[Huawei Developers] Jack Wu Shenzhen:
Sports and health apps are thriving as more and more people place greater value on their health and exercise. This has in turn increased traffic and brought more complex demands. To seize this opportunity and retain long-term users, what is needed is to perform precise operations.

To do so, a practical, industry-specific event tracking system is vital. It is the very start of data analysis and paves the way for data-based operations. In light of this, Analytics Kit offers the event tracking template for the sports and health apps, which provides E2E event tracking management, simplifying app development. Analytics Kit thereby facilitates event tracking and maximizes data value, driving sports and health apps towards digital transformation.

Intelligent Event Tracking​

1. Selecting a Template​

Select Health of Sports and Health. The page displayed shows four templates: Behavior analysis, Account Analysis, Consumption Analysis, and Services and Other.

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* Template for sports and health apps

2. Configuring Event Tracking​

Analytics Kit supports event tracking either by coding or through visual event tracking. Tracking by coding can be implemented by copying the sample code, downloading the report, or using the tool provided by Analytics Kit. Tracking by coding is relatively stable, and can collect and report complex data. Visual event tracking comes with lower costs and technical requirements, and allows the visual event to be modified and added after the app release. To use visual event tracking, you need to integrate Dynamic Tag Manager (DTM) first. You can then synchronize the app screen to a web-based UI and click relevant components to add events or event parameters.

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* Configuring event tracking

3. Verifying the Tracking Configuration​

You can use the verification function to quickly identify incorrect and incomplete configurations, as well as other exceptions in events and parameters once event tracking is configured for a specific template. With this function, you can configure event tracking more accurately and mitigate business risks.

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* Verifying the tracking configuration

4. Managing Event Tracking​

The management page presents the event verifications and registrations, the proportion of verified events to its maximum, as well as the proportion of registered parameters to its maximum. Such information serves as a one-stop management solution, giving you a clear understanding of event tracking progress and the structure of tracking configurations.

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* Managing event tracking

Case​

Released in February, 2016, Now: Meditation has become a leading app dedicated to meditation and mental health in China. Its user retention rate and payment conversion have significantly improved since it utilized the event tracking template for sports and health apps provided by Analytics Kit. The template provides analysis reports containing various indicators and comparison analysis by different dimensions, giving an insight into how users used the app, identifying unusual payment conversion rates, and showing conversion rates of different channels. All of these can illustrate what attracts users to the app and what can be done to encourage users to make payments.

1. Understanding App Usage to Guide Product Optimization​

After event-related data was reported, operations personnel of Now: Meditation checked them in the session path analysis report. The report clearly showed how users behaved in the app, what they did following each step, the steps where users churned, and the steps with an unexpected churn rate.

This powerful function enabled the personnel to find that most active users tended to check content related to improving sleep. Operations personnel concluded that this type of content was most popular among users. Consequently, in the updated version of the app, the product team adjusted the display level for this particular content. They also optimized push notifications by using A/B Testing and sent targeted notifications to audiences. One month after these measures were taken, the retention rate skyrocketed.

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* Example of a session path analysis report

2. Analyzing the Reasons Behind Uninstallations​

Analyzing why users uninstall an app has become a must. Few data analysis platforms, however, could perfectly meet this demand. Luckily, with the uninstallation analysis function in Analytics Kit, capturing app uninstallation events is no longer a daunting task thanks to the system-level broadcast capability. This function shows the uninstallation status and characteristics of users' pre-uninstallation behavior. With this information at your disposal, you'll be capable of finding the root reason behind uninstallation and better optimizing operations campaigns and the product.

The uninstallation analysis report of Now: Meditation clearly showed that before users uninstalled the app, they tended to engage in three events: tapping push notification, ad display, and performing searches. Operations personnel believed the reasons why users uninstalled the app were due to inappropriate frequency, timing, and incorrect audience for push notifications and ads. Other reasons include lack of informative course content and wrong course recommendations. Based on this assumption, the product team decided to send push notifications and ads less frequently, opting to send different notifications and ads to different audiences by using A/B Testing, and in accordance to user attributes. On top of this, the team also improved the course recommendation mechanism. These small changes have delivered a sense of personalization to users, which in turn has led to a significant drop in the uninstallation rate.

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* Example of an uninstallation analysis report

3. Attributing Contribution Rates of Slots to Convert More Users​

An app tends to have different banners, icons, and content, designed to induce VIP members toward making purchases. This leads to some questions: what is the difference in how much each slot and marketing campaign contributes to payment conversion? How to optimize the combination of slots? And how to allocate resources to them more reasonably?

In order to answer these questions, the operations personnel of Now: Meditation used the event attribution analysis and marketing attribution analysis models in Analytics Kit. With these models, they were able to evaluate the user attraction and conversion effects of slots by week and month and check how push notifications contributed to user conversion. Let's take the analysis of the home screen slots as an example. The operations personnel used event attribution analysis to conduct an analysis of the slots. They chose Payment completed as Target conversion event and selected Push notification tapping, Pop-up window tapping, Splash ad tapping, Banner tapping, Searching, Checking exclusive content, and Checking popular courses as To-be-attributed event. They then chose Last event attribution as Attribution model. The following day, the report showed how much each slot contributed to the target conversion event. With this information, the personnel then adjusted how traffic and marketing campaigns were allocated to slots. As a result, they could effectively plan resource allocation.

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* Example of attribution analysis

4. Establishing a Churn Warning System to Win back Inactive and Lost Users​

What's the top concern of apps now? Undoubtedly, it's how to retain users. In the case of Now: Meditation, operations personnel used retention analysis and revisit users analysis to reveal the causes behind user churn. The personnel then used the user lifecycle analysis function to save inactive and lost users as an audience. Once this audience was created, they analyzed the scale of such users, their ratio in all users, their behavior characteristics, the phase from which they turned, and whether they came from a specific channel. With such information, the personnel prioritized which audiences they should attempt to win back. Then, they tried to engage users through ads, push notifications, SMS messages, and e-mails according to users' interest, benefits, and emotions. By the end of this, they established a complete churn warning and user winback system.

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* Example of a user lifecycle analysis report

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