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Product Usage: Metrics, Analysis, and Strategies (with Examples)
Discover how product usage data reveals valuable insights into user behavior, letting you craft better user experiences, increase retention, and foster growth.
Understanding how users interact with your product can provide valuable insights to enhance their engagement even further.
This primer aims to help you understand product usage, how to grow it, and what you can do with the insights you gather.
We’ll cover:
- A definition of product usage
- The key metrics you should track to measure product usage
- Methods of analyzing product usage
- Examples of product usage analysis in three use case scenarios
- Some tips for improving product usage
Let’s get started.
What is product usage?
Product usage is the data that tells you how your customers interact with your product. It's like a window into their behavior, revealing when they use your product, which features they engage with the most, and how long they spend on each task.
This data can be collected from a variety of sources, including in-app tracking, user surveys, and customer support interactions.
Product usage data serves a crucial purpose for businesses. It helps companies gain a deeper understanding of user behavior, identify areas for improvement, and ultimately create a better product.
Key metrics for measuring product usage
To truly understand how your product is being used, it's important to track key product usage analytics that provide a complete view of user behavior and engagement.
Here are some of the most important product usage metrics you should be monitoring:
Daily Active Users (DAU)
DAU measures the number of unique users who interact with your product on a daily basis. This metric offers a snapshot of your product's daily health and popularity. It can be used to identify trends, fluctuations, and potential issues in user engagement.
A unique user is usually defined as an individual who interacts with the product at least once within a 24-hour period, regardless of how many times they engage. Keep in mind that what counts as “active” will vary according to your product’s intended use.
How to calculate it
DAU = Number of unique users who interacted with the product in a day
Example: A mobile game developer tracks DAU to see how many players log into their game each day. If 1,200 different players accessed the game on June 5th, the DAU for June 5th would be 1,200.
Monthly Active Users (MAU)
MAU measures the number of unique users who interact with your product within a month. This metric provides a broader view of user engagement over a longer time frame. It's helpful for understanding overall growth trends, seasonal variations, and the long-term health of your product.
How to calculate it
MAU = Number of unique users who interacted with the product in a month
Example: An e-commerce platform might track MAU to assess overall website traffic and customer engagement. If 15,000 different users visited the site and made purchases in May, the MAU for May would be 15,000.
Session duration
Session duration measures the average length of time users spend in a single session with your product. It's a valuable metric for understanding user engagement levels and identifying potential areas for improvement in the user experience.
A session typically starts when a user opens the app or website and ends after a period of inactivity (e.g., 30 minutes).
How to calculate it
Average session duration = Total time spent by all users in a given period / Total number of sessions in that period
Example: A social media app tracks session duration to see how long users typically spend on the platform during each visit. If users collectively spent 50,000 minutes across 5,000 sessions, the average session duration would be 10 minutes.
Feature usage
Feature usage tracks how often specific features within your product are used. By understanding which features are most popular and which ones are underutilized, you can make data-driven decisions about product development and prioritize enhancements that will have the greatest impact on user satisfaction.
How to calculate it
Feature usage = Number of times a specific feature is used
Example: A project management tool tracks feature usage to see how often users create new tasks, assign tasks to team members, and use the calendar view. If the "create task" feature is used 1,000 times in a week, that's the feature usage for that week.
Retention rate
Retention rate measures the percentage of users who continue to use your product over a specified period. It's a critical metric for understanding the long-term value of your product and identifying areas where you might be losing users.
How to calculate it
Retention rate = (Number of users at the end of a period who were also present at the start of the period / Number of users at the start of the period) * 100
Example: If 1,000 users sign up for a free trial of a software product and 400 of them are still using it after a month, the one-month retention rate is 40%.
Churn rate
Churn rate is the opposite of retention rate and measures the percentage of users who stop using your product over a specified period. It's an essential metric for understanding customer attrition and identifying areas where you can improve customer satisfaction and retention.
How to calculate it
Churn rate = (Number of users who churned during a period / Number of users at the start of the period) * 100
Example: If a music streaming service had 50,000 subscribers at the beginning of a quarter and lost 2,500 subscribers during that quarter, the churn rate would be 5%.
Engagement rate
Engagement rate measures how actively users are interacting with your product. It can encompass a variety of actions depending on the nature of your product, such as comments, likes, shares, time spent on specific features, or the number of tasks completed.
How to calculate it
Engagement rate = (Total number of specific actions taken by users / Total number of users) * 100
Example: An e-commerce website tracks engagement on a product page by measuring actions like "Add to Cart," "Add to Wishlist," and time spent on the page. If 1,000 users viewed the product page, 50 added it to their cart, and 20 added it to their wishlist, the engagement rate would be 7% (calculated as (50 + 20) / 1000 * 100).
What methods are there for analyzing product usage?
User analytics tools
These tools provide a wealth of information about how users interact with your product. They track user actions, such as button clicks, page views, and feature usage, allowing you to identify patterns, trends, and areas for improvement.
Popular tools like Google Analytics, Mixpanel, and Amplitude offer various features for data visualization, segmentation, and cohort analysis.
- Example: Using Amplitude, a product team can track how user engagement changes over time, identifying which features drive the most interaction and where users tend to drop off.
Heatmaps
Heatmaps are visual representations of where users click, scroll, and hover their mouse on a webpage or app screen. They use color coding to indicate areas of high and low engagement. This information can inform future changes which can improve the overall user experience.
- Example: A website owner might use Hotjar to create a heatmap of their landing page. This could reveal that users are clicking on an image that isn't linked, prompting them to make it clickable to improve navigation.
User surveys and feedback
Gathering direct feedback from users is a crucial part of understanding their needs and pain points. Surveys and feedback forms can provide qualitative data that complements the quantitative data from analytics tools. You can ask users about their experience with specific features, what they like and dislike, and what they would like to see improved.
- Example: A software company might send a survey to users who recently canceled their subscription to understand why they left and what could be done to improve the product.
A/B testing
A/B testing involves creating two or more versions of a feature or page and comparing their performance. This allows you to see which version resonates better with users and leads to higher engagement or conversion rates.
- Example: An e-commerce platform might use Eppo’s sophisticated A/B testing to compare two different checkout flows. They could track metrics like conversion rate and cart abandonment to determine which flow is more effective.
Three specific examples of product usage analysis in action
Product usage analysis can be applied across various industries and product types to gain valuable insights and drive improvements. Let's explore three specific examples:
E-commerce platform
Product usage analysis plays a crucial role in making the customer journey on an e-commerce platform much better. By tracking user journeys from the landing page to checkout, businesses can identify friction points and areas for improvement.
For instance, analyzing drop-off points in the purchase funnel can reveal where customers are abandoning their carts, allowing the company to address issues like confusing navigation or unexpected shipping costs.
An e-commerce platform might discover that a high percentage of users abandon their carts during the shipping information step. This could indicate that the shipping costs are too high or that the shipping options are unclear.
Mobile app
For mobile apps, product usage analysis focuses on monitoring feature usage and session duration. By understanding which app features are most popular and which ones are underused, developers can prioritize enhancements and ensure that the app delivers value to its users.
Analyzing session duration can also help identify areas where users might be getting stuck or losing interest, leading to improvements in the app's flow and overall user experience.
A fitness app might find that users rarely access the "meal planning" feature. This could suggest that the feature is difficult to find or that it doesn't meet user needs. The developers could then redesign the feature or promote it more to increase usage.
Content platform
On content platforms, product usage analysis involves tracking content engagement and user interaction. This includes metrics like views, likes, shares, comments, and time spent on each piece of content.
By understanding which types of content click most with users, platforms can tailor their content strategy to deliver more of what their audience wants, ultimately increasing engagement and retention.
A news website might discover that articles with video content receive significantly more engagement than text-only articles. This insight could lead them to invest in producing more video content to attract and retain readers.
Ways to make your product usage metrics grow
Improving product usage involves a multifaceted approach that focuses on understanding and catering to your users' needs. Here are some effective strategies to boost your product usage metrics:
Focus on the onboarding experience
A smooth and intuitive onboarding process is vital for getting new users up to speed quickly. This isn't just about creating a visually appealing tutorial; it's about guiding users to their "aha moment" — the point where they truly understand the value your product offers.
Consider using interactive walkthroughs, checklists, and tooltips to highlight key features and guide users through essential tasks. Break down complex processes into manageable steps, and offer timely support and resources to address any questions or challenges.
- Example: A project management tool could incorporate an interactive checklist that guides new users through creating their first project, adding team members, and assigning tasks.
Treat UX as one of your top priorities
A positive user experience is the cornerstone of user retention and long-term product success. It encompasses everything from intuitive navigation and clear instructions to visually appealing design and fast loading times.
Regularly collect user feedback through surveys, in-app messages, and user testing to identify and address any friction points or usability issues.
- Example: An e-commerce site could streamline the checkout process by consolidating multiple pages into a single, easy-to-follow form. Offering guest checkout options and multiple payment methods can further reduce friction and improve conversion rates.
Personalize the user experience
One size doesn't fit all when it comes to user experience. By analyzing product usage data, you can segment your users based on their behavior, preferences, and goals. Leverage this information to deliver custom recommendations, content, or features that resonate with each user segment.
- Example: A music streaming app could analyze a user's listening history and create custom playlists tailored to their musical taste. It could also suggest new artists or genres based on their preferences, enhancing the overall listening experience.
Make sure feature updates and improvements are always on the horizon
Stagnation is the enemy of growth. Regularly update your product with new features, improvements, and bug fixes to keep users engaged and excited.
Use product usage data to spot areas where your product could use a few extra improvements, and gather feedback from users to make sure that your updates align with their needs and expectations.
- Example: A social media platform could introduce new interactive features like polls or Q&A sessions to encourage user participation and create a more dynamic experience.
Next steps
So you want to make your product usage grow. You know what it is, which metrics you should be tracking, and how to calculate them. But now, new questions will start cropping up, like:
How can I track these metrics and make sure the data is trustworthy?
Once I track these metrics, how can I use them to run experiments?
Will my experimentation tool be able to manage large influxes of data?
To set you on the right path to find the answers, we encourage you to give Eppo a shot.
Eppo is an experimentation and feature management platform that’s built with statistical rigor in mind. It can help you make the most out of your data and give you enough confidence to make critical data-based decisions.
Let’s take a look at how Eppo can help:
- Uncover the full story of product usage: Go beyond vanity metrics and dive into the details of how users interact with your product. Track custom events, analyze feature adoption, and find areas of friction with Eppo's event tracking and analysis capabilities.
- Make data-driven decisions with confidence: Eppo's direct integration with your data warehouse ensures that your product usage metrics are accurate, reliable, and consistent with your core business metrics.
- Experiment with precision and speed: Leverage Eppo's advanced experimentation framework to test new features, UI changes, or onboarding flows with statistical rigor. Eppo's powerful engine helps you quickly identify winning variations and roll them out to your entire user base with confidence.
- Drive continuous improvement with a data-centric culture: Eppo's centralized platform allows your entire team to access and analyze product usage data. Easily share insights, collaborate on experiments, and continuously iterate on your product.
- Optimize for the metrics that matter: Eppo lets you define and track custom metrics. By focusing on the metrics that truly impact your bottom line, you can create personalized user experiences to optimize outcomes.
Discover how product usage data reveals valuable insights into user behavior, letting you craft better user experiences, increase retention, and foster growth.
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