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Duration 14 hours
Course Outline
Introduction to WrenAI Spreadsheets and Metrics Library
- Overview of features and practical applications
- Key distinctions compared to conventional spreadsheets
- Introduction to pre-built metric templates
Initiating AI-Powered Spreadsheet Workflows
- Creating and formatting spreadsheet structures
- Employing natural language for generating formulas and queries
- Applying AI assistance to streamline data preparation
Utilizing the Metrics Library
- Reviewing standardized KPIs across various departments
- Setting up metrics for RevOps, finance, and marketing functions
- Best practices for maintaining consistency and accuracy
Data Connectivity and Real-Time Updates
- Linking spreadsheets to databases and SaaS platforms
- Automating data refresh cycles for efficiency
- Managing user permissions and access controls
Developing Operational Reporting Workflows
- Creating recurring reports using templates
- Monitoring cross-functional performance indicators
- Setting up automated alerts and notification systems
Visualization and Distribution
- Generating charts and dashboards directly from spreadsheets
- Collaborating with team members in real-time environments
- Publishing reports for key stakeholders
Expanding Operational Analytics at Scale
- Implementing the metrics library across multiple business units
- Standardizing reporting processes throughout the enterprise
- Integrating with existing BI platforms
Advanced Features and Future Developments
- Exploring AI-driven forecasting capabilities in spreadsheets
- Customizing and expanding the metrics library
- Previewing upcoming features in WrenAI operational analytics
Conclusion and Recommended Next Steps
Requirements
- A solid grasp of operational reporting principles
- Prior experience using spreadsheet applications
- Knowledge of business metrics and KPIs
Target Audience
- Revenue Operations (RevOps) teams
- Financial operations teams
- Marketing operations and PMO teams