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Duration 14 hours
Course Outline
Introduction to WrenAI Spreadsheets and the Metrics Library
- Overview of core capabilities and practical use cases
- Key distinctions from traditional spreadsheet tools
- Introduction to pre-built metrics
Getting Started with AI-Powered Spreadsheets
- Creating and formatting spreadsheets effectively
- Utilizing natural language for formulas and queries
- Applying AI assistance to streamline data preparation
Working with the Metrics Library
- Exploring standardized KPIs across different departments
- Configuring metrics for RevOps, finance, and marketing
- Best practices for ensuring consistency and accuracy
Data Connectivity and Live Updates
- Connecting spreadsheets to databases and SaaS applications
- Automating data refresh cycles
- Managing permissions and access controls
Operational Reporting Workflows
- Building recurring reports using templates
- Tracking cross-functional performance indicators
- Automating alerts and notifications
Visualization and Sharing
- Generating charts and dashboards from spreadsheet data
- Collaborating with team members in real time
- Publishing reports for stakeholders
Scaling Operational Analytics
- Applying 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-driven forecasting within spreadsheets
- Customizing and extending the metrics library
- Upcoming features in WrenAI operational analytics
Summary and Next Steps
Requirements
- A solid grasp of operational reporting concepts
- Practical experience with spreadsheet applications
- Familiarity with business metrics and KPIs
Target Audience
- Revenue operations (RevOps) teams
- Finance operations teams
- Marketing operations and PMO teams