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The Challenge

• These B2B teams across a $4B organization shipped on gut feel, not data.
• The conversion funnel was unpredictable.
• Dev and design hours went to features that earned $0.

Key problems

• No A/B testing discipline.
• Inconsistent conversion rates.
• Teams couldn’t tell which change worked (or why).

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What I Did

• Built a scalable A/B framework that tests hypotheses, not hunches.
• Built a backlog that powered 200+ tests on pages, CTAs, and flows
• Mapped the end-to-end customer journey to identify conversion drop-offs.
• Mapped the full journey to spot conversion drop-offs.
• Aligned growth, design, and engineering on testable ideas.
• Created feedback loops so results feed into prioritization.

How I Think

I test assumptions, not features.

This product experimentation system:

• Cut debate cycles.
• Saved engineering and design time.
• Delivered compounding learning across a $4B organizational portfolio.

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Results

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🚀 Up to 2x improvement in conversion rates.

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📉 Reduced resource waste across design/dev.

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🧪 200+ tests executed in a structured cadence.

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💬 Stakeholders now debate data, not opinion.

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Client name under NDA.

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Targeting to Staff, Principal, or Lead Product Roles

Series A-F funded SaaS stuck between $500K-$10M ARR?

Need someone who speaks both product and revenue?

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Message me → LinkedIn

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Darpan Dadhaniya

Toronto, Canada

About Me

Leadership Values

Case Studies

Product Thinking

• Sitemap

  Playbooks

Product-Led Growth

Activation Playbook

Product Foundations

Metrics Playbook

Roadmap Playbook

Prioritization Playbook

Experiments Playbook

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