Metrics for Measuring Mobile User Engagement

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Introduction

User engagement has been a hot topic for usability researchers looking to “explain how and why applications attract people to use them.” (Sutcliffe, 2010, p.3) Over the course of the years, a variety of techniques have emerged to measure user engagement on the web. Yet with the rise of mobile phones and mobile usage, the focus has shifted from web to mobile analytics.

Background

In 2016, mobile usage surpassed desktop usage for the first time (GlobalStats, 2016). Ever since, mobile usage has been on a rapid incline. This past year, consumers spend nearly 4 hours on their phones (Curtin, 2018). This trend has garnered the attention of companies looking to gain a competitive advantage through mobile experience design. In response, mobile analytics tools and platformed have surged in attempt to measure mobile user engagement.

Mobile Analytics Metrics

Number of Users

Mobile analytics track user engagement by assessing a variety of metrics. A common metric for measuring engagement is the number of downloads and installations, since the goal is to build a broad user base. Getting thousands of daily downloads indicates that consumers are responding well to your app. It is important to track the number of users and what they do after downloading an app. Just because someone has downloaded an app does not mean that they are actively using it. Gauging the number of users over time more accurately reveals an app’s retention rate. (Mobile Analytics: The Ultimate Guide, 2019)

Retention Rate

Retaining a mobile customer is much harder than acquiring one. According to Quettra’s data, “the average app loses 77% of its daily active users (DAUs) within the first three days after its installation.” (Tolub, 2016). Successful companies like Google put a lot of effort into engaging users who are at a risk of dropping out, especially new and lapsed users. New users, for instance, need reminders to encourage them to stay (e.g. “We’ve got what you need!”). Lapsed users also need a reason to return to an app (e.g. “Try some of our new…”). (Merritt, 2012)

Session Length and Interval

Session length measures the time each user spends in an app. A session interval can also be calculated to show the frequency at which a user opens and uses an app. Measuring the length and frequency of each session can ultimately reveal the app’s most addictive features. Deep links can be set up to lead users directly to the most active parts of the app. (Tolub, 2016).

Screen Flow

Screen Flows visualize user journeys by tracing the number of visits or exists per screen. This metric can track the string of actions that users users take from one screen to the next. Analysing the navigation pattern of users can help unveil road bumps or problematic areas in an app. If users have to move between two screens too often, the app might need to curtail the process to improve user experience. (Mobile Analytics: The Ultimate Guide, 2019)

Funnels and Conversion

User engagement is contingent on how easily users can complete goals, such as signing up, making a transaction, filling a form, or giving a review. The conversion rate captures what percentage of users can perform a target action, whereas funnels track the steps users take to complete an action. Funnels and conversion rates examine user engagement by determining the bottleneck where users drop off in an app. (Localystics Analytics, 2019)

Conclusion (Post Class Discussion)

Mobile metrics are attractive for merchants looking to boost their profile with impressive performance statistics. These quantitative measures certainly cannot replace the value of qualitative user research. Daily active users and retention rate alone does not necessarily reveal how users are engaging with your app, especially over a long period of time. For this reason, it is important to make use of metrics like screen flows, funnels, and conversion rate. These analytics will give you deeper insight on user engagement by revealing road bumps in your user journeys, drop-off screens, how users engage with certain features, and what percent of users can complete a specific goal. By analyzing the statistical patterns in user behavior, you can can determine what features are worth adding or fixing in order to enhance user engagement.

Bibliography

Sutcliffe, Alistair. “Designing for user engagement: Aesthetic and attractive user interfaces.” Synthesis lectures on human-centered informatics 2.1 (2009): 1-55.

Curtin, M. (2018, October 30). Are You On Your Phone Too Much? The Average Person Spends This Many Hours On It Every Day. Retrieved from https://www.inc.com/melanie-curtin/are-you-on-your-phone-too-much-average-person-spends-this-many-hours-on-it-every-day.html

Mobile Analytics: The Ultimate Guide | Topics. (2019). Retrieved from https://mixpanel.com/topics/what-is-mobile-analytics/

Localytics Analytics. (n.d.). Retrieved from https://docs.localytics.com/dashboard/analytics.html#session-opens-session-closes

Merritt, A. (2012). Tapping into Mobile App Engagement. Google Best Practices. Retrieved from https://services.google.com/fh/files/misc/google-best-practices-whitepaper-mobile-app-engagement.pdf

Tolub, Y. (2016, August 23). Mobile App Analytics: The 12 Most Important Metrics to Measure. Retrieved from https://www.uxmatters.com/mt/archives/2016/08/mobile-app-analytics-the-12-most-important-metrics-to-measure.php