The Analytics & Reporting Plugin transforms raw data into clear, actionable insights, helping businesses make smarter, data-driven decisions. Instead of relying on multiple external tools, this plugin integrates directly into your platform to deliver real-time analytics, performance dashboards, and customizable reports.

Whether you’re running an e-commerce store, SaaS product, or internal business system, this plugin gives you the visibility needed to optimize sales, track user behavior, and measure key performance indicators (KPIs) with confidence.

What’s Included:

• Interactive Dashboards: Visualize data with charts, graphs, and tables

• Custom KPI Tracking: Monitor sales, conversions, churn, or engagement metrics

• Exportable Reports: Generate PDF or CSV reports for stakeholders

• Multi-User Access: Role-based permissions for teams and departments

• Scheduled Reports: Automate weekly or monthly updates

• Documentation & Support: Step-by-step setup and technical guidance

Technical Implementation:
Built with modern visualization libraries such as Chart.js, D3.js, and Highcharts, and powered by secure back-end frameworks like Node.js, Laravel, or Django, this plugin ensures fast, reliable performance. It integrates seamlessly with MySQL, PostgreSQL, MongoDB, or third-party APIs. The codebase is modular and lightweight, ensuring that analytics do not slow down your platform.

How the Price is Formed:

• Base Price ($1,500): Includes setup of core dashboards and KPI tracking

• Customization Add-ons: Advanced visualization, industry-specific KPIs, or additional data sources may increase cost

• Advanced Features: AI-driven analytics, predictive reporting, or integration with enterprise BI tools (e.g., Power BI, Tableau) are priced based on complexity

• Individual Orders: Custom reporting logic or large-scale enterprise analytics solutions are quoted after consultation

Important Note:
The listed price covers the standard package. For enterprise-level reporting, predictive analytics, or custom KPIs, pricing may vary depending on data volume, integration complexity, and feature requirements.