Secure registration, login, and account management for users, including analysts, marketers, and administrators.
Role-based access controls to manage permissions for different system features and data.
Social Media Data Integration
Integrate with various social media platforms (e.g., Twitter, Facebook, Instagram, LinkedIn) to collect data such as posts, comments, likes, shares, and user profiles.
Support for real-time and historical data retrieval.
Data Collection and Storage
Collect and store social media data from integrated platforms efficiently.
Ensure data is organized and accessible for analysis and reporting.
Sentiment Analysis
Analyze social media content to determine sentiment (e.g., positive, negative, neutral).
Provide sentiment trends and insights over time.
Trend Analysis and Reporting
Identify and analyze trends in social media conversations, hashtags, and topics.
Generate reports and visualizations on social media trends, engagement metrics, and performance.
Influencer and Engagement Analysis
Identify key influencers and analyze their impact on social media conversations.
Track engagement metrics such as likes, shares, comments, and follower growth.
Competitor Analysis
Monitor and analyze competitors’ social media activity and performance.
Provide comparative insights and benchmarks against competitors.
Customizable Dashboards
Offer customizable dashboards for users to visualize key metrics, trends, and insights.
Allow users to configure and save different dashboard views based on their needs.
Alert and Notification System
Send real-time alerts and notifications for significant events or changes in social media activity (e.g., spikes in mentions, negative sentiment).
Provide options for configuring alert thresholds and notification preferences.
Data Export and Integration
Allow users to export data and reports in various formats (e.g., CSV, PDF, Excel).
Integrate with other business systems (e.g., CRM, marketing platforms) for seamless data sharing and analysis.
User Interaction and Feedback
Provide features for users to comment on and discuss insights or reports.
Offer mechanisms for collecting user feedback and suggestions.
Historical Data Analysis
Support analysis of historical social media data to identify long-term trends and patterns.
Provide tools for comparing historical data with real-time data.
Non-Functional Requirements
Performance
Ensure the system can handle large volumes of social media data and perform analyses efficiently.
Provide quick response times for data retrieval, analysis, and report generation.
Scalability
The system should be scalable to accommodate increasing amounts of data, users, and social media platforms.
Support both horizontal and vertical scaling to manage growth and increased data volume.
Availability
Ensure high availability with minimal downtime (e.g., 99.9% uptime).
Implement redundancy and failover mechanisms to maintain system operation during failures.
Security
Protect user data, social media data, and system communications through encryption and secure access controls.
Implement regular security assessments and adhere to data protection regulations.
Usability
Design an intuitive and user-friendly interface for analysts, marketers, and other users.
Provide clear navigation, help documentation, and user support.
Compatibility
Ensure compatibility with various devices (e.g., desktops, tablets, mobile phones) and operating systems.
Integrate seamlessly with social media platforms and other business systems.
Maintainability
The system should have a modular and well-documented codebase to facilitate maintenance and updates.
Implement automated testing, continuous integration, and version control practices.
Reliability
Ensure reliable operation with robust error handling and recovery mechanisms.
Minimize system errors and downtime through proactive monitoring and maintenance.
Compliance
Adhere to relevant regulations and standards for data privacy and social media analytics (e.g., GDPR, CCPA).
Ensure compliance with industry best practices and guidelines.
Efficiency
Optimize resource usage (e.g., memory, processing power) to ensure efficient operation and cost-effectiveness.
Implement data processing and storage practices that minimize resource consumption.