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Duration 14 hours
Course Outline
Introduction to WrenAI Spreadsheets and the Metrics Library
- Overview of features and practical applications
- Key distinctions from conventional spreadsheets
- Introduction to pre-configured metrics
Getting Started with AI-Powered Spreadsheets
- Creating and formatting spreadsheets
- Using natural language for formulas and queries
- Leveraging AI support for data preparation
Utilizing the Metrics Library
- Reviewing standardized KPIs across various departments
- Setting up metrics for RevOps, finance, and marketing
- Best practices for maintaining consistency and accuracy
Data Connectivity and Real-Time Updates
- Linking spreadsheets to databases and SaaS tools
- Automating data refresh intervals
- Managing permissions and access controls
Operational Reporting Workflows
- Developing recurring reports using templates
- Monitoring cross-functional performance indicators
- Automating alerts and notifications
Visualization and Sharing
- Generating charts and dashboards from spreadsheets
- Collaborating with team members in real-time
- Distributing reports to stakeholders
Scaling Operational Analytics
- Implementing the metrics library across multiple business units
- Standardizing reporting processes across the enterprise
- Integrating with existing BI platforms
Advanced Features and Future Capabilities
- Exploring AI-based forecasting in spreadsheets
- Customizing and expanding the metrics library
- Upcoming enhancements in WrenAI operational analytics
Summary and Next Steps
Requirements
- A solid grasp of operational reporting principles
- Proficiency with spreadsheet applications
- Knowledge of business metrics and KPIs
Target Audience
- Revenue operations (RevOps) teams
- Finance operations teams
- Marketing operations and PMO teams