Available for Remote Contract Work

I Find Where Your
SaaS Revenue Is Leaking

I help B2B SaaS teams find hidden churn risk, MRR leakage, and expansion opportunities — using SQL, Python, and executive dashboards that connect directly to CS action.

$411K Silent MRR risk surfaced
13.8% Enterprise churn identified
98% Churn model recall
2.2M SaaS rows analyzed
See My Diagnostic Offer → View Portfolio
Services

Two Ways to Work Together

Start low-risk with a 3-day diagnostic. If the findings are valuable, we go deeper with a full audit.

⚡ Start Here
3 Days
SaaS Revenue Leak Diagnostic
$250–$500 / engagement
  • Data quality & completeness review
  • KPI / metric definition check
  • Initial MRR & churn observations
  • 3–5 churn or revenue risk signals
  • Recommended full audit scope
  • Short executive memo + walkthrough call
  • Milestone payment — no upfront risk
7 Days
SaaS Revenue Leakage Audit
$750–$1,500 / engagement
  • Full MRR waterfall breakdown
  • Churn segmentation (plan, industry, channel)
  • Usage decay & silent churn analysis
  • Feature adoption vs retention mapping
  • Support / CSAT risk analysis
  • High-risk account list (CS-ready)
  • Executive dashboard + 30-min walkthrough
  • 1-page action memo for CS / Growth / Product
Portfolio

Revenue Analytics Projects

Real analytical work. Real findings. Packaged the way a founder or CS lead actually reads it.

B2B SaaS Analytics ✓ Completed · 8 Chapters
Velocity SaaS — Revenue Turnaround Analysis
End-to-end revenue diagnostic on a 2,000-account, 2.2M-row B2B SaaS dataset

A full 8-chapter SaaS revenue analytics project. Net New MRR collapsed to $852 in Jan 2024 as churn absorbed gross gains. Enterprise churn hit 13.8%. $411K in MRR identified at silent risk from usage decay. SSO, Webhook & Integration adoption mapped as retention moats. Event-led acquisition flagged as weakest channel. Packaged into a live Streamlit churn predictor for CS teams.

$411K Silent MRR at risk identified
$852 Net New MRR Jan 2024 after churn
13.8% Enterprise churn rate
98% Churn model recall (logistic regression)
$281K Organic Search expansion MRR
90% New MRR decline from May 2022 peak
8-Chapter Analysis Covers
Q1 MRR Waterfall Q2 Churn Segmentation Q3 Cohort Retention Q4 Feature Adoption Q5 Support & CSAT Q6 Marketing ROI Q7 Usage Decay Q8 ML Churn Model
SQL · DuckDB Python · Pandas Scikit-learn Logistic Regression Looker Studio Streamlit Matplotlib / Seaborn
▶ Loom — Coming Soon → GitHub ⚡ Streamlit App 📊 Dashboard
E-Commerce Analytics ✓ Completed
Olist E-Commerce Revenue Leakage Analysis
Surfaced $7.2M in revenue opportunity from operational inefficiencies

Analyzed the Olist marketplace dataset to identify operational revenue leakage across shipping delays, order cancellations, and seller performance gaps. Built an executive Looker Studio dashboard with business-ready KPIs and actionable findings — demonstrating the same revenue-framing approach applied to a marketplace context.

$7.2M Revenue opportunity surfaced
SQL Complex CTEs + window functions
Looker Executive dashboard built
SQL DuckDB Looker Studio CTEs & Joins Executive Dashboard
→ GitHub
Technical Stack

What I Work With

Tools chosen for SaaS revenue analytics — not for resume padding.

🗄️
SQL
MRR waterfall, cohort retention, churn segmentation, usage decay. Window functions, CTEs, complex joins — no join duplication.
DuckDBMySQLCTEsWindow Fns
🐍
Python
Data cleaning, feature engineering, churn modeling. Recall optimization, data leakage prevention built in from the start.
PandasScikit-learnLogistic Reg
📊
Dashboards
Executive dashboards for founders — not analysts. KPI scorecards, waterfall charts, risk tables with clear insight labels.
Looker StudioMatplotlibSeaborn
⚡
Streamlit
Live churn predictor — CS teams input account data, get risk scores, see top drivers, export prioritized call lists.
Web AppCSV ExportRisk Scoring
💼
SaaS Metrics
MRR, NRR, GRR, logo vs revenue churn, expansion MRR, ICP definition, cohort LTV — business outcomes, not just metric definitions.
MRR WaterfallNRR / GRRCohorts
✍️
Executive Communication
Findings written for founders and CS leads — not data teams. Action memos, risk summaries, Loom walkthroughs.
Action MemosLoom VideosPDF Reports
Why Trust Me

Common Questions, Honest Answers

I'd rather address these directly than hope you don't ask.

🤖
"Did you just use AI to build this?"
I use AI as a productivity assistant. The metric definitions, SQL logic, model choices, and business recommendations are mine. I'll walk through any query or assumption live on a call.
🎓
"You're still a student — no real experience."
I don't have a corporate title. I have a full 8-chapter revenue analysis on 2.2M rows of SaaS data. Review the GitHub, run the queries, read the findings — then decide.
💸
"What if I pay and you disappear?"
First engagements use milestone payments — small amount upfront, payment after insight preview on Day 2, final payment after delivery. You never pay everything upfront.
📐
"How do I know your findings are accurate?"
Every diagnostic starts with a data quality review — you know what I found, what I couldn't verify, and where confidence is high vs uncertain. Every finding includes auditable logic.
🛠️
"We already have a BI tool."
A diagnostic is a second set of eyes — not a replacement. Most teams have dashboards but haven't done a structured leakage audit. I find what's hiding between the metrics.
🎯
"Can you guarantee results?"
No — and be skeptical of anyone who does. I identify likely leakage points, estimate MRR at risk, and provide prioritised recommendations. Recovery depends on your team's execution.

Ready to Find Where Your Revenue Is Leaking?

Start with a low-risk 3-Day Diagnostic. See the findings first. Decide if a full audit is worth it.

📧 Get in Touch 📄 Sample Audit PDF ▶ Loom — recording next
Connect on LinkedIn → linkedin.com/in/suraj-rajput-155a24404