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Documentation Index

Fetch the complete documentation index at: https://docs.moodmnky.com/llms.txt

Use this file to discover all available pages before exploring further.

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User Profiling Infrastructure

The user profiling system collects, stores, and utilizes user data to enable personalized experiences across all MOOD MNKY agents.

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Overview

User profiling enables:
  • Personalization - Tailored experiences based on user data
  • Preference Learning - Automatic preference detection
  • Behavior Analysis - Understanding user patterns
  • Recommendation Engine - Data-driven recommendations

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Architecture

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Profile Storage

User profiles are stored in multiple layers:
  • Core Profile: Basic user information and preferences
  • Behavioral Data: Interaction patterns and history
  • Preference Vectors: Embeddings of user preferences
  • Segmentation Tags: User category assignments

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Data Collection

Profile data is collected from:
  • Explicit Input: User-provided information
  • Implicit Signals: Behavior and interaction patterns
  • External Sources: Integrated third-party data
  • Inferred Data: ML-predicted attributes

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Profile Components

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Demographics

  • Age, location, language
  • Cultural background
  • Communication preferences

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Preferences

  • Product preferences (fragrances, styles)
  • Content preferences
  • Interaction style preferences
  • Communication channel preferences

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Behavioral Patterns

  • Purchase history
  • Engagement patterns
  • Feature usage
  • Time-based patterns

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Psychographic Data

  • Personality traits (Enneagram, MBTI)
  • Values and interests
  • Lifestyle characteristics
  • Emotional patterns

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Personalization Vectors

Diagram showing how user preferences are converted to vectors for similarity matching
User preferences are converted to vectors for:
  • Similarity Matching: Finding similar users
  • Recommendation: Product and content recommendations
  • Clustering: User segmentation
  • Prediction: Behavior forecasting

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Privacy & Governance

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Data Privacy

  • Consent Management: User consent tracking
  • Data Minimization: Collect only necessary data
  • Anonymization: PII protection
  • Right to Deletion: User data removal

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Data Governance

  • Access Control: Permission-based access
  • Audit Logging: Data access tracking
  • Compliance: GDPR, CCPA compliance
  • Privacy Operations - Privacy management

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Configuration

User profiling configuration: 
user_profiling:
  storage: "postgresql"
  vector_store: "pinecone"
  update_frequency: "realtime"
  retention_days: 1095  # 3 years
  anonymization: true