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To measure retention and user engagement, you might have heard of measuring stickiness with the popular DAU/MAU ratio.
Here’s where it may disappoint you, though…
- It’s not suitable for products where daily engagement isn’t the norm, such as B2B tools used only on workdays.
- It fails to highlight variability among users, making it difficult to see who’s slightly active versus who’s a power user.
- It doesn’t show what drives engagement, as it averages all activity into a single number. This hides which features or actions users value most and where they encounter friction
Instead, the Power User Curve will reveal all of this and more.
In this blog, you’ll learn:
- What the Power User Curve is and why it’s better than traditional metrics like DAU/MAU.
- How to interpret different curve shapes and what they mean for your business.
- How to use the Power User Curve to track trends, improve retention, and guide product development.
What Is a Power User Curve?
The Power User Curve is basically an activity histogram (that looks like a bar chart) revealing the distribution of user activity over a certain time period.
- For example, for a fitness tracking app, you could find out what percentage of users (within the same month) log in a workout once, what percentage does it twice, and so on.
The term was popularized by Andrew Chen and Li Jin. A monthly Power User Curve is sometimes called the L30 curve and a weekly one L7 (short for “last 7/30 days,” originally coined by the Facebook growth team).
The curve shows the distribution of engagement levels among all your users: from power users to the more inactive ones.
Power User Curves show if your product is resonating with a core group of highly engaged users, even when overall engagement metrics like DAU/MAU seem low. They can go beyond app opens or logins, focusing on actions that deliver value to users.
The key is to tailor the curve to meaningful metrics for your product and track it over time or against benchmarks in your category to see what’s working—and what’s not.
How to Analyze the Curve
The shape of your Power User Curve reveals key insights into user engagement. Whether you're looking at monthly trends (L30) or weekly activity patterns (L7), understanding the curve shape helps you identify strengths and opportunities for improvement.
The x-axis in the chart represents the number of active days, and the y-axis is the percentage of users who engage with the product. So, for example, if 200 out of your 1000 overall users are using your product only on one day within a month, day 1 would show 20%. Or, if no one uses your product every day of the month, we would see a 0% measurement for day 30 on the chart.
(1) Left-Leaning Curve: A Possible Warning Sign
What It Means
A left-leaning curve indicates that most users are lightly engaged, performing the goal action only a few times in the given timeframe. Power users are rare or nonexistent.
For products that rely on consistent engagement, such as collaboration tools or habit-forming apps, this curve typically highlights missed opportunities.
However, this shape may be acceptable if your product is designed for sporadic use. For example, tax software or event planning tools might naturally see lower usage frequencies.
Example
For a language-learning app, a left-leaning curve might show that users log in rarely, perhaps only before an upcoming trip. They may not engage with features like daily practice reminders or gamified challenges that could deepen their involvement with the app.
What to Do If You Want to Activate Users More
To address a left-leaning curve, focus on strategies that encourage consistent use and build stronger habits:
1) Improve Onboarding to Highlight Core Features
Help users immediately understand how your product fits into their daily workflows.
- Example: For a file-sharing platform, show users how to use collaboration tools or automate file organization during onboarding.
2) Re-Engage Infrequent Users
Use targeted campaigns to bring users back and encourage more consistent engagement.
- Example: For a food delivery service, send push notifications highlighting limited-time discounts or new restaurant options in the user’s area.
3) Promote Underused Features
Spotlight valuable but overlooked features to enhance the product’s relevance.
- Example: A fitness app could promote its meditation or sleep-tracking tools to users who only log workouts, encouraging them to explore additional benefits.
4) Integrate Into Existing Workflows
Add integrations or features that make your product indispensable.
- Example: A document editing tool could integrate with cloud storage platforms, allowing users to seamlessly access and edit files from anywhere.
What to Do If You’re Okay With Less Frequent Usage
When engagement is low, businesses need to focus on delivering significant value during the moments users are active.
Consider an online education platform or a travel booking app—users might only log in occasionally, but these companies maximize revenue by offering premium courses, trip insurance, or upselling experiences during those limited interactions.
(2) Smiling Curve: A Reason to Smile
What It Means
A smiling curve reflects balanced engagement, with a strong group of power users who engage frequently (e.g., 20-30 days in L30) and a significant base of casual users who engage occasionally (e.g., 1-5 days in L30). This curve suggests that your product serves a dual audience effectively: both those who rely on it daily and those who use it occasionally but still find value.
A smiling curve is a positive indicator, but it also reveals room for growth—particularly by converting casual users into more frequent ones and strengthening mid-level engagement.
Example
For a fitness app, a smiling curve might show power users logging workouts almost daily, while casual users log in only after group classes or to track specific exercises, such as a weekly run.
This reflects two distinct patterns of engagement: consistent users who rely heavily on the app and occasional users who engage only when they need specific functionalities.
What to Do
1) Encourage Casual Users to Engage More Frequently
Casual users may not fully grasp how the product can fit into their routines or provide consistent value. Use personalized prompts, gamification, or in-app guidance to nudge them toward more frequent use and higher-value workflows. Highlight features that align with their goals and simplify their daily tasks.
- Example: For a fitness app, introduce streak challenges to motivate users to log workouts regularly, helping them build a habit of engaging with the app more consistently.
2) Reward and Retain Power Users
Ensure power users feel valued and have access to premium tools or exclusive benefits. This not only retains them but encourages advocacy.
- Example: For a language learning app, offer power users access to advanced lessons, live tutoring sessions, or exclusive content like cultural deep-dives and mini-games to keep them engaged and motivated.
A Smiling L7 Curve Looks Different
In an L7 curve, the "smile" typically shifts earlier in the timeframe, with strong engagement during weekdays (Days 1-5) and lighter activity on weekends.
The L7 curve is most relevant for products where engagement is tied to a typical workweek, such as B2B tools, collaboration platforms, or professional software. For these products, daily engagement isn’t expected on weekends, making an L7 curve a better fit than L30.
(3) Right-Leaning Curve: Dominated by Power Users
What It Means
A right-leaning curve signifies that a large proportion of users engage frequently, with power users dominating the curve. This is a positive indicator of strong retention and habit formation within a dedicated core audience.
However, it may also indicate a challenge: while your product works well for a loyal group of frequent users, it may not be connecting as effectively with less engaged users. These occasional users might not yet understand the product’s value or find it easy to fit into their routines.
Example
For a social media platform, a right-leaning curve might show that most users log in nearly every day to interact with posts, check updates, or contribute content.
This pattern reflects strong retention and habit formation, driven by features that encourage daily activity, such as notifications, trending topics, or personalized feeds.
What to Do
If you want to address the gap between power users and casual users but keep your current power users happy, consider these strategies:
1) Nurture Power Users to Maintain Loyalty
Strengthen your relationship with power users by providing exclusive content, tools, or experiences that reward their loyalty.
- Example: For a fitness app, provide advanced performance tracking dashboards or personalized coaching plans to keep avid users loyal and engaged.
2) Re-Engage Casual Users
Focus on bringing casual users into the fold by making the product’s value more apparent.
- Example: Use personalized email campaigns or notifications to remind infrequent users about trending content or missed opportunities to engage.
3) Optimize Features for Broader Appeal
Review which features power users rely on and adapt them to serve less engaged users.
- Example: Simplify complex tools like content creation or sharing features to encourage casual users to participate more actively.
4) Maintain Healthy Engagement for Ultimate Power Users
Focus on sustaining or growing the number of highly active power users while avoiding the risks of over-engagement or burnout. Encourage consistent, meaningful use without promoting habits that could lead to dissatisfaction or churn.
- Example: Introduce wellness features, such as reminders to take breaks, to ensure long-term retention without overwhelming users.
Multiple Curves
The power user curve doesn’t just offer a snapshot of user engagement—it becomes even more insightful when compared across multiple timeframes. By analyzing month-over-month trends, you can uncover critical moments when user behavior shifted, evaluate the impact of product updates, and identify areas to double down on.
Ideally, you would see a trend of users shifting more and more to the right side of the chart.
What to look for
Identify Critical Inflection Points: When you notice a sudden increase or improvement in engagement (e.g., October and November showing growth in the middle-to-late active days), it might correlate with a successful product launch or marketing push. These are key areas to replicate or expand on.
Track New Cohorts for Gradual Growth: For products with network effects, such as marketplaces or social media platforms, newer cohorts may start with lower engagement but improve as network density increases. Month-over-month comparisons let you monitor whether these cohorts are catching up to older, more engaged ones.
Diagnose Retention Challenges: A decline in engagement could highlight friction points or indicate areas where users lose interest. These insights can guide re-engagement campaigns or feature tweaks to maintain user attention. In the data above, there’s a clear drop in December’s activity curve, which aligns with the holiday season. Understanding these natural fluctuations helps you set realistic expectations and adapt strategies during predictable slow periods.
Weekly vs. Monthly Measuring
Different products have different engagement patterns, so it’s important to choose the right timeframe for measuring user activity. While the L30 curve (30-day) captures broader monthly trends, the L7 curve (7-day) is better suited for tools that align with weekly workflows.
L30 (30-Day Curve): Best for Products with Long-Term Engagement
The L30 curve is ideal for products where monthly activity is a meaningful measure of engagement. This includes apps or services where users interact at varying frequencies but don’t necessarily engage daily.
Examples:
- Fitness Tracking Apps: Users may log workouts sporadically but stay engaged across the month.
- E-Commerce Platforms: Customers might make purchases or browse deals a few times a month.
- Streaming Services: Viewers may binge-watch a few times a month or consume an episode or two daily.
- Social Media Platforms: Many users log in every day to stay connected, interact with posts, or share updates.
L7 (7-Day Curve): Best for Work-Week Engagement
The L7 curve works well for B2B tools or other products designed for regular, work-related use over a typical Monday-to-Friday schedule. These tools aren’t expected to engage users on weekends or holidays.
Examples:
- Team Collaboration Tools: Apps like Slack or Asana are used almost exclusively during workdays.
- Productivity Software: Tools like Google Workspace or project management platforms align with work schedules.
- Sales CRM Tools: Platforms like Salesforce are heavily used during work hours for tracking leads and managing sales pipelines.
Bonus Tips
Here are some more actionable tips you can use to get the most out of your Power User Curves.
(1) Analyze Curves by Cohorts
The Power User Curve provides an overall view of engagement, but segmenting by cohorts can reveal patterns unique to specific user groups.
How: Break down your curve by user demographics, activity type, or geographic location using analytics tools.
Example: A language-learning app could analyze engagement by country or language pair to identify which regions or language combinations have the highest activity. Investing in additional content, gamification, or marketing for popular language pairs, like English-to-Spanish, would further boost engagement.
By identifying cohort-specific behaviors, you can tailor your product offerings or marketing campaigns to meet diverse user needs, driving more personalized engagement and stronger retention across all segments.
(2) Highlight Power User Success Stories
Your most engaged users can act as role models, showing casual users how your product delivers value and encouraging them to explore more features.
How: Share real-life use cases, case studies, or in-app prompts that showcase power users' achievements and how they maximize your product’s capabilities.
Example: A project management tool could feature a case study about a user who reduced task completion time by automating workflows, inspiring others to try automation features.
By highlighting success stories, you not only motivate casual users to deepen their engagement but also build trust and credibility around your product.
(3) Dive Deeper into User Behavior
The Power User Curve provides a snapshot of engagement levels, but it doesn’t explain why users behave the way they do. Digging into behavioral data uncovers the motivations, pain points, and barriers driving user actions.
How: Use advanced analytics like feature tagging, heatmaps, or session recordings to analyze specific interactions and uncover patterns in user behavior.
Example: If users frequently navigate to a feature but drop off before completing an action, conduct usability testing to understand whether the issue lies in unclear instructions, design flaws, or unmet expectations.
This deeper understanding can help you refine your business model, build better re-engagement strategies, or double down on features power users value most.
(4) Personalize In-App Experiences for Different User Segments
Not all users interact with your product the same way. Personalization ensures every segment achieves their goals efficiently, leading to higher satisfaction and retention.
How: Segment users based on their goals or use cases, then customize onboarding flows, recommendations, or dashboards to align with their needs.
Example: A task management app could include an onboarding survey asking users whether they want to "organize personal tasks," "manage a small team," or "coordinate large projects." Based on the response, casual users might see a simple task list interface, while power users managing complex team workflows would be introduced to advanced features like analytics and resource allocation tools.
Tailoring the experience to each segment helps users see immediate value, reducing churn and encouraging more consistent engagement.
(5) Remove Friction in the User Journey
Users often disengage when they encounter obstacles or complex workflows. Identifying and removing these friction points makes the experience smoother and more enjoyable.
How: Use tools like session recordings and usability testing to pinpoint where users struggle, then simplify or streamline those areas.
Example: For a subscription-based streaming service, a confusing sign-up process could lead to drop-offs. Simplifying account creation with fewer steps or adding a single-click sign-up option can improve retention.
Eliminating friction boosts user satisfaction, improves retention rates, and helps casual users become power users over time.
Conclusion
The Power User Curve offers a more nuanced and actionable way to measure user engagement compared to traditional metrics like DAU/MAU. By visualizing the distribution of user activity, it helps uncover critical insights about your product’s strengths, weaknesses, and opportunities for growth. Whether your curve is left-leaning, smiling, or right-leaning, each shape provides valuable lessons about user behavior, retention, and engagement patterns.
Through this blog, we’ve explored how to interpret different curve shapes, align your strategies with user behaviors, and use actionable tips to enhance both retention and engagement. From addressing sporadic usage to leveraging cohort analysis, showcasing success stories, and personalizing experiences, the Power User Curve equips you with the tools to build a product that resonates with users and supports long-term growth. Now it’s your turn to apply these insights and turn your engagement data into meaningful outcomes.
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