Use case - User Engagement – UXCam

A language app called TalkyTalk* allows users to learn another language through challenges and rewards. The TalkyTalk team would like to increase their user engagement so that users spend a longer period of time within the app and therefore ultimately learn the language.

For the TalkyTalk team's baseline metrics, they went to Session Analytics within UXCam to get their average time in-app, users, and more. These metrics will be used to compare the current version of the app vs. a new release after updates have been made. The team looked at daily, weekly, and monthly metrics.

In order to provide the best user experience, engaging content, and promote power users, the TalkyTeam defined and investigated the difference between

Highest engaged content vs lowest
Users who complete Streaks/Challenges vs. those that do not
User onboarding

To make the investigation more specific, the TalkyTalk team sent UXCam user properties and custom events so the team can filter and report on that data.

Custom User Property	Property	Description
Streak	10day, 30day, 3month, 6month, 1year	Users who use the app daily achieve streaks
Challenge	Number_completed, Number_incomplete	Users who connect to social apps can participate in challenges against their networks
Subscription	Trial, Paid, Free, Canceled	User’s subscription

Custom User Property	Property	Description
Social_Share	Facebook, Twitter, LinkedIn	Users can share their certificates on social platforms
Invite_Link	Sent_pending, Sent_signup	Users can invite their friends to download and use TalkyTalk and receive rewards
Progress	Lesson_started, lesson_compete, lesson_incomplete, level	Tracks progress of each lesson and which level
Language	Language_added, language_removed	Tracks added and removed languages

Highest engaged content vs lowest

The TalkyTalk team started investigating their data with Heatmaps and Event Analytics within UXCam. Heatmaps were used to identify the most popular screen within their app and Event Analytics was used to show data around any custom events the team has sent to UXCam.

The TalkyTalk team defines the highest engagement/most popular screen as the longest time spent on the screen. Other teams can define this in other ways, such as the screen with the most gestures or highest visit count.

Once the TalkyTalk team sorted the screens within Heatmaps for engagement time they saw that the “HomeActivity” page is the screen with the highest engagement. The “Book” screen was the lowest engaged screen; a screen where users can practice reading a short, beginner-level book in the language they are learning.

The “HomeActivity” screen is no surprise in being the most engaged screen as users have many options on that screen like switching their language, viewing their streaks and challenge awards, sharing with their friends, and more.
It is surprising that that “Books” screen has little to no engagement. In order to dig into why the engagement was low, the TalkyTeam wanted to see the screens visited before and after the “Books” screen.

The “Books” screen within Heatmaps opens up a detailed view; on the left side, the team can view what are the entry and exit screens. The screen that most people view before “Books” is the “LanguageMain” screen. This makes sense because all the books are based on whatever language the user is learning, so users have to go (for example) to Home > Spanish > Books.
The screen that people view after the “Books” page is App closing; they leave the app. This also makes logical sense.

The TalkyTalk team moved to Sessions within UXCam and filtered for the “LanguageMain” page. They saw through recorded replay that not many users are scrolling down to see all the options.

The team hypothesized that since the menu item for “Books” was at the bottom of the “LanguageMain” page, users are simply missing the option.

The TalkyTeam made plans to update the "Books" menu item to be on the main “HomeActivity” page and also moved the option higher up within the language page. They also incorporated a new challenge to encourage users to use this page/feature.

Users who complete streaks/challenges vs. those that do not

The TalkyTeam sent custom user properties to UXCam for users that participate in Streaks and Challenges.

The TalkyTeam can see in Session Analytics that the overall time in-app for these that complete Challenges are more than Streak- completers.

Also within Session Analytics, the team reversed the logic to see that the users that did not participate in any Streaks or Challenges had a lower average time in-app. Therefore the team learned that Challenges are a key feature when engaging users.

The TalkyTalk team updated the Session Analytics to show those that completed Challenges, grouped by app familiarity, and observed that users do not opt into the Challenges until after their 10th session.

The team made plans to refocus Challenges as a key feature for new users and send a push notification to those users that are actively using the app but have not opted into Challenges just yet.

User Onboarding

The TalkyTalk team used Event Analytics to see an overview of what their Trial users are doing within the app vs. other subscription types. They filtered on count of user with events and grouped them by Subscription.

The graph reflected that trial users are taking more onboarding actions (such as signing up) which was not a surprise as most users start with a trial instead of starting with a paid subscription. Trial users had more rage taps though, which was surprising.

To see what was causing the rage taps, the TalkyTalk team clicked on the graph that represented Rage Taps within the bar to see all sessions with the rage taps. After watching a few recordings, the team noticed that many users were rage-taping through the onboarding process (basically hitting the next button multiple times and not reading the steps).

With this insight, the product team redesigned the onboarding tour with fewer screens, a skip option, and a time estimate so users would know it would not take long. The team also highlighted Challenges within the app as a main focus in the tour.

Design before:

Design after:

Conclusion

The team launched a new version of the app and compared the data between the previous version and the new version. The team used Session Analytics within UXCam and filtered on Average time in App and grouped by day and App Version. The overall time in-app rose by 20%.

The TalkyTalk team also checked the different sections of UXCam that were covered in this article such as Heatmaps and Event Analytics to do a direct comparison.

Moving forward, the team can use these reports to further dig into the details such as most popular language for users to learn, track progress within user cohorts, and how often user share their social or referral links (all using the custom events sent over previously).

Do you want to measure and increase user engagement? Start with this process:

Gather benchmark data of your current app such as average time in-app, user data (DAU, WAU, MAU), number of logins, feature usage, conversion rate, etc.
Define key aspects of your app in which you would like to analyze
Send all custom data to UXCam such as user properties and/or custom events
Run reports to dig into the data you have collected through mainly Session Analytics and Event Analytics
Make appropriate updates and launch a new version of the app
Compare results
Iterate!

Need more information about what metrics to track, best practices, and other examples, check out these resources:

*Name of real company has been replaced for privacy reasons

Images are examples, not real data