Based on the datasets and models that you create, the User Analysis module lets you perform multi-dimensional perspective analytics on tags, user RFM analysis, AIPL and flow analysis, and purchased customer analysis. During the analysis, you can filter for target audiences that meet specific rules for future marketing outreach.
You can also use the Audience Analysis feature to perform perspective and significance analysis on your filtered target audiences. This helps you understand their core features and supports your marketing policy orchestration.
User analysis types include the following:
Perspective Analytics: Analyzes user tag datasets, including custom tag datasets, to understand the distribution of consumer tag features.
RFM Analytics: RFM is a key method for measuring customer value and profitability. It uses three indicators to describe a customer's value: recency, frequency, and monetary value. Customers are classified into eight types based on these indicators: high-value, key to retain, key to develop, key to win back, general value, general to retain, general to develop, and potential. Understanding the distribution and behavioral features of these customer types helps you identify their value and supports marketing decisions.
AIPL Analytics: Divides your audience into four stages: Awareness, Interest, Purchase, and Loyalty. This analysis provides insights into the number of users in each stage and their change trends, which enables quantitative, path-based management of your brand's audience assets.
AIPL Flow Analytics: Analyzes the conversion and churn of different user types in the AIPL model over a specified period. This helps you accurately understand the audience distribution at each stage and achieve highly efficient conversions.
The following sections provide details.