Referral Programs for Transactional AI/ML (Growth)
Referral Programs playbook for transactional AI/ML companies at Growth. Tailored to the transactional business model with implementation steps and expert guidance.
Timeline: 2-4 weeks
Prerequisites
- ✓ Product-market fit
- ✓ Analytics tracking key events
- ✓ Budget for 2-4 weeks
Step-by-Step Guide
Discovery & Audit phase for referral programs in ai-ml. Focus on understanding the landscape and planning.
Strategy Design phase for referral programs in ai-ml. Focus on understanding the landscape and planning.
Initial Implementation phase for referral programs in ai-ml. Focus on execution and iteration.
Measurement Setup phase for referral programs in ai-ml. Focus on execution and iteration.
Optimization Cycle phase for referral programs in ai-ml. Focus on execution and iteration.
Scale & Systematize phase for referral programs in ai-ml. Focus on execution and iteration.
Expected Outcomes
- ✓ Validated referral programs for transactional AI/ML
- ✓ KPI baselines established
- ✓ Growth process documented
KPIs to Track
- ● Time to First Referral
- ● Referral Rate
- ● Referred User LTV
- ● Program Participation Rate
- ● Viral Coefficient
Common Mistakes to Avoid
Ehsan's Growth Commentary
After working with 93+ AI/ML companies, the pattern is clear: Referral Programs at the Growth stage requires systematic processes. The teams that win start smaller than they think they should and iterate 3x faster than their competitors.
With 200-500 people and $15-50M budget, focus Referral Programs efforts on the single highest-ROI activity. Do not spread thin across multiple sub-channels. Validate one approach before adding another.
Ehsan Jahandarpour
AI Growth Strategist & Fractional CMO
Forbes Top 20 Growth Hacker · TEDx Speaker · 716 Academic Citations · Ex-Microsoft · CMO at FirstWave (ASX:FCT) · Forbes Communications Council