Data Strategy & Infrastructure for PE-Backed SaaS Growth ($1M to $5M ARR Goal)
The Challenge
A rapidly scaling PE-backed B2B SaaS company ($1M ARR) faced significant operational friction due to siloed data across Salesforce, accounting software, and product usage databases. This resulted in unreliable ARR forecasting, inefficient sales processes, lack of clear KPIs for investors, and difficulty proving value.
Approach & Execution
Project Overview
The client, a promising PE-backed B2B SaaS provider in the [Specific Industry] sector, needed to professionalize its data operations to support ambitious growth targets ($1M -> $5M ARR). Disparate systems and lack of data discipline created significant reporting challenges and hindered strategic decision-making required by both management and investors.
My Role & Work Done
As the lead data strategist and technical implementer:
- Stakeholder Alignment: Facilitated workshops with C-suite, Sales, Finance, Product, and PE stakeholders to define critical KPIs (aligned with investor reporting needs) and dashboard requirements.
- Data Infrastructure Architecture: Designed the ETL process and data warehouse schema to integrate data from Salesforce, financial systems (e.g., QuickBooks, Xero), and product analytics (e.g., Mixpanel, Segment).
- Data Transformation & Modeling: Developed SQL and R scripts for data cleaning, transformation, and calculation of standardized KPIs (MRR, Net Retention, LTV:CAC, etc.).
- BI Implementation: Built comprehensive dashboards in Looker (or specified BI tool), providing tailored views for different audiences (Executive Summary, Sales Pipeline Analysis, Rep Performance, Financial Metrics).
- CRM Process Optimization: Collaborated with the VP Sales to audit and refine Salesforce stages, required fields, and data entry processes to improve pipeline integrity and forecast reliability.
- Training & Handover: Provided training and documentation to enable internal teams to utilize and maintain the new reporting system.
Challenges
Integrating diverse data sources with varying levels of quality, defining universally accepted KPI logic across departments, and driving adoption of new CRM processes were key challenges overcome through meticulous planning, technical expertise, and strong stakeholder communication.
Solution Overview
Designed and led the implementation of a centralized data warehouse (e.g., BigQuery/Snowflake) integrating data from key sources via API and ETL processes (using R/SQL). Standardized KPI definitions (MRR, Churn, LTV, CAC, Pipeline Velocity) across departments. Built interactive dashboards in Looker providing real-time, trusted insights tailored for C-suite, Sales, Finance, and Investors. Led CRM data cleansing and process optimization efforts.
Key Results & Impact
- Enabled reliable, data-driven ARR forecasting, crucial for strategic planning towards the $5M ARR target.
- Provided leadership and investors with clear, consistent visibility into pipeline health, sales performance, and key SaaS metrics.
- Created a single source of truth, unifying data from Salesforce, finance, and product analytics.
- Reduced time spent by Finance and Ops on manual reporting by ~80%.
- Improved sales team accountability and CRM data discipline through process changes and transparent reporting.