Levi Olmstead
What Is User Engagement? (+How to Improve It)
- Published: November 7, 2023
- Updated: April 29, 2024
Whether you’re a startup founder building an MVP or a product manager at a venture-scale company, there’s a significant correlation between user engagement and every other positive product health metric—APRU, profitability, recurring revenue, retention, customer satisfaction, conversions, etc.
Engaged users are more likely to understand how your product solves their challenges, share your product with their network, upgrade to paid (or pricier) tiers, and become dedicated product evangelists who stick around.
The most successful products have built their business model on cultivating user attention and getting them to see the platform as an indispensable extension of their personal or professional life.
This article will explore the concept of user engagement and explain how to build sticky products that drive engagement.
What Is User Engagement?
User engagement measures how users interact with a product, derive value from it, and see it as essential to their contextual needs. Consequently, higher engagement metrics generally indicate that users find your product helpful, which leads to increased user retention, satisfaction, and revenues.
User Engagement vs. Customer Engagement
User and customer engagement are similar concepts, but they primarily differ based on the subset of users involved, their conversion potential, the stage in the conversion funnel, etc. Here are the main differences between user and customer engagement:
- Focus: User engagement focuses on your entire user base while customer engagement is restricted to paying users (individuals, companies, etc.).
- Conversion potential: The essence of user engagement is to convert the audience into customers; in contrast, customer engagement aims to increase revenue from existing customers by encouraging upsells, cross-sells, and additional purchases.
- Metrics: Product teams measure user engagement with activity metrics like active usage (DAUs/WAUs/MAUs), session duration, bounce rate, click-through rate, and user-generated content volume, while customer engagement efforts tend to prioritize revenue-adjacent metrics like purchase frequency, customer lifetime value, advocacy, and referrals.
- Product-centric vs. revenue-centric: User engagement focuses on the product and those using it while customer engagement emphasizes understanding paying customers and offering them a fitting experience to boost retention and advocacy.
Examples of How Different Industries Measure User Engagement
In this section, we’ll dive into the practical ramifications of user engagement, specifically, how certain industries measure (i.e., common user engagement metrics), optimize for it, and their general approach to user engagement.
1. E-commerce stores
E-commerce brands like Amazon, Wish, Alibaba, and Walmart must keep users browsing around long enough to find products they love, add as many as possible to a cart, and check out immediately—or return at a better time to complete their purchase.
To maximize the chances of having those outcomes, digital retailers track metrics like:
- Conversion Rate: This measures the percentage of website visitors who complete a desired action, such as purchasing. These platforms track how many users move from browsing to buying.
- Add-to-Cart Rate: The percentage of visitors who add items to their shopping cart, indicating a strong intent to purchase. This is a valuable precursor to actual purchases.
- Average Order Value (AOV): AOV calculates the average amount spent by customers in a single transaction and signals how much customers are willing to spend.
- Cart Abandonment Rate: The percentage of users who add products to their cart but do not complete the purchase. A lower abandonment rate indicates better engagement.
- Click-Through Rate (CTR): Measures the percentage of users who click on a specific link, advertisement, or product listing.
- Page Views and Time on Site: Longer time spent and more page views can indicate deeper engagement.
- Search and Filter Usage: How hard do customers have to search to discover products?
- Wish List and Favorites: Saving products for laters shows an intent to return and purchase it.
- Review and Rating Submission: The number of product reviews and ratings submitted by users. High-quality reviews can increase engagement and trust.
- Followers and Subscriptions: Metrics related to the number of users following sellers or subscribing to specific product categories, showing ongoing engagement with the platform.
- Repeat Purchase Rate: Repeat customers are highly engaged and valuable.
Additional edge cases to consider include Alibaba’s livestream shopping which measures engagement with metrics like comments, purchases, and viewer counts, and eBay’s auction model which emphasizes bids submitted and successful auction completion rates.
2. Enterprise software
B2B software applications like HubSpot, Mailchimp, and Salesforce use end-user monitoring to determine when users need to be re-engaged, if their product’s onboarding process needs to be reworked, issues with enterprise UX design, and product health metrics that might signal that users are facing issues, such as:
- User outcomes: Open rates, click-throughs, and conversions on their end-users’ campaigns.
- Feature engagement: Monitoring user interactions with specific features of cloud services, sharing data sets, joining exchanges, etc.
- Time-to-adoption: The amount of time it takes to adopt an application into consistent usage.
- DAU/WAU/MAU: Measures the number of users who are active on a daily, weekly, or monthly basis.
- Digital adoption: End-user adoption of products or services, typically after achieving their “aha!” moment where they realize the value of product.
3. B2C apps
Consumer applications (Uber, Apple Fitness, Headspace, Instacart, Facebook, and Twitter) cater directly to individuals and as such, they’re more likely to lose users who churn on a whim. Consequently, they must keep tabs on activity metrics, track usage over time, and if/how much of their network they invite to share the experience with.
For instance:
- Headspace, a mindfulness application might track session duration, frequency, and completed courses.
- Instacart’s grocery pickup/delivery model can better understand users by observing their basket size, repeat orders, and order frequency.
- Canva’s graphic design platform might have to focus on the number of design elements created, templates used, and other metrics related to collaboration, sharing, and team usage.
- Twitter: Tweets, retweets, followers, hashtag usage, etc.
4. Streaming services
Netflix, Peacock, Disney+, Hulu, and Prime Video need to immerse users, get them to complete more shows, keep going down the rabbit hole (with newer shows), and even create their own playlists/wish lists.
- Viewing Time: Includes tracking the average time users spend per session and overall viewing hours.
- Content Consumption: This data helps with content recommendations and production decisions.
- Completion Rate: High completion rates indicate user engagement and content satisfaction.
- Session Frequency: Frequent sessions suggest active engagement.
- Content Rating and Feedback: Users’ ratings, reviews, and feedback on content help platforms understand user preferences and content quality.
- User Profiles: The number of user profiles created within an account may indicate multiple users within a household, each with their preferences and engagement.
- Content Search and Discovery: Including the number of searches, clicks, and interactions with recommendation algorithms.
- Playlist Creation: Users who load up on movies and serials they want to check out later are potential binge watchers—all they need is a nudge from time to time to remind them and they’ll go down the rabbit hole.
Methodologies for measuring user engagement typically involve advanced data analytics, machine learning, and recommendation algorithms to personalize the user experience. A/B testing and experimentation are also used to optimize the platform for engagement.
Some edge cases to consider:
- Peacock’s Free Tier: Peacock offers a free, ad-supported tier alongside its premium subscription service. They may focus on metrics related to ad engagement and the conversion rate from free to paid subscriptions.
- YouTube TV’s Ad Engagement: As an ad-supported platform, YouTube TV closely tracks ad viewability, click-through rates, and engagement with sponsored content.
- Tubi TV’s Advertising Metrics: Tubi TV is primarily ad-supported and relies on metrics related to ad impressions, click-throughs, and viewer interaction with ads.
RECOMMENDED Article
6 Tips to Improve User Engagement
At first, “How do we improve user engagement?” sounds almost rhetorical—how else but by building a better product people want to use?
Instead, we focus on the tips, optimization best practices, and UX philosophy to adopt across your user onboarding experience to create a sticky product and drive product adoption.
1. Build user personas and perform cohort analysis
User personas help you sketch a profile of what your ideal user(s) look like so you can optimize your product to their use cases and get them to engage more often. Depending on your industry, niche, and target user base (i.e., B2B/B2C), your persona-building might need to factor in:
- Demographics: Age, Gender, Location (city, region, country), Marital status, Education level, Occupation, Income level.
- Psychographics: Interests and hobbies, Values and beliefs, Lifestyle (e.g., active, sedentary, eco-conscious), Personality traits, Attitudes and opinions, Motivations and goals.
- Technographics: Technology proficiency, Preferred devices (e.g., smartphone, tablet, desktop), Operating system (iOS, Android, Windows, macOS), Social media platforms used, Internet usage habits.
- Behavioral Information: Online behavior (browsing, shopping, social media), Buying behavior (impulse, budget-conscious, brand loyal), Frequency of product/service usage, Pain points and challenges, Decision-making process.
- Professional Information: Industry, Job title, Company size, Work responsibilities and challenges
- User Journey Mapping: The stages in their user journey, from discovery to purchase and post-purchase behavior.
On the other hand, cohort analysis refers to grouping users into buckets based on their shared characteristics such as sign-up date, acquisition channel, location, product version, subscription type, and engagement frequency.
The goal is to observe users who share certain behavioral traits, understand their usage patterns, and discover engagement aids to help them explore your product deeper.
2. Enable users with helpful documentation and support
Self-help end-user support resources like support content libraries, wikis, pre-recorded demos, courses, knowledge bases, product documentation, and digital communities enable users to quickly ramp up their usage of your product at their own pace.
With a digital adoption platform like Whatfix, product teams can enable their end-users with an embedded self-help wiki that overlays their application UI. Whatfix Self Help automatically crawls a product’s documentation, tutorials, video repos, knowledge base, FAQs, and more – aggregating all help and support content into one searchable wiki.
Above: Example of contextual help and user support built with a Digital Adoption Platform.
Whatfix’s Self-Help overlays on to any web application, desktop application, mobile app, or website. It provides contextual help to users and integrates with your FAQs, support center, LMS, user documentation, and more. Users are presented with common issues and help content for their contextual area in the application, or they can use an open-ended search to find the specific help content they’re looking for. These help support cards often prompt in-app guidance, walking users through the specific workflow they need help on.
3. Provide in-app guided experiences
In-app guidance experiences offer contextual support—they surface useful tips, cues, and highlights right when users need them and, as a result, make it easier to navigate your product without engaging support.
A guided onboarding, engagement, and adoption platform like Whatfix enables your with a no-code editor to create, launch, test, and analyze in-app guidance cues and messages such as:
- UI tooltips: Small pop-up messages or hints that provide information about specific elements or buttons within the app when users hover over or click on them.
- Onboarding checklists: Interactive checklists that guide users through a series of tasks or steps, helping them keep track of their progress.
- UX hotspots: Small, beacon-like UI elements that can pulsate to draw users’ attention to specific elements or features.
- Interactive Walkthroughs: Comprehensive, multi-step guides that lead users through complex processes, such as setting up an account or creating a project.
- Onboarding Tours: Interactive product tours that guide new users through the key features and functionalities of the app during their first visit.
- Spotlight or Focus Modes: Highlighting a specific element, feature, or button by darkening the background and drawing attention to the highlighted area.
- Video Tutorials: Embedded video popups that provide detailed guidance on how to use specific features or accomplish tasks.
- Error Messages with Solutions: Instead of just displaying error messages, the app provides potential solutions or links to relevant resources. This can also include field validation errors and messages on forms.
Create contextual user onboarding flows, drive adoption of new features, and make in-app announcements with Whatfix
Whatfix is a no-code digital adoption platform that enables product managers to create contextual in-app guidance, product-led user onboarding, and self-help user support – all without engineering dependencies. With Whatfix, create branded product tours, user onboarding checklists, interactive walkthroughs, pop-ups, smart tips, and more – all enabling customers and users with contextual guidance at the moment need. With Whatfix, analyze, build, and deliver better user experiences.
4. Use product analytics software to capture user behavior data
Product analytics platforms (like Whatfix Analytics) offer the most transparent way to observe your users’ behavioral patterns, detect issues they might be facing, and marginal changes that can improve user experience.
And, speaking of product analytics, there are different approaches you can take and metrics you might track with a tool like Whatfix, such as:
- User Activity Tracking: Monitor user actions, such as clicks, page views, feature usage, and navigation paths, to understand how users interact with the product.
- Conversion Funnel Analysis: Track user progression through specific sequences of actions, such as signing up, onboarding, or making a purchase, to identify drop-off points and optimize the user journey.
- Retention Analysis: Measure user retention over time, understanding how many users continue to engage with the product after their initial interaction.
- Cohort Analysis: Group users based on shared characteristics (e.g., sign-up date, acquisition channel) and compare their behavior over time.
- A/B Testing: Conduct experiments to compare the performance of two or more variations of a feature or design to determine which is more effective.
- Feature Adoption and Usage Analysis: Track which product features are most and least used, helping prioritize feature improvements and development.
- User Path Analysis: Study the typical paths that users take within the product to understand how they navigate and achieve their goals.
- User Segmentation: Divide the user base into distinct segments based on characteristics like behavior, demographics, and usage patterns, allowing for more targeted analyses and strategies.
- Funnel Conversion Rate Optimization: Optimize conversion rates at different stages of the user journey by identifying and addressing bottlenecks.
- Event Tracking: Monitor specific user events or interactions (e.g., adding items to a cart, sharing content) to assess their impact on user engagement and conversions.
- Error and Bug Tracking: Identify and address software errors and bugs that negatively affect the user experience and product performance.
Analyze user behavior and track product usage with Whatfix Analytics
Enable your product managers to easily track and analyze user behavior and product usage with Whatfix Analytics, a no-code event tracking solution. With Whatfix Analytics, capture all user actions without engineering support, understand product usage, identify dropoff areas, understand feature adoption, map user journeys, build user cohorts, and make data-driven product decisions.
5. Gather user feedback
Although user feedback doesn’t directly impact engagement metrics significantly, it helps you understand what to change about your product to improve user experience and what features your end-users are requesting the most. In practice, you can insert these survey and feedback prompts after pillar experiences when users are more likely to respond honestly.
There are several channels product-led companies can use to collect product feedback, including:
- In-App Surveys: Pop-up surveys or questionnaires displayed within the software or app, allowing users to provide feedback while using the product.
- Feedback Forms on the Website: A dedicated feedback form on the company’s website where users can submit their thoughts, suggestions, and concerns.
- Customer Support Interactions: Collect feedback after customer support interactions, either through direct questions or post-support surveys.
- Feature Request Forms: Allow users to submit feature requests or product enhancement suggestions through a designated form on the company’s website or within the app.
- User Forums and Communities: Online forums or community platforms where users can share feedback, discuss issues, and suggest improvements.
- Social Media: Monitor social media platforms for comments, mentions, and messages from users who are discussing the product or sharing feedback.
- Review aggregators such Google Play, Apple App Store, G2 Crowd, Capterra, and Trustpilot.
- NPS (Net Promoter Score) Surveys.
6. Test new UX, messaging, features, user paths, and experiences
A culture of continuously experimenting with variables will help your product team observe how real users interact with your product vs. what you expect, ensure that your messaging is clear and aligns with user expectations, and helps you to deploy user paths that guide users to their desired outcomes faster.
One effective user path to analyze, optimize, and continuously test is your onboarding experience. User onboarding flows should guide users to relevant information or assist them within your application based on their current context, desired outcome, or needs. As a result, you’ll be able to reduce friction, reduce your time-to-value, increase feature adoption, and retain more users.
Analyze, build, and deliver more engaging user experiences with Whatfix’s in-app guidance, self-help support, and product analytics
Whatfix is an all-in-one growth engine designed to help product-led teams understand their users, educate them at scale, and build loveable experiences.
- Whatfix Analytics: Track user behavior through your funnel and find what makes them click
- In-app guidance: Coach users through your product with contextual cues and experiences
- Self-help support: Equip users to resolve issues at their convenience with step-by-step guides
Learn how Whatfix can help you build engaging product experiences with our user engagement platform that’s designed for scale.
What Is Whatfix?
Whatfix is a digital adoption platform that provides organizations with a no-code editor to create in-app guidance on any application that looks 100% native. With Whatfix, create interactive walkthroughs, product tours, task lists, smart tips, field validation, self-help wikis, hotspots, and more. Understand how users are engaging with your applications with advanced product analytics.
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Whatfix's digital adoption platform empowers your employees, customers, and end-users with in-app guidance, reinforcement learning, and contextual self-help support to find maximum value from software.
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