About

Most Marketing Systems Are Broken. Few Companies Know Where.

Marketing activity is not the issue. Measurement and diagnosis are.

Using structured analysis, attribution modeling, and performance diagnostics, I identify where your system is failing and where revenue is being lost.

About

Clarity Before Growth

I’m Cliff. I work with companies to bring clarity to what is actually happening in their marketing.

Not what dashboards suggest.
Not what reports claim.
But what is truly driving performance and what is quietly draining budget.

Most marketing looks fine on the surface. Traffic is coming in. Leads are being generated. Campaigns are active.

But underneath, the fundamentals are often broken.

Attribution is misleading.
Conversion paths are inefficient.
Budget is being scaled in the wrong places.

The issue is not effort. It is visibility.

Experience

Built on Real Performance, Not Vanity Metrics

Over the past 15 years, I have managed over $30 million in marketing spend and helped companies scale revenue across SaaS, tech, and lead generation.

My focus has always been the same. Identify what is actually working, eliminate what is not, and improve efficiency at every stage of the funnel.

Most marketing performance is inflated by surface level metrics.

Branded search.
Misleading attribution.
Weak conversion systems.

I focus on what actually drives revenue, not what looks good in a report.

What I Actually Look At

What I Analyze

When I audit a marketing system, I am not looking at surface metrics. I break down how performance is actually generated.

  • Attribution accuracy across channels
  • Cost per acquisition vs true customer value
  • Conversion drop-offs across the funnel
  • Lead quality and downstream revenue impact
  • Speed to lead and sales follow-up efficiency
  • Channel level profitability, not just cost per lead

What I Typically Find

Common Problems I Find

Most systems are not completely broken. They are inefficient in ways that compound over time.

  • Paid campaigns optimized for the wrong metrics
  • Strong top-of-funnel with weak conversion paths
  • Over-reliance on branded search inflating performance
  • Misleading attribution hiding underperforming channels
  • Budget being scaled before the system is ready

Before vs After Thinking

Before vs After

Before:

  • Decisions based on incomplete data
  • Budget allocated based on surface metrics
  • Growth feels inconsistent or unpredictable

After:

  • Clear understanding of what drives revenue
  • Budget allocated based on performance reality
  • Scalable and repeatable growth