Revenue Operations Analytics

SaaS deal desk analytics using BigQuery, SQL, and Looker Studio

Project Overview

Analysis of 9,994 SaaS transactions (2020-2023) across 99 customers, 14 products, and 48 countries to uncover revenue optimization opportunities.

Key Finding

Discounts above 20% destroy profitability across all segments:

• No Discount: +320,988 EUR profit (29.5% margin)
• High Discount (41%+): -99,559 EUR loss (-77.4% margin)
• Recommendation: Cap discounts at 20% to protect 135K+ EUR in annual profit

Technologies

• BigQuery - Cloud data warehouse
• SQL - CTEs, window functions, aggregations
• Looker Studio - Interactive dashboard
• Python - Data extraction (kagglehub)

Project Structure

sql/
    01_explore_schema.sql        # Data exploration and profiling
    02_data_cleaning.sql         # Cleaning view with derived metrics
    03_revenue_analysis.sql      # MRR, discount impact, YoY growth, CLV
looker_studio/
    dashboard_config.md          # Dashboard documentation and link

Dashboard

View Looker Studio Dashboard

Analysis Highlights

• Monthly Revenue Trend: Consistent growth from 1K EUR (Jan 2020) to 110K+ EUR (Dec 2023)
• Discount Impact: 1,393 deals with over 20% discount destroyed 135K EUR in profit
• Segment Growth: Enterprise surged 51.5% YoY in 2023
• Discount Abuse Detection: Flagged high-discount contacts for deal desk review

Skills Demonstrated

SQL (CTEs, Window Functions, CASE), BigQuery, Looker Studio, Revenue Operations, Deal Desk Analytics