Feature Drop-Offs: Causes & 4 Ways to Reduce Them

Feature Drop-Offs: Causes & 4 Ways to Reduce Them cover

When left unaddressed, feature drop-offs lead to user dissatisfaction and result in churn. This article helps you identify and eliminate them by answering the following questions:

  • Why do users stop using certain features?
  • How can you identify drop-offs with product analytics and user surveys?
  • What strategies can you use to reduce drop-offs and improve the user experience?


  • A feature drop-off is the abandonment of a feature or product over time. It signals decreased engagement and indicates friction in the user experience.

Regularly flagging drop-off points helps you:

Possible reasons users abandon a feature:

How to identify drop-off points:

Metrics to help you measure drop-offs:

4 ways to reduce drop-offs in your user journeys:

  1. Personalize the onboarding flow.
  2. Offer secondary onboarding for every new feature.
  3. Deliver proactive customer support.
  4. Improve feature experiences with A/B testing.

Userpilot is a product growth tool that helps SaaS companies reduce drop-offs in their user journeys and enhance feature engagement. Book a demo now to explore.

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What is a feature drop-off?

Feature drop-off is the abandonment of a feature or product during a user session. Feature drop-off analysis helps identify where user engagement dips and which features are leading to friction.

Drop-offs also indicate a value gap in what your product delivers vs what regular users expect from it.

What are the benefits of tracking drop-offs?

Tracking where users disengage can feel like focusing on the negative, but it’s a proactive way to boost your product’s health and optimize engagement.

Here are the key benefits:

1. Identify points of friction to remove them

A feature with declining usage often points to hidden obstacles in the user journey. Maybe the feature is hard to find, poorly explained, or buggy.

Tracking drop-offs helps you pinpoint these friction points so you can strategize to remove them, leading to a much smoother experience for users.

For example, if you notice users are disengaging because the feature is complex, you could deploy tooltips to explain the feature better or have your dev team redesign it for simplicity.

2. Increase feature adoption

When you remove friction by analyzing user behavior, you remove roadblocks from the user journey. This helps increase user engagement and makes it more likely for users to see the full potential of your features.

By tracking drop-offs, you can identify the features that contribute to churn and step in to improve the experience.

3. Prioritize feature development as per user needs

Tracking how users behave in-app helps you understand their needs better.

You’ll see the features they use frequently and the ones they ignore. If a feature isn’t gaining traction despite your best efforts, it is likely not a good fit for most users.

These insights can help you inform feature development. You can refine popular features or develop complementary ones and evaluate scaling back for those that don’t attract users.

4. Improve user experience and increase retention

Continuously identifying and removing friction with drop-off analysis and user feedback creates a cycle of data-driven product development. This improves the overall user experience, leading to more paying customers in the long run.

You can also expand the same strategy to other channels, such as your landing pages and social media posts, to reduce conversion friction.

Why do users stop using a feature?

Even well-developed features can suffer from disinterest. Here are five common reasons this happens:

  • Friction in user experience: From cluttered interfaces to bugs and the lack of proper integrations, many things can cause friction in the user experience. The presence of these will keep users from engaging regularly with your product.
  • Poor onboarding: Sometimes, the product is great but the onboarding flows confuse users. When customers struggle to understand each feature and how it works, the result is reduced engagement.
  • Steep learning curve: Some features may have a steep learning curve due to their complexity or advanced capabilities. If users feel that learning to use a specific feature is too time-consuming or difficult relative to the perceived value it offers, they may choose not to use it.
  • Inadequate customer support: When users encounter issues or have questions about a feature, prompt and effective customer support is crucial. Lack of adequate support can leave users feeling frustrated and abandoned, pushing them to stop using the feature entirely.
  • Long time to value: Users often look for quick wins. If a feature takes too long to deliver tangible value or the benefits are not immediately apparent, users may lose interest and disengage.

How to identify drop-offs for features

Analytics tools play a critical role in identifying drop-off points. While you can use a single method to identify friction points, combine different methods to glean the most value from your analysis.

Let’s explore how this is done with the best tools for the job.

1. Identify where users drop off with funnel analysis

Funnel Analysis tracks the user journey through a series of steps toward a defined goal, such as discovering and using a feature.

It helps to identify at which stage users drop off, providing insights into potential issues or friction areas within that journey.

Analytics tools such as Userpilot let you conduct funnel analysis and generate reports to spot drop-offs across various features.

For example, by examining a funnel analysis report, you can see a sharp decline in progression between steps, suggesting friction.

Funnel report generated with Userpilot.

2. Track user paths for your feature with path analysis

Path analysis visualizes the various routes users take through your product, revealing how they navigate towards and within specific features. Each stage in this analysis comprises a feature users engage with, an event they complete, or a page they view.

You can also track drop-offs for every path as users move from one stage to another. This helps identify exactly where they face trouble.

User path analysis in Userpilot.

3. Monitor how users interact with your UI with heatmaps

Heatmaps use color overlays to show where users click, hover, and scroll on your app interface.

As in the image below, hot areas with vibrant colors indicate high engagement, while cooler zones mean fewer instances of interaction.

Heatmap reports help you get granular with user behavior tracking. You can spot features users repeatedly engage with and the ones they completely ignore. You can also spot how new features perform by tracking their UI interactions.

Generally, low engagements signal drop-offs, while increased user activity indicates that users value the feature.

Features heatmap report in Userpilot.

4. Track feature retention with cohort analysis

Cohort analysis divides users into groups based on shared characteristics (such as sign-up date) and tracks their behavior patterns over time.

This analysis helps you measure how many users return to perform the same event. By conducting regular cohort analysis, you can identify which features have high and low retention rates and how they contribute to overall product retention.

Cohort analysis with Userpilot.

5. Collect user feedback to ask users where they face friction

Feedback surveys help you hear from your users directly. Gather both quantitative and qualitative data regarding how your users feel and identify friction areas other report types might be missing.

For example, a feature might be popular with your users but still be hard to use. In such a scenario, a heatmap or a funnel report cannot highlight the perceived difficulty. A CES survey, on the other hand, can help you collect direct feedback regarding how easy it is to use.

You can also ask users to expand on their responses with open-ended questions, giving you deeper insights related to their experiences.

Customer effort score survey created with Userpilot.

Related metrics that help measure drop-offs

Track the following metrics to spot drop-offs in your product easily:

  • Product stickiness: This metric measures how often users return to your product over a specific period. The easiest way to track product stickiness is to find your daily active users to monthly active users ratio. A high stickiness score suggests users find continuous value in your features, meaning you see fewer drop-offs.
  • Feature activation rate: This measures the percentage of users who start using a feature after discovering it for the first time. It assesses the initial appeal and ease of using your features. Low activation rates may signal usability issues or a lack of a clear value proposition, leading to drop-offs.
  • Feature adoption rate: This metric tracks the percentage of users that incorporate your features into their workflows and continue using them over a specific period. If you have a good activation rate but poor product adoption, your feature might have usability issues.
  • Retention rate: The retention rate is the percentage of users who continue using your features long after adoption. Declining retention is a sign of drop-offs.
  • Churn rate: This metric is the opposite of the retention rate; it measures how many users stopped engaging with your app in a given period.

4 ways to reduce feature drop-offs for your SaaS company

Now that you’ve seen how to identify drop-offs and the metrics to track, it’s time to learn how to boost engagement. Here are four ways to lower friction for your users.

1. Personalize the onboarding flow

One size does not fit all. If you have a single onboarding flow for all your new users, you’re likely showcasing irrelevant features and delaying their time to value.

Different segments care about different features. Use personalization to introduce only the features relevant to each use case and speed up product adoption.

Welcome surveys enable you to collect user data upfront. Use this information to segment users, understand their needs, and trigger the right onboarding flow for the right user.

Welcome surveys built with Userpilot.

2. Offer secondary onboarding for every new feature

Don’t assume existing users will independently discover new features and magically know how to use them right away.

Instead, trigger detailed secondary onboarding each time you roll out features so existing users can learn about them and use them in the right way. This has dual benefits:

  • It quickly draws users’ attention to the new release.
  • It shows them how to engage and maximize it, eliminating friction and improving user satisfaction.
Feature release announcement created with Userpilot.

3. Deliver proactive customer support

Proactive support anticipates and addresses user issues or questions before they become significant problems. So, how can you offer proactive help?

Use contextual tooltips to provide in-app support when users explore a feature for the first time or if they struggle to get things done.

In addition, create a robust resource center that contains helpful content for users at different journey stages. This allows users to troubleshoot issues themselves without waiting for hours to get live help.

An in-app resource center built with Userpilot.

4. Improve feature experiences with A/B testing

Iterative testing allows your product to stay competitive and ensure user loyalty. A/B testing can help you test multiple variations of your UI to find the ones that users prefer the most.

To run an A/B test, define a hypothesis that could help reduce feature drop-offs. Then, use A/B testing to validate your ideas. If a new variant results in better engagement, that’s a sign you’ve addressed the source of friction in your UX.

Now, all you need to do is iterate to keep improving the user experience.

A controlled A/B test in Userpilot.

Userpilot: The best tool for monitoring feature engagement

Userpilot is a product growth tool with powerful features to help you understand user behavior and trigger in-app experiences to boost engagement.

Here’s how Userpilot can help:

  • Analytics tools: Userpilot lets you generate trends, funnels, cohorts, and path analysis reports to gain a comprehensive understanding of in-app user behavior and understand why users abandon the journey.
A trends analysis report in Userpilot.
  • Feature tagging: Tag existing and new features to measure associated user interactions. You can visualize the result in a comprehensive dashboard like the one below, to see the total number of events and interactions.
Userpilot’s features and events dashboard.
  • Heatmaps: Track UI interactions for a specific feature. Generate heatmap reports and analyze them to identify features with high and low engagement.
  • A/B testing for flows: Userpilot’s A/B testing feature lets you test different variations of in-app flows and UX enhancements to discover what works best for your users. You can conduct controlled A/B tests, head-to-head tests, and multivariate tests.
Types of A/B tests available in Userpilot.
  • Analytics dashboards: Userpilot’s analytics dashboards let you track key features relating to user experience and product performance in one place. To track feature engagement, you can view the core feature engagement dashboard. It lets you track usage trends, adoption rates, and retention for your most vital features.
Start tracking your core features code-free with Userpilot.
  • Session recordings: Watch video recordings of how users interact with your features. Observe their navigation patterns and the points where drop-offs occur. Then, use the insights to determine how best to boost engagement.


The best way to deal with feature drop-offs is by continuously studying user behavior, and making data-driven enhancements in the UX. This helps you understand what your users need, track changes in their preferences, and identify where your product may be lacking.

Userpilot helps you do all three. Book a demo now to track drop-offs and enhance overall product growth.

Try Userpilot and Take Your Product Growth to the Next Level

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