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Understanding User Engagement Patterns and Perform Churn Analysis

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data-mining data-visualization data-visualization-python python churn-prediction user-analytics

user-engagement-and-churn-analysis's Introduction

User-Engagement-and-Churn-Analysis

Introduction:

Understanding User Engagement Patterns and Perform Churn Analysis and Mitigating User Churn in a Digital Classroom Platform The dataset provided includes information about user interactions, specifically the guardian's unique ID, the timestamp of messages sent, and the type of messages. The analysis aims to derive actionable insights for improving user retention.

Work Process

Python: For Data Cleaning, Data Processing, EDA, Analysis

Recommendations for Content Posting:

  • Evening Posting: Schedule gamified lessons during the evening hours when there is a peak in engagement. This aligns with users' availability and willingness to interact.
  • Late-Night Posting:Consider posting content late at night for users who are active during these hours. This may capture the attention of those who prefer engaging with content after completing their daily tasks.
  • User Segmentation: Explore if different user segments show preferences for specific posting times. Consider segmenting users based on engagement frequency or content preferences.
  • Feedback Mechanism: Implement a feedback mechanism to understand user preferences regarding content timing. Collecting direct feedback can provide valuable insights.
  • A/B Testing: Conduct A/B testing by posting content at different times on different days to evaluate the impact on engagement.

Further Analysis Considerations:

  • Event Correlation: Check for any external events, promotions, or campaigns during the months of notable increase to correlate with engagement patterns. Check if there are specific events, promotions, or campaigns on the higher engagement days that contribute to increased activity.

  • Content Strategy: Analyze changes in content types, themes, or delivery strategies that may have influenced user engagement. Investigate the types of content or activities scheduled on higher engagement days. Identify patterns in the content that resonates well with users.

  • User Interaction: Explore user interactions on specific days or weeks with high or low engagement to identify contributing factors. Explore user behavior on Saturdays to understand why engagement is lower on this day. Consider user preferences, possible distractions, or external factors.

Scope of Improvement:

  1. Content Relevance: Analysis: Evaluate the engagement based on the relevance of content delivered. Rationale: Ensure that content aligns with user interests and educational needs.

  2. Interactive vs. Passive Content: Analysis: Differentiate engagement patterns for interactive (e.g., gamified) and passive content. Rationale: Understand if interactive elements contribute to sustained engagement.

  3. User Journey Analysis: Analysis: Map the user journey from initial engagement to churning. Rationale: Identify critical touchpoints where interventions or improvements can be made.

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