[General Topics] Jack Wu Shenzhen:
HUAWEI Analytics Kit is a one-stop data analysis platform for mobile app developers that utilizes data to drive daily app operations, bringing out dynamic details in a comprehensive, timely, and efficient manner. These cutting-edge solutions inspire out-of-the-box app service innovations, helping developers and operations personnel grow revenue and expand the reach of their apps.

In order to provide a comprehensive overview of how and when Analytics Kit can be applied, this article addresses a diverse range of related topics. We hope that it sheds light on the most important aspects of this exciting new app service paradigm.

In our current era of "post-mobile" Internet, characterized by slow traffic growth, and difficulty in monetizing products and services, access to both capital and users has become crucial, due to the finite nature of each. Developers have struggled to create unconventional apps that attract new users, and provide a steadily growing income. The best, and perhaps only, tool at their disposal is refined operations, which is, detailed analysis of user behavior for the purpose of gaining insight into user requirements and pain points. These assumptions are systematically verified, and then translated into marketing strategies, allowing the developers behind an app to perceive it through the eyes of its users, and grow its user base beyond previous expectations.

But how exactly can enterprises and operations personnel gain such precise insight? And how can they truly stand in users' shoes? This is where the notions of "Event" and "Event analysis" come into the picture.

What is an Event?

An event refers to the behavior of a user with regard to a product, or in other words, a specific event is something that a user completes at a specific time point, place, and manner.

Take the process of browsing for a typical item on an e-commerce platform, as an example. Corresponding events can include tapping the registration button, accessing the product details app, and exiting the page. Therefore, event monitoring is, in essence, the detailed study of user behavior within an app.

What is Event Analysis?

Event analysis attempts to determine the motivations and principles behind user events. It uses multiple dimensions to better capture the various attributes of individual users, for the purpose of user activation promotion, retention, and recall policies that are targeted precisely to match the users themselves.

Within a mobile app team, certain roles are dedicated for specific event indicators. For example, operations personnel may focus on the source of new users in recent months, product managers may care most about the geographical distribution of active users and daily purchasing trends, while R&D engineers may want to know the crash times of a new version. Event analysis provides the high-level information to satisfy each team member.

How Do I Use Event Analysis?

HUAWEI Analytics Kit implements automatic collection on various events and event presetting. If you are unable to collect system-level events for your app (such as uninstallations, resets, and crashes), Analytics Kit does so for you automatically, without need for manual tracking, analyzing user churn and app exception scenarios.

It also empowers you to customize events for in-depth and personalized analysis. For custom events, it is recommended that you set appropriate event parameters, in order to fully reveal important details, such as user trends and multi-dimensional comparisons. After setting the parameters, you can view the parameter details in the event analysis report.

By selecting an event, you'll be able to view detailed analysis corresponding to it, including real-time and historical trends, as well as custom parameters and default indicators (app version, model proportion, OS version, and number of events per session).

Event analysis also supports segmentation according to different conditions, which helps immensely with multi-dimensional drill-down analysis. By adding user attributes, audience, and login status as filter criteria, you can query event data that meets specific conditions with a high degree of precision.

Applicable scenarios for event analysis:

1: The operations personnel for a mobile game would like to know the purchasing information related to game props over the past month, such as the number of payments, number of users making payments, and the payment amount.

Define an event and the event parameters.

You can filter out and view the average number of daily events, average number of daily users, average number of payment times per user, and payment amount, according to time-based segments.

2: The operations personnel for a fresh product purchase app find that the traffic for a channel has soared recently, and they suspect that the spike in traffic is fake. How can they analyze the traffic to confirm that it's real?

Then select the event analysis details for the channel ad link, filtering out for user attributes, audience, and login status, and perform drill-down analysis based on the location, operating system, and app version to reveal the presence of fake traffic.

View the channel parameter analysis card.

Data-driven growth starts with the event model. The event-parameter model helps you gain crucial insight into the authentic interactions between users and apps. By accounting for all event-related factors, you can determine the root causes of user behavioral events, quickly locate strategic points, and enhance operations efficiency to unforeseen levels.

The event model also forms the basis for the funnel, retention, and behavior path analysis models, which will be covered in greater detail.