SaaS Funnel Leakage & Revenue Impact Analysis

Overview

This project simulates a 20,000-user B2B SaaS customer journey to identify revenue leakage across the acquisition → activation → trial → subscription funnel.

The goal was to:

• Identify key funnel bottlenecks
• Diagnose root causes of conversion drop-offs
• Quantify financial impact (ARR)
• Prioritize growth initiatives using data

This project combines product analytics, growth analysis, and revenue modeling.

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Dataset

Synthetic event-based SaaS dataset generated using Python.

• 20,000 users
• 229,000+ events
• 3,654 subscriptions
• Multi-session behavioral simulation
• Channel-level and device-level behavioral differences
• Payment failures and churn modeling included

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Funnel Conversion

Step	Users	Conversion from Previous
Signup	20,000	—
Onboarding Start	16,827	84%
Activation (Create Project)	11,876	70.6%
Trial Start	10,020	84.3%
Subscription	3,654	36.4%

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Key Findings

1️⃣ Activation is the Primary Growth Lever

• Activated users convert at 30.3%
• Non-activated users convert at 0.7%
• 43x conversion uplift

Improving activation by 5 percentage points would result in:

• +303 additional paid users
• ~$296K ARR increase

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2️⃣ Paid Social Underperforms on Activation

Activation Rate by Channel:

Channel	Activation Rate
Referral	75%
Organic	68.7%
Paid Search	59.1%
Partner	57.5%
Paid Social	43.4%

Closing the activation gap between Paid Social and Organic could generate:

• +386 additional paid users
• ~$377K ARR annually

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3️⃣ Mobile Checkout Friction

Trial → Paid Conversion:

Device	Conversion
Web	38.1%
Mobile	32.4%

Payment Failure Rate:

Device	Failure Rate
Web	5.5%
Mobile	13.7%

Mobile experiences a 2.5x higher payment failure rate.

Reducing mobile failure to web levels could generate:

• +91 paid users
• ~$89K ARR annually

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Revenue Opportunity Summary

Initiative	Estimated ARR Impact
Improve Paid Social Activation	~$377K
Reduce Mobile Checkout Failures	~$89K
Activation Improvement (5pp overall)	~$296K

Total Identified Revenue Opportunity: ~$466K+ annually

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Visualizations

Funnel Overview

Activation by Channel

Payment Failure Rate by Device

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Strategic Recommendations

1. Prioritize activation improvements for Paid Social users
2. Optimize mobile checkout reliability and payment UX
3. Focus growth efforts on high-performing channels (Referral & Organic)
4. Improve onboarding UX to increase activation rate

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Tech Stack

• Python
• Pandas
• NumPy
• Matplotlib
• Faker (data simulation)
• Jupyter Notebook

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How to Run

pip install -r requirements.txt
python src/generate_data.py

Why This Project Matters

This project demonstrates:

• Funnel analytics
• Product & growth analysis
• Segmented conversion modeling
• Checkout friction diagnostics
• Revenue impact simulation
• Strategic prioritization using data

It bridges the gap between analytics and business decision-making.