Content Compass - Recommendation Where to go Next

Content Compass provide guidance towards creating content that aligns with trends and SEO best practices. It recommend articles for inclusion on a website based on trending topics identified through Google Trends

I. Content Compass Feature Specification

This document outlines the feature specification for ConentCompass, a system designed to recommend articles for inclusion on a website based on trending topics identified through Google Trends.

A. System Overview

Content Compass will analyze user browsing behavior and leverage Google Trends data to suggest relevant articles that align with current user interests and trending topics. This will help improve user engagement and content discoverability on the website.

B. Requirements

  1. Data Collection:

    • User Browsing Data: Content Compass will collect anonymized data on user browsing behavior, including:
      • Pages visited
      • Time spent on each page
      • Click-through rates on internal links
    • Google Trends Data: The system will integrate with Google Trends API to retrieve data on trending topics. This data will include:
      • Search queries with high popularity growth
      • Related searches

  2. Data Analysis:

    • User Interest Identification: The system will analyze user browsing data to identify patterns and topics of interest to each user. This may involve techniques like collaborative filtering or topic modeling.
    • Trend Analysis: Content Compass will analyze Google Trends data to identify emerging trends and popular search queries.

  3. Recommendation Generation:

    • Based on the analysis of user browsing data and Google Trends data, the system will recommend articles relevant to:
      • User interests
      • Trending topics
      • Content gaps on the website (e.g., topics not currently covered)

  4. Content Suggestion Delivery:

    • The recommended articles will be presented to website editors through a user interface (UI).
    • The UI will display:
      • The title of the recommended article
      • A brief description of the article content
      • The relevance score (based on user interest and trend data)

C. Success Criteria

  • Increased click-through rates on recommended articles
  • Higher user engagement with website content
  • Improved website traffic and user retention
  • Editors finding the recommendations valuable and relevant

D. Non-Requirements

  • ContentCompasss will not generate content automatically. Editors will have full control over the decision to publish recommended articles.
  • The system will not collect any personally identifiable information (PII) about users.

E. Future Considerations

  • Integration with social media platforms to identify trending topics
  • User feedback integration to refine recommendations over time
  • A/B testing different recommendation algorithms for optimal performance

This feature specification provides a high-level overview of the RecommendContent system. Further technical specifications will be developed during the implementation phase.

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