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AI-Driven Revenue Growth

Spearheading an AI-led strategy to achieve a 38% increase in Annual Recurring Revenue.

2 years
Senior Product Manager at Vendasta
B2B SaaSAI/MLGTM StrategyGrowth
Case Study: AI-Driven Revenue Growth

The Problem

Understanding the challenge

The company's sales team was struggling with inefficient lead qualification from a high-volume freemium model, which hampered conversion rates and slowed revenue growth in a competitive market.

Key Challenges

  • Low user engagement and retention rates
  • Competing priorities across multiple teams
  • Limited data visibility and insights

The Solution

Strategic approach and implementation

I conceived and launched an AI-driven lead scoring system integrated within the CRM to prioritize high-intent leads. I also spearheaded the GTM strategy shift from a costly freemium model to a focused 14-day trial, creating a more qualified user pipeline and improving time-to-value.

The Results

Quantifiable impact and business outcomes

38%

ARR Increase

32%

Sales Conversion Boost

200%

Day 1 User Retention

40%

Reduction in User Issues

Business Impact

This strategic shift not only drove significant top-line revenue growth but also improved sales team efficiency and overall customer satisfaction by focusing efforts on the most promising leads.

Leadership Insight

Key learnings and strategic takeaways

Key Learnings

  • AI is most powerful when it solves a well-understood human and business need.
  • Sometimes, attracting fewer, more qualified users is more profitable than attracting many.
  • A seamless onboarding experience is critical for converting trial users to paid customers.

What's Next

Continue to refine the lead scoring model with new data and expand the targeted onboarding flows to other user segments.

Deep Dive Available

I have detailed technical documentation and specific KPIs available for this project. Let's discuss how these insights apply to your current roadmap.