design tool, creating an account, adding teammates, and actually creating designs are more important than opening support tickets, so those first three interactions will have higher values than the last.

Here’s a table you can use:

Sum up the event values, and you have your user engagement score:

Feature adoption rate

This metric calculates the total number of users frequently interacting with a specific feature. Combining the adoption rates for key and secondary features gives you a clear understanding of which user groups are well-engaged and making progress on your app.

Regularly tracking feature adoption lets you know which features resonate more with users, and you can dig further to understand why customers don’t regularly interact with other aspects of your tool.

Calculate the feature adoption rate by dividing that feature’s monthly active users (MAUs) by the number of user logins in that period. Multiply the result by 100.

For example, imagine you had 200 monthly active users for your key feature in Q1 of 2023, and the average monthly login is 500.

Your feature adoption rate is:

200/500 X 100 = 40%

Product stickiness

Product stickiness is when customers find your product useful enough to engage with it regularly and renew/upgrade their subscriptions at the right time.

Stickiness is driven by transactional values like price, quality, etc., and a high number of active users shows you’re doing something right.

Measure product stickiness by calculating your platform’s daily active users (DAU) to monthly active users (MAU) ratio.

User retention rate

Retention measures the percentage of users who keep returning to your tool after a specific period. Increased retention means you’re meeting customer needs and have reached adoption.

On the other hand, low retention can mean three things for product adoption:

• Poor onboarding: Your onboarding flows didn’t properly communicate the product’s value, so users assume the tool isn’t for them.
• Poor customer product fit: You attracted the wrong audience through false promises or incorrect positioning.
• You’re not helping users get repeated value: It’s not just about activation; you need to prompt new feature discovery and consistently ensure users maximize your product.

How to calculate user retention rate:

Determine the period to measure retention (e.g., the past 3, 6, or 12 months).

Subtract the number of users acquired during that period from the number of paying users you had at the end of the period. Divide the answer by the number of paying users at the beginning of that period.

Imagine you had the following data:

• 800 users acquired in the past 12 months
• Before then, you had 1000 paying customers
• Adding everything, you had 1200 paying customers at the end of the 12 months (many left after the trial period, and some paying customers churned along the way)

Your user retention rate is: (1,200 – 800/1,000) X 100 = 40%

Customer churn rate

This metric calculates the number of users that stop doing business with you after a specific period.

High churn rates indicate low product adoption and are a sign that you need to improve the customer experience ASAP.

Here are the types of churn you should track for SaaS.

Customer churn rate is the percentage of customers that cancel their subscription within a given period.

You calculate this metric by dividing the number of customers at the start of the period by the number that churned during the period and multiplying by 100.

Net promoter score (NPS)

NPS is one of the few product adoption metrics that help you gauge customer sentiment and measure loyalty.

NPS surveys involve asking users, on a scale of 0-10, how likely they are to recommend you to others. Users are grouped into promoters, passives, and detractors based on their responses. And the NPS score is the difference between the percentage of promoters and the percentage of detractors.

Combining NPS scores with product usage data for each response segment allows you to spot behavioral patterns across different segments and understand why some users adopt your product (promoters) or don’t (detractors).

Customer satisfaction score (CSAT)

The satisfaction score is measured in-app with CSAT surveys at different touchpoints to get a granular understanding of customer satisfaction/dissatisfaction.

Users will be unmotivated to progress and adopt your tool if unsatisfied with their experience. By measuring customer satisfaction at every touchpoint, you’ll understand where the friction lies and make improvements to drive product adoption.

Calculate your CSAT score by finding the ratio of happy customers to the number of customers asked.

Expansion MRR rate

This is the additional revenue generated from existing customers in the current month. Expansion revenue typically comes from upsells and cross-sells.

Account expansions result from user growth and are strong indicators of adoption. It means your product meets user needs, they are getting repeated value from it while they grow.

Calculate your expansion MRR rate by finding the difference between the expansion MRR at the end of the month and what you had at the beginning. Then divide by the expansion MRR at the beginning of the month and multiply by 100.

Customer lifetime value (CLV)

CLV is the total worth of a customer to a business over the course of their relationship. This metric helps you see how user adoption benefits the bottom line—the average customer lifetime value increases as users adopt your platform and stick around for longer.

There are many ways to calculate CLV, but a common approach is to find the ratio of the average revenue per account to the customer churn rate:

Tracking product adoption metrics with Userpilot

Userpilot is a no-code product growth platform with features to help you measure and improve product adoption metrics. Here’s how our platform can help:

Understand in-app user behavior

Userpilot’s pages feature lets you see how users interact with every page of your app.

That way, you can see what’s being used but not adopted and contextually trigger a flow to prompt adoption.

Track product usage data through feature tagging and heatmaps

Do you want to track engagement for specific features on your platform?

Userpilot’s feature tags let you do that with ease. You can tag as many UI elements as you want and monitor how users engage with them. Through this, you’ll identify the most used and unused features and try to find any trend affecting engagement.

Userpilot also has feature heatmaps that show you a map of all the clicks on a screen based on the feature tags you added:

Conclusion

Product adoption is key to ensuring customer retention and loyalty.

You can’t achieve high adoption rates overnight, but regularly tracking your adoption metrics will show you how to grow. Always remember to be customer-centric in every strategy you deploy and keep an open mind because you may have to make many tweaks.

Ready to start tracking key product adoption metrics? Get a Userpilot Demo and see how our platform can help!