CriticalKPI
CriticalKPI

Measure what matters.
Chasing one metric costs you the rest.

Real performance gains come from focusing on the right KPI — then executing relentlessly. That's how I've driven outcomes across marketing, design, product discovery, and ecommerce personalization.

Now I bring the same discipline to product content optimization with CatalogIQ — AI catalog enrichment that improves product discoverability, increases engagement, and drives higher conversion.

For manufacturers, distributors, retailers, and marketplaces in modern commerce.

Optimized discovery & conversion for enterprise retail

Core focus areas

Signal over noise — applied.

Four disciplines that turn catalog and commerce data into measurable performance.

Catalog Intelligence

Your catalog isn't content. It's infrastructure.

  • Attribute modeling & normalization
  • Data quality scoring
  • Enrichment frameworks
  • Governance systems
See CatalogIQ In Action

Commerce Diagnostics

I don't chase symptoms. I isolate root causes.

  • KPI audits
  • Funnel diagnostics
  • Catalog performance breakdown
  • Competitive signal benchmarking

Product Discovery

If customers can't find it, you can't sell it.

  • Search relevance & tuning
  • Taxonomy architecture
  • Faceting & filtering strategy
  • Zero-click discovery alignment

Testing & Optimization

Stop guessing. Start compounding.

  • Experimentation frameworks
  • KPI definition & success modeling
  • Conversion system design
  • Governance over random testing
Catalog Quality

Catalog quality used to be a vague worry. Now it is a number you can act on.

For years, "our data could be better" was a feeling no one could size. CatalogIQ reads every product the way a machine does and turns it into a single score, with the gaps ranked by impact, so you can stop guessing and start sequencing the fix.

2016–2024 · Experimentation at scale

Optimizing how the world's brands sell

At Certona/Monetate and then Reflektion/Sitecore, I spent eight years optimizing ecommerce search, recommendations, and personalization for enterprise retail — Nike, The Home Depot, Gap, Uniqlo, Petco, DSW, Vera Bradley, Finish Line, and dozens more. Thousands of experiments, one question every time: does this actually help the customer find it and buy it?

score("sku-40219") → { readiness: 92, gaps: ["material", "dimensions"], lift_estimate: "+7-10x impressions" }
1,500+A/B & personalization tests
$30M+incremental demand influenced
120+ecommerce optimization audits

Let's talk about your catalog.

Whether it's discovery, experimentation, or getting your product data AI-ready — start with the metric that matters.