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Duration 14 hours
Course Outline
Introduction to WrenAI Spreadsheets and the Metrics Library
- Overview of features and practical applications
- Distinguishing these tools from conventional spreadsheets
- Exploring the integration of pre-built metrics
Getting Started with AI-Driven Spreadsheets
- Creating and structuring spreadsheets
- Utilizing natural language for formulas and queries
- Leveraging AI assistance for data preparation
Navigating the Metrics Library
- Reviewing standardized KPIs across various departments
- Tailoring metrics for RevOps, finance, and marketing teams
- Ensuring consistency and precision through best practices
Data Integration and Real-Time Updates
- Connecting spreadsheets to databases and SaaS platforms
- Automating data refresh schedules
- Overseeing permissions and access controls
Designing Operational Reporting Workflows
- Generating recurring reports using templates
- Monitoring cross-functional performance metrics
- Setting up automated alerts and notifications
Visualization and Distribution
- Developing charts and dashboards from spreadsheet data
- Collaborating with colleagues in a real-time environment
- Sharing reports with key stakeholders
Expanding Operational Analytics
- Implementing the metrics library across multiple business units
- Standardizing reporting procedures on an enterprise scale
- Integrating with current BI platforms
Advanced Capabilities and Future Developments
- Investigating AI-based forecasting within spreadsheets
- Adapting and expanding the metrics library
- Previewing upcoming features in WrenAI operational analytics
Wrap-up and Recommendations for Next Steps
Requirements
- A foundational grasp of operational reporting principles
- Proficiency in using spreadsheets
- Awareness of business metrics and KPIs
Target Audience
- Revenue Operations (RevOps) teams
- Finance Operations teams
- Marketing Operations and PMO teams