User Analysis Overview

You can also use Audience Analysis to run perspective analysis and RFM analysis on a selected audience, gaining insight into core characteristics to inform marketing strategy planning.

User analysis types include:

• Multi-dimensional Analysis: Import table data from data sources and perform drill-down analysis with grouping and filtering conditions. This helps you understand product usage patterns and identify key factors that drive indicator changes.

• Perspective Analysis: Provides insight into how consumer characteristics are distributed across user tags, including user attributes and custom tags.

• RFM Analysis: The RFM model measures user value and profitability based on three indicators: recent transaction behavior, overall transaction frequency, and transaction amount. Users are classified into eight categories: high-value users, key users, key development users, key retention users, general value users, general maintenance users, general development users, and potential users. By analyzing the distribution and behavior of each category, you can identify value characteristics to support marketing decisions.

• AIPL User Analysis: The AIPL model categorizes users into four stages: awareness, interest, purchase, and loyalty. It provides insight into user counts and trends at each stage, enabling you to quantify brand user assets and coordinate linked operations.

• AIPL Flow Analysis: Analyzes user conversion and churn across AIPL stages within a specified time period, helping you understand user distribution at each stage and improve conversion efficiency.

The following topics describe each analysis type in detail.