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Duration 14 hours
Course Outline
Introduction to WrenAI Spreadsheets and the Metrics Library
- Overview of key capabilities and applicable use cases
- Comparing WrenAI features with traditional spreadsheets
- Overview of pre-built metrics available
Getting Started with AI-Powered Spreadsheets
- Creating and formatting spreadsheet layouts
- Generating formulas and queries using natural language
- Utilizing AI assistance for efficient data preparation
Utilizing the Metrics Library
- Reviewing standardized KPIs across different departments
- Setting up metrics for RevOps, finance, and marketing teams
- Best practices for ensuring consistency and accuracy
Data Connectivity and Real-Time Updates
- Integrating spreadsheets with databases and SaaS tools
- Automating data refresh cycles for up-to-date insights
- Managing user permissions and access control
Optimizing Operational Reporting Workflows
- Designing recurring reports using templates
- Monitoring cross-functional performance indicators
- Automating alerts and notifications for key events
Visualization and Collaboration
- Generating charts and dashboards directly from spreadsheets
- Enabling real-time collaboration among team members
- Publishing reports for stakeholders and decision-makers
Scaling Operational Analytics
- Implementing the metrics library across multiple business units
- Standardizing reporting processes throughout the enterprise
- Integrating with existing BI platforms
Advanced Features and Future Directions
- Exploring AI-driven forecasting capabilities within spreadsheets
- Customizing and expanding the metrics library
- Overview of upcoming features in WrenAI operational analytics
Conclusion and Recommended Next Steps
Requirements
- A solid grasp of operational reporting fundamentals
- Practical experience with spreadsheet applications
- Knowledge of business metrics and KPIs
Target Audience
- Revenue operations (RevOps) teams
- Finance operations teams
- Marketing operations and PMO teams