How to Analyze Feature Usage and Gain Valuable Insights in SaaS
How can you analyze feature usage to understand your users’ behaviors and needs better?
Armed with the right product analytics tool, you can analyze how users engage with specific features and functions, unlocking a treasure trove of insights that can transform your product and business.
In this article, we walk you through everything you need to know about analyzing feature usage and its relevant metrics.
Summary of how to analyze feature usage in SaaS
- Feature usage examines everything relating to how a product feature is used.
- Tracking feature usage provides insights that help you prioritize product development, enhance the user experience, improve engagement, and drive retention.
- The feature usage rate is the total number of users who have used a feature divided by the total number of product users, multiplied by 100.
- To conduct an in-depth feature usage analysis, you’ll need metrics like the number of active users, number of feature users, time frame under consideration, etc.
- Next, you’ll need to collect relevant data with an analytics tool. This may involve tracking custom events, tagging in-app elements, and getting deeper insights with heatmaps and user surveys.
- The next phase of your analysis involves observing the tracked user behavior on a graph or chart to identify patterns and trends.
- For a better understanding of user behavior, you’ll need to observe how user engagement varies for different user segments.
- Finally, create a retention table to analyze the impact of your observed feature on product retention rates.
- In addition to aiding the collection of valuable product data through surveys and in-app tracking, Userpilot enables you to visualize the data and create tailored experiences based on it.
- Book a demo today to see firsthand how it helps you with feature data collection and analysis.
What is feature usage?
Feature usage refers to how users interact with a particular feature in your product. It is a metric that measures how often and in what ways a product feature is used.
It is important to note that while feature usage may seem similar to product usage, they are different. Product usage measures the user’s behavior toward the overall product, whereas feature usage focuses on a particular feature.
Why should you track feature usage?
Tracking the feature usage rate helps you assess the impact and relevance of different product features to users. This helps you to:
- Prioritize product development: Identify your product’s most important features and prioritize your future development efforts on features your users need.
- Enhance the user experience: Study feature usage patterns to understand which features different user segments prefer and tailor their experience accordingly.
- Improve user engagement: Identify the features driving value in your product and help users engage more with them. You can also tailor the user experience to encourage their adoption.
- Drive user retention: Identify difficult-to-use or irrelevant features and address existing pain points to improve satisfaction and boost user retention.
How do you calculate feature usage rates?
The most basic feature usage metric tells you the total number of users who have used a feature.
To make this metric more meaningful, however, you can calculate the number of feature users as a percentage of overall product users. It is calculated as:
(Total number of unique users who used the feature / Total number of unique product users) x 100
For example, if 1000 users engage with your product in a month and 400 use Feature A, the usage rate for Feature A will be (400/1000) x 100 = 40%.
Of course, you can go even further to get more insights by calculating the:
- Number of unique feature users in a period (daily, weekly, monthly, etc.).
- Frequency of feature usage (average feature usage per user per period).
- The average time between feature engagement per user, etc.
Your goal here is to gain as much insight as possible into which customers are using the feature, how they use it, how often, and why.
5 Steps to conduct a feature usage analysis
You’ll need more than a single number to conduct an in-depth feature usage analysis and uncover some truly actionable insights.
To conduct a thorough analysis, you’ll need to complete 5 key steps:
1. Determine the key metrics for tracking feature usage
To correctly calculate the feature usage rate, you must first determine several key metrics:
- Active users: How many unique users interacted with your product?
- Feature users: How many users are using the feature?
- Usage frequency: How often do they use the feature?
- Usage length: How much time do they spend on the feature?
- Time frame: What is the length of time for which feature usage is being measured?
By comparing these metrics, you can determine the feature usage rate and get an insight into how users interact with the feature.
2. Collect feature usage data with an analytics tool
Once you’ve determined which metrics to track, it’s time to collect the necessary feature usage data using an analytics platform. Of course, how this works will vary by platform, but you will want to:
Set up custom events to track user interactions with features
Event analytics enables you to track and analyze user engagement with different product features. Custom events merge multiple events into one, enabling you to track a series of user actions as if they were one.
For example, you can create a custom event to track how many users create a workflow, complete their account setup, or set up a payment method.
Tag UI elements inside your app to monitor feature engagement
The easiest way to track feature data is to tag the specific feature or UI element you would like to track. Unlike custom events, these are more granular, allowing you to tag actions like clicks, hovers, and text inputs.
It, thus, helps you see which features customers use the most and which ones they use the least. It also gives you an insight into how customers engage with different product features.
Use feature heatmaps to analyze feature usage rates on specific pages
After tagging your features, you can then easily visualize usage data with heatmaps.
Heatmaps show you page/feature usage data through a simple color-coded graph. Features are color-coded based on the number of user interactions, with warmer colors representing more popular features.
Armed with this data, you can analyze page/feature effectiveness, track user engagement with different features, check for dead clicks, and capture high-engagement portions of your page.
Gather qualitative feedback for specific feature insights
In-app surveys, customer interviews, and focus group sessions are also excellent sources of user data. They provide valuable insights into what customers think of a feature beyond the numbers.
Strategically placed surveys can also be a source of proxy metrics for feature usage. For example, Customer Satisfaction Score (CSAT) and Customer Effort Score (CES) surveys measure user experience and satisfaction levels with a feature.
To get even more relevant data, you can trigger surveys after specific events or for specific user groups.
3. Dig deeper into user behavior to identify trends
By this point, you’ve done enough to collect all necessary data. Now it’s time to dig into the numbers.
Many analytics tools provide simple feature and event dashboards for tracking user behavior trends and patterns. You can view all-time trends or track interactions for a specific period.
Dig deep into the data to easily identify your most used features, see how feature usage has evolved, and more. You can dig even deeper to see what users were doing before getting to a feature.
For example, you can see when users are most active when using a new feature, or just compare various features’ usage rates for the same segment.
4. Look at feature usage for different user segments
To better understand user behavior, you’ll have to look at how different users interact with each feature. This is because user engagement often varies according to each user’s needs.
You can do this by tracking feature usage by user segment. This enables you to identify patterns and trends that are specific to particular groups and see how each group interacts with a feature.
For example, you can identify the top features for each user segment, determine which features power users use, compare feature usage between old and new customers, etc.
5. Analyze the impact of a particular feature on retention
User retention is key to the success of any SaaS business. Your goal, therefore, with feature usage analysis is to build up feature engagement, making your product more valuable to users.
To measure the impact of feature usage on retention, you can create cohort tables to:
- Compare the usage rate of retained versus churned users.
- Identify which features are most used by retained users.
- Determine which features are most used during the periods with the highest retention rates.
- Learn how each feature correlates with retention.
How to measure feature usage and act on insights with Userpilot
Userpilot is a product growth platform with a variety of powerful analytics features for tracking and analyzing feature usage. It helps you to:
Visualize feature usage data on dashboards
Userpilot enables you to monitor core feature engagement metrics on a simple but detailed Userpilot dashboard.
First, you tag features and track both simple and custom events.
Once that’s done, it offers real-time insights into the features and events you’ve identified. You can see the most engaged users, most engaged accounts, most used features, user activity trends, and more.
Whether you’re tracking goals or monitoring usage trends, you can view them all in one place, making it easy to spot recurring patterns and find correlations in different data sets.
This helps your SaaS business make smarter, data-powered decisions that drive retention and boost your ROI.
Create custom dashboards with different metrics
Business needs are hardly ever uniform, and the same applies to analytics. You may want your dashboard to capture more than it does or may desire to streamline it to make it more targeted.
To that end, Userpilot is rolling out a feature soon that enables users to create custom dashboards. This means you can choose which metrics you want to track, create custom filters, and more.
For example, you can create specialized dashboards to monitor conversions, track new user activation, or even track user engagement with a specific feature.
Create interactive product experiences to increase feature usage
Finally, Userpilot equips you to act on the data you collect. It provides a variety of UI patterns, from tooltips to modals, slideouts, etc., to help you reach users with customized in-app flows and experiences.
For example, you can trigger an interactive guide to help users who are struggling to gain value in a feature. You can also identify the needs of a segment and guide them down the happy path with targeted flows.
Even more, you can trigger in-app messaging when a user first interacts with a particular feature or when an event occurs. As you do, you’ll boost feature engagement and drive adoption.
Conclusion
A comprehensive feature usage analysis can help you unlock valuable insights into your product and how it is used. From understanding users’ needs to identifying challenges, it’ll play a crucial role in your product’s growth.
Ready to get started? Userpilot equips you to collect, analyze, and act on relevant usage data points. Book a Userpilot demo today to see how its powerful insights can help you improve your user experience.
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