[Huawei Developers] Jack Wu Shenzhen:
With increasing user acquisition costs, many enterprises have embarked on finding out how to move towards a refined way of operating, but they are facing a challenge: how exactly can this be done?

This challenge is closely related to content marketing, event marketing, channel expansion, and product design. However, the most fundamental thing needed to overcome the challenge is by achieving an in-depth understanding of users.

Do you know your product's user group?

Which of them are your target users?

Which of them are potential high-value users?

How many users are added every day?

What is the change trend of active users?

You will find the answers to all of your questions in the user analysis model of HUAWEI Analytics Kit.

What Is the User Analysis Model?

The user analysis model, commonly based on the user model, uses the user layering model to analyze the entire user base and find behavior and feature differences between users to formulate targeted marketing policies, as well as fully explore and improve user values. The following will describe the user model, user layering, and capabilities provided by the user analysis model of Analytics Kit.

COLOR="darkorange"]About the user model[/COLOR]

As a systematic method for researching users, the user model helps you understand users' real requirements to avoid making mistakes when coordinating product design and operations. In the early phase, there are two methods for building a user model: one is based on in-depth revisits with users, and the other is based on the opinions and market research data of authoritative experts in the industry. Since these methods may be too time-consuming or not sufficiently objective, they are not a useful way of keeping pace with the rapid iteration of Internet products and the surge in the user base.

That is why we are putting forward a refined operations method based on user behavior data and centering on the cycle of "development-release verification-iterative optimization". By continuously collecting and integrating user behavior data, you can manage users by layer to build the user model.

About user layering

User layering is to group users by dimension based on the layering model. You will need to set user attributes and group users in detail. Common layering models include the user lifecycle model, user value pyramid model, AARRR model, and RFM model.

About user analysis

The user analysis model provided by Analytics Kit is built based on user behavior data. It provides the following capabilities:

1. Basic user analysis: Analyzes new users and active users to understand the changes in key operation indicators such as the daily active user (DAU) and monthly active user (MAU).

2. User layering model: Use the user lifecycle model as an example. It analyzes the user lifecycle to present the user growth and conversion data in each phase of the lifecycle, helping you accurately locate the channels that effectively acquire new users, increase active users, and attract high-value users.

3. Audience analysis model: Gains insight into user segmentation by audiences preset in the system or from your own customizations.

The following uses the user analysis model as an example. The user layering model and audience analysis model will subsequently be introduced and shared.

What Are the Application Scenarios of User Analysis?

Personnel at an online education app launched an online and offline activity from February 6 to February 19 to attract new users. They also wanted to know the trends of new and active users during the activity.

On the user analysis page, they could view the trends of new and active users, collect statistics by day, week, or month, and view the number of new users, proportion of new users, number of active users, proportion of active users, number of churned users, churn rate, and total number of users in a period during the activity.

The analysis report by week showed that the number of new and active users increased during the activity compared with before the activity, indicating that the activity really contributed to new user attraction.

What operations personnel care about the most is the activity level. Under User analysis > Active users, they can view the DAU, weekly active user (WAU), and MAU.

In conclusion, the basic user analysis function of Analytics Kit provides trend changes and details about operation indicators such as new and active users. By using these trends, you can further understand user retention by the retention analysis model and gain a deeper insight into users via the user layering model and audience analysis model. All of these mode will be explained later.