[Freeday](https://www.freeday.ai) is an AI-driven digital workforce provider helping businesses automate routine tasks. To secure its next investment round and ensure sustainable growth, Freeday required a comprehensive data infrastructure overhaul to standardize SaaS metrics, optimize financial reporting, and integrate analytics across its operations. ## Problem Statement Freeday faced several key data challenges: - **Inconsistent SaaS Metrics Calculation**: Metrics such as net revenue retention, CAC payback period, and ARR growth were not consistently tracked. - **Incomplete CRM and Financial Data**: HubSpot deals lacked structured start and end dates for licenses, and financial data was not categorized according to standard SaaS cost structures. - **Lack of Centralized Reporting**: Investors required a clear-cut monthly performance report integrating financial and commercial data from a single source of truth. - **Need for Embedded Analytics**: Clients and AI engineers required access to standardized performance metrics within the client portal. ## Delivered Solution To address these challenges, we implemented a scalable, cloud-based data infrastructure: 1. **Standardized Data Infrastructure** - Utilized [[Tooling/Extraction/Airbyte]] to extract data from [[HubSpot]], [[Exact Online]], [[InfluxDB]] and other sources. - Consolidated commercial, financial, and product data into [[Snowflake]]. - Implemented [[Cube]] as a semantic layer, ensuring consistent metric definitions across the organization. 2. **Data Transformation & Modeling** - Expanded HubSpot deal and company properties to accurately capture license agreement start and end dates. - Standardized financial data classification using [[dbt]] to align with SaaS cost structures. 3. **Advanced Analytics & Reporting** - Developed an Internal Analytics Dashboard in [[Looker Studio]], offering a real-time view of key SaaS metrics. - Built financial and commercial reports in [[Google Sheets]] tailored for investors, reducing due diligence friction. 4. **Embedded Client Portal Analytics** - Connected Freeday’s client portal to Cube’s [[Semantics API]], enabling real-time access to performance metrics for both clients and AI engineers. - Ensured that all stakeholders discuss and analyze the same standardized data, improving decision-making. ## Results With the new data architecture in place, Freeday achieved the following benefits: - **Investor Readiness**: Management could effortlessly respond to due diligence questions with structured, data-backed insights. - **Consistent & Reliable SaaS Metrics**: Standardized calculations improved business intelligence and investor confidence. - **Integrated Financial Reporting**: Looker Studio dashboards provided a unified view of financial performance. - **Enhanced Client Engagement**: Embedded analytics empowered both AI engineers and clients to optimize digital employee performance using real-time insights. - **Scalability for Future Growth**: The robust data model supports further expansion and advanced analytics use cases.