11 quantitative and qualitative product adoption metrics to track
Ok, so to kick off, let’s dive into each metric, breaking down what it measures, how to calculate it, and what actions you can take based on your findings.
1. Product Adoption Rate
What is product adoption rate and why does it matter?
Product adoption rate is a metric that measures the percentage of new users who have adopted your product within a given timeframe. It’s a solid indicator of how effectively your product resonates with its intended audience, showing if users are reaching that “aha” moment.
How to calculate or track the metric
Measure product adoption by dividing the number of users who have engaged meaningfully with the product by the total number of new users, then multiply by 100 to get a percentage.
Formula:
Product Adoption Rate = Active New Users / Total New Users × 100
What high or low values mean
A high adoption rate indicates that your product is meeting user needs, while a low rate suggests friction in the onboarding flow or unclear value propositions.
Actions to improve or iterate
Streamline the onboarding process to ensure new users quickly understand the product’s benefits. Trigger in-app guides and tooltips to help users navigate complex features and reach the "aha" moment faster. This works whether you’re releasing a new product, or pushing new software to an established offering.
2. User Activation Rate
What the metric measures and why it matters
Activation rate measures the percentage of users who complete a specific set of key actions that indicate they’ve reached a “first success” moment in your product. This metric is essential because it reflects whether new users are getting value out of the product quickly enough to keep them engaged. For many SaaS products, a user’s early experience often determines if they’ll continue using the product long-term.
How to calculate or track the metric
To calculate activation rate, define the actions that indicate a user has reached their “aha moment” and track how many users complete these steps shortly after signing up. Common actions might include completing a tutorial, setting up a profile, or using a core feature.
Formula:
Activation Rate = (Users Who Reach Activation / Total New Users) × 100
What high or low values mean
A high activation rate suggests that users are successfully adopting core features and are likely finding value in the product early on. Conversely, a low activation rate could mean users are encountering friction points, getting lost during onboarding, or failing to understand the product’s benefits.
For example, if only 30% of new users reach activation within their first day of signing up, it might signal issues with the onboarding process, such as unclear instructions or too many steps required to experience initial value.
Actions to improve or iterate
To boost activation rates, streamline the onboarding process by highlighting only the essential steps to reach that “aha moment.” Consider adding guided tutorials, tooltips, and checklists to lead users toward activation more efficiently.
Sprig’s session recordings and heatmaps can be invaluable for identifying areas where users get stuck or confused, enabling product teams to make data-driven improvements to the onboarding flow. Additionally, using in-app messaging to encourage users through these key actions can increase the likelihood of reaching activation.
Replays results page in Sprig — Sprig AI instantly analyzes and groups session clips into themes to uncover patterns in your users' behavior.The results page of a Heatmap study in Sprig — including the AI Summary and heatmap, scrollmap, and clickmap data.3. Customer Satisfaction Score (CSAT)
What the metric measures and why it matters
CSAT measures how satisfied customers are after specific interactions, providing a quick pulse on user sentiment and areas for improvement.
How to calculate or track the metric
After an interaction (like completing onboarding or using a new feature), survey users to rate their satisfaction on a scale of 1-5. Calculate CSAT by dividing positive responses (4s and 5s) by the total number of responses.
What high or low values mean
A high CSAT score reflects strong user satisfaction, while a low score signals a need for improvement in user experience or product functionality.
Actions to improve or iterate
Use low CSAT scores as prompts for deeper analysis—like, let’s say you’ve got a great landing page and a high conversion rate, but then people aren’t sticking around. After identifying a drop-off in satisfaction, use tools like session recordings to watch how users engage with the interface and where friction occurs.
Pro Tip: Trigger user surveys after key events to gather timely insights. For example, after completing onboarding, ask users if they feel ready to use the product. (Note: Sprig offers a free CSAT template to help get you up and running.)
4. Customer Effort Score (CES)
What the metric measures and why it matters
CES measures the effort a user feels they had to put into an interaction, like setting up an account or resolving an issue with customer support. The lower the effort, the better the experience.
How to calculate or track the metric
Survey users on how easy or difficult an action was on a scale of 1-7. Calculate CES by averaging scores across users.
What high or low values mean
A low CES suggests a smooth, user-friendly experience, while a high score indicates potential barriers that could hinder product adoption.
Actions to improve or iterate
To lower CES, analyze the user journey to identify and remove friction points. Consider in-app tooltips or walkthroughs to simplify complex steps. (Note: Sprig offers a free CES template that you can customize and drop into your product experience quickly and easily.)
5. Net Promoter Score (NPS)
What the metric measures and why it matters
NPS assesses user loyalty by asking how likely they are to recommend the product on a scale of 0-10. It’s a valuable insight into customer loyalty and satisfaction.
How to calculate or track the metric
Survey users, then classify responses: promoters (9-10), passives (7-8), and detractors (0-6). Subtract the percentage of detractors from promoters to get your NPS score.
What high or low values mean
A high NPS suggests high user satisfaction and strong word-of-mouth potential. A low NPS might indicate unmet user needs or a poor customer experience.
Actions to improve or iterate
Use qualitative feedback from detractors to pinpoint issues. Address these through UI improvements, feature updates, or customer support adjustments. (Note: This is where Sprig’s continuous feedback tools and surveys can be a real boon to your product analysis! You can also get started with Sprig’s free NPS survey template.)
Results page of a drop-off analysis Survey in Sprig — Sprig AI analyzes all responses to generate a study summary and key takeaways.6. Feature Adoption Rate
What the metric measures and why it matters
This metric tracks the adoption of specific features by users, helping product managers understand the value and usability of each feature.
How to calculate or track the metric
Divide the number of users engaging with a feature by the total active users, then multiply by 100. Here’s the formula, just for clarity’s sake:
Feature Adoption Rate = Users Engaging with Feature / Total Active Users x 100
What high or low values mean
High feature adoption shows strong user engagement and value recognition. Low adoption can indicate issues with discoverability or unclear instructions.
Actions to improve or iterate
Consider adding in-app prompts to guide users to new features and simplify the learning curve.
Pro Tip: Collect qualitative data from users who drop off when attempting new features. Trigger automated surveys to capture insights and analyze the data to find common themes.
7. Time to Value (TTV)
What the metric measures and why it matters
TTV measures the time it takes for a user to experience the value of the product. Shorter TTV typically indicates a smoother onboarding flow and higher user satisfaction.
How to calculate or track the metric
Measure TTV from the moment a user signs up to when they complete a key action that provides value, like achieving a milestone or benchmark in the product.
What high or low values mean
A low TTV signals that users quickly understand the value of your product, likely reducing customer churn (more on that below). High TTV may reveal user onboarding inefficiencies or a need for better guidance.
Actions to improve or iterate
To reduce TTV, you should identify key actions that lead to early wins for users. Then, adjust onboarding to guide users directly to those actions and reduce the average time it takes for them to love your product.
Pro Tip: Run a heatmap or session recording study during key TTV actions to see where users get stuck.
8. Customer Retention Rate
What the metric measures and why it matters
The customer retention rate tells you what percentage of users stick around and continue using your product over a set period of time. This metric is a direct indicator of your product’s “stickiness” and can show how well your team is meeting the ongoing needs of your users. In a SaaS environment, high retention rates often lead to increased revenue through renewals and upsells, whereas low retention rates suggest issues in either the value proposition or the user experience.
How to calculate or track the metric
Calculate the customer retention rate by taking the number of active users at the end of a period, subtracting new users acquired during that period, and dividing by the number of users at the start of the period.
Formula:
Retention Rate = (Users at End of Period − New Users / Users at Start of Period) × 100
What high or low values mean
A high retention rate means your users are likely satisfied and see recurring value in your product. On the other hand, a low retention rate can indicate that users may not be realizing the full value of the product, or they’re experiencing friction points that lead them to stop using it.
For example, a B2B SaaS platform with a retention rate below 70% could signal that users aren’t regularly engaging with the software or encountering challenges that aren’t being resolved by customer support.
Actions to improve or iterate
To improve retention, focus on deepening the engagement users have with your product. Here’s where Sprig's heatmaps and session recordings can be invaluable. Analyze drop-off points in workflows, understand common pain points, and consider implementing an in-app messaging system to guide users through areas where they commonly get stuck. You can also run surveys to gather feedback on what improvements would keep them coming back.
9. Product Usage Frequency
What the metric measures and why it matters
Product usage frequency measures how often users are engaging with your product over a specific period. In a SaaS context, more frequent usage generally correlates with higher user satisfaction and retention. Product managers can gain insights into how essential their software is in daily workflows by tracking this metric, which helps prioritize features that drive regular engagement.
How to calculate or track the metric
This metric can be tracked by determining how many times a user logs into or interacts with the product in a given timeframe (e.g., daily, weekly, or monthly).
To determine product usage frequency, divide the total number of sessions by the number of users within the specified period. This can yield useful insights into DAU (Daily Active Users) and MAU (Monthly Active Users) ratios.
What high or low values mean
High usage frequency suggests that users find ongoing value in the product and see it as integral to their routines. Conversely, low usage frequency could indicate that users only find your product useful in limited scenarios or struggle to fit it into their regular processes.
For instance, a project management tool that’s only accessed once a month by most users may not be offering enough day-to-day value, signaling a need to re-evaluate its features or user journey.
Actions to improve or iterate
If product usage frequency is low, consider adding features that enhance daily relevance, like task reminders or integrations with other tools. Product teams could also use in-app notifications to suggest features based on the user’s role and activity. Testing these changes with session recordings or targeted surveys can offer real-time data on what’s working, helping to refine and increase regular user engagement.
10. Churn Rate
What the metric measures and why it matters
Churn rate measures the percentage of your user base who stop using your product over a specific period. For SaaS businesses, it’s one of the most critical metrics, directly impacting revenue. Understanding churn helps product teams address the reasons users leave, enabling them to proactively make improvements that enhance user retention and ultimately increase profitability.
How to calculate or track the metric
Calculate churn rate by dividing the number of users who stopped using your product by the total number of users at the beginning of the period.
Formula:
Churn Rate = (Users Lost in Period /Total Users at Start of Period) × 100
What high or low values mean
A high churn rate is typically a red flag, suggesting there may be unresolved issues such as a poor onboarding process, limited perceived value, or lack of engagement. On the other hand, a low churn rate means users are staying engaged and continue to find value in the product.
For example, if a SaaS company notices that 15% of users are churning every month, this could indicate a misalignment between the product's features and user expectations.
Actions to improve or iterate
To lower churn, begin by understanding the “why” behind user exits. Conduct exit surveys, analyze feedback, and use session recordings to track where and when users drop off. Sprig’s tools make it easy to gather data that can guide interventions. Improving the onboarding flow, adding educational content to highlight key product benefits, and iterating on user-requested features can all help reduce churn.
11. Customer Lifetime Value (CLTV)
What the metric measures and why it matters
Customer Lifetime Value (CLTV) represents the total revenue your company can expect from a single customer throughout their engagement with your product. This metric helps product managers and VPs understand which users contribute the most to long-term profitability and provides insights into what features or experiences boost customer loyalty.
How to calculate or track the metric
To calculate CLTV, multiply the average revenue per user (ARPU) by the customer’s average lifespan in months or years, then factor in retention rate and churn.
Formula:
CLTV = ARPU × Customer Lifespan
What high or low values mean
A high CLTV indicates that users are staying with your product long-term and generating substantial revenue. Low CLTV, however, may point to a misalignment between your pricing model and customer expectations, or it may suggest high churn.
For example, if a SaaS product shows an average CLTV of only a few months, the company may need to address user satisfaction and retention issues.
Actions to improve or iterate
Improving CLTV involves enhancing both product value and user engagement. Focusing on features that foster loyalty and upsell opportunities can encourage customers to stay longer and upgrade as their needs evolve.
Sprig’s insights help you understand user behavior around key features and identify areas for potential upsell. In-app prompts and tailored messaging at pivotal points in the customer journey—like right after a user completes onboarding—can also be effective strategies for boosting CLTV.
Building scalable insights with product adoption metrics
Tracking and optimizing product adoption metrics, from activation rates to customer lifetime value, can transform your understanding of user engagement and retention. By taking a balanced approach that includes both quantitative and qualitative data, you can capture the full story behind user behaviors.
With these metrics as your guide, you’re ready to create a product that not only attracts new users, but also retains and grows your customer base over the long haul.
Sprig’s suite of AI-driven analytics tools, including session recordings and heatmaps, allows SaaS companies to automate and scale this data gathering, ensuring that teams are equipped with the insights needed to build a more effective product adoption strategy.
Book a demo today to see how Sprig can help your team streamline your processes—from measurement, to analysis, to iteration.