HUAWEI Analytics Service丨Analysis of paid users to improve payment and conversion

The " AARRR " model is one of the important theories of business operations. As an important part of the model, Laxin deeply affected the subsequent user conversion. In order to improve the quality of new pulls, increase user activity and retention, they have done everything possible, but the income obtained is not satisfactory, and there is no way to improve the income.

The "Paying User Analysis" report is newly added to Huawei Analytics Service 6.0.0, which provides in-depth insights into the payment situation from paying users' purchase behavior, purchase frequency, and purchase habits, and combines with other analysis models of Huawei Analytics Services to help companies improve their products. Operating income.

1. Guide users to quickly generate consumer willingness

The user's first payment is an important signal for the user's affirmation of the value of the APP. Under normal circumstances, it takes a period of experience for users to discover the core value of the APP and are willing to pay for the APP.

Different APPs have different levels of attraction to users, which leads to large differences in the initial payment time of different APP users. So how to guide users to quickly generate consumer willingness?

• Identify high-frequency events for first-time paying users

Enter the "Audience Analysis" report page, create a new first-time paying group, view the first-time paying group report, and determine the high-frequency use ability of first-time paying users. Take an education app as an example. As shown in the figure below, the most frequent events among the first-time paying people are searching courses and sharing courses.

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Enter the "Payment Analysis" report page to filter the "first-time paying users" group through the "filter", check the payment rules of the first-time paying group, and formulate operating strategies.

• aimed at unpaid users and guides them to reach high frequency/core functions in

Through the analysis of first-time purchasers, it is found that when users use the function of searching courses or sharing courses, they are more likely to have the first payment action. Therefore, it is possible to strengthen the guidance of users' ability to search and share courses in the APP, or to guide users to use and experience by pushing the detailed introduction of the function for unpaid users.

2. Increase the average user payment amount (ARPU) and payment rate

Increasing the average user payment amount (ARPU) and the payment rate are the main goals for increasing the overall payment of APP users. Due to the different payment capabilities and payment preferences of different users, different users have different payment contributions to the APP. It is necessary to layer users through the RFM model and adopt different operating strategies for different types of users to improve payment indicators.

• Determine user payment habits
  Click to enter the "Payment Analysis" report page to view the trend of current APP users' paying users and the changing trend of paid amounts. According to the trend changes, combined with filter capabilities and comparative analysis capabilities to determine the payment habits of different groups of people.

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As shown in the above figure, for example, the paying users of the APP are active users with higher paying and concentrated in the Beijing area, so the APP can continuously guide conversion activities for active users in this area.

• Develop payment strategies for different types of users

Hierarchical users through the RFM model

R stands for Recency. (last consumption): the last consumption made by the user since the date of access. You can measure the user's consumption cycle.

F stands for Frequency. (User consumption frequency): The number of consumption by the user in a specified time period.

M stands for Money (consumption amount): the consumption amount of the user in the specified time period.

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For different types of users, the corresponding content can be personalized, such as annual membership customization, full reduction activities and discount activities to stimulate consumption, such as coupon distribution.

Through the analysis of the payment situation of different types of APP users, hierarchical operation can improve the overall payment index and increase the ROI.

for more details>>

Visit Huawei Analysis Service official website

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Obtain the development guide document
Huawei Mobile Services open source warehouse address: GitHub , Gitee

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