Case Studies

Results, not
recommendations

Every outcome below was measured with statistical rigor. No inflated claims, no cherry-picked metrics — just documented results from growth systems that compound.

B2B Services Experimentation · Instrumentation

50% Lift in Lead-to-Order Conversion Rate

Challenge

A B2B services company had a 8% lead-to-order conversion rate and no visibility into where or why leads were dropping out of the funnel. Growth decisions were being made on channel-level CPL data, not funnel-level performance data.

What We Did

Instrumented the full conversion funnel with event tracking. Diagnosed the primary drop-off stage. Formed and prioritized hypotheses. Designed and executed a statistically powered A/B test with predefined success criteria and guardrail metrics.

8% → 12%

Lead-to-order conversion rate

50%

Relative improvement

p=0.01

Statistical confidence

SaaS Experimentation · Growth Foundations

33% Lift in Free-Trial to Paid Conversion

Challenge

A Series B SaaS company had strong top-of-funnel but poor trial-to-paid conversion. Activation events were undefined, onboarding was undifferentiated, and there was no experimentation infrastructure to test improvements systematically.

What We Did

Defined and instrumented activation events. Built a behavioral signal model to identify high-intent trial users. Designed an onboarding sequence experiment. Ran with proper statistical power and iterated on validated findings.

33%

Relative lift in trial-to-paid CVR

p=0.01

Statistical confidence

Series B

Company stage

PE-backed Platform Automation · Unit Economics

COGS Reduced from 50% to 38%, Margin Expanded to 47%

Challenge

A PE-backed platform had COGS at 50% of revenue with delivery operations heavily dependent on manual workflows. Contribution margin was 35% — well below the threshold needed to demonstrate scalable unit economics to the board.

What We Did

Mapped all delivery workflows. Identified automation opportunities by time-cost impact. Deployed AI agents for research and summarization tasks. Automated reporting, client communication sequences, and internal handoffs. Rebuilt operational SOPs around the new workflows.

50% → 38%

COGS as % of revenue

35% → 47%

Contribution margin

70–80%

Manual effort reduction

Multi-location Business Instrumentation · Retention Automation

20–30% Increase in Repeat Revenue Through Retention Systems

Challenge

A multi-location business had strong acquisition but poor repeat purchase rates. No retention system existed — reactivation was ad-hoc and inconsistent. There was no visibility into which customers were at risk of churning versus which were primed for expansion.

What We Did

Instrumented purchase frequency and engagement signals. Built a customer health model to segment by retention risk. Deployed automated retention, reminder, and reactivation workflows triggered by behavioral signals. Established a repeat revenue dashboard for ongoing management.

+20–30%

Repeat revenue increase

Automated

Retention trigger system

0 FTE

Added to manage the system

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