SaaS Revenue Optimization
Pricing strategy, customer journey redesign, and market expansion to unlock new growth.
247%
Revenue Increase
8.3x
ROI Multiple
14 days
Implementation
Context & Challenges
A mid-market B2B SaaS platform with strong PMF but flat growth and rising CAC. Pricing tiers were product-driven, not value-based. Onboarding drop-off and underserved segments limited expansion.
Approach
- Value-based pricing and packaging redesign with conjoint-informed guardrails.
- Journey mapping for trial-to-paid and expansion motions; friction removals.
- ICP segmentation; new entry SKU for self-serve and land-and-expand.
- Experiment system: weekly pricing/offer tests with AI-assisted analysis.
Outcomes
- ARPU lift from re-tiering; improved conversion on optimized trials.
- Lower payback period and improved LTV/CAC through upsell paths.
- New segment acquisition with minimal incremental cost.
Artifacts
- Pricing grid and guardrail model
- Onboarding flow wireframes
- Experiment tracker with win/loss log
System components
- Event intake → revenue pipeline → KPI dashboard
- Automated weekly ARR and cohort reports
- Alerting: churn, credit risk, billing failures
Result: a complete operational system—foundation for larger AI programs.
Discuss revenue optimizationBusiness impact
We model revenue outcomes and track against baseline using standardized SaaS metrics.
Before → After (60–90 days)
| Metric | Baseline | After |
|---|---|---|
| MRR | $420k | $520k (+24%) |
| NRR | 96% | 107% (+11 pts) |
| ACV | $18.5k | $22.4k (+21%) |
| Gross margin | 74% | 80% (+6 pts) |
Where the value comes from
- Packaging and guardrails move ACV and MRR.
- Onboarding and upsell journeys lift NRR via expansion and reduced churn.
- Automation reduces COGS, raising gross margin.
Levers: pricing tiers, discount bands, trial-to-paid friction, activation prompts, renewal offers, credit/collections automation.