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Course Outline
Overview of WrenAI Spreadsheets and the Metrics Library
- Key capabilities and practical use cases
- Distinguishing features from traditional spreadsheets
- Introduction to the pre-built metrics collection
Starting with AI-Powered Spreadsheets
- Creating and styling spreadsheets
- Utilizing natural language for formulas and queries
- Employing AI assistance for data preparation
Utilizing the Metrics Library
- Reviewing standardized KPIs across different departments
- Configuring metrics for RevOps, finance, and marketing
- Best practices for ensuring consistency and accuracy
Data Connectivity and Real-Time Updates
- Linking spreadsheets to databases and SaaS tools
- Automating data refresh cycles
- Managing permissions and access controls
Operational Reporting Workflows
- Developing recurring reports using templates
- Monitoring cross-functional performance indicators
- Setting up automated alerts and notifications
Visualization and Collaboration
- Generating charts and dashboards from spreadsheet data
- Collaborating with team members in real time
- Publishing reports for stakeholders
Scaling Operational Analytics
- Implementing the metrics library across multiple business units
- Standardizing reporting processes on an enterprise-wide scale
- Integrating with existing BI platforms
Advanced Features and Future Possibilities
- Discovering AI-driven forecasting within spreadsheets
- Customizing and expanding the metrics library
- Upcoming features in WrenAI operational analytics
Conclusion and Next Steps
Requirements
- A basic understanding of operational reporting concepts
- Prior experience working with spreadsheets
- Familiarity with business metrics and KPIs
Target Audience
- Revenue operations (RevOps) teams
- Finance operations teams
- Marketing operations and PMO teams
14 Hours
