The Commerce Eligibility Index™ (CEI) — Who We Are and Why We Built This
The AI Shelf Is the New Shelf
Something fundamental is changing in how people find products.
For twenty years, the path to purchase looked the same: a consumer typed a query into a search engine, clicked a link, and landed on a product page. Brands optimized for that path — better SEO, better ads, better landing pages.
That path is breaking.
Today, a growing share of product discovery starts with an AI assistant. A shopper asks ChatGPT for the best running shoes under $150. A procurement manager asks Claude to compare industrial suppliers. A parent asks Gemini for a car seat that fits a specific vehicle.
The data is clear:
37% of consumers now start product searches in AI tools rather than search engines (Eight Oh Two, January 2026)
58.5% of Google searches end with no click at all (SparkToro/Datos, 2024)
AI-influenced transactions reached $262 billion globally in the 2025 holiday season alone (Salesforce)
Gartner projects search engine volume will drop 25% by 2026 as AI assistants absorb discovery traffic
This isn't a future trend. It's happening now.
The Problem No One Is Measuring
Here's what most brands haven't realized: the product catalogs they've spent years building were designed for humans, not machines.
A human shopper can look at a product page with a missing material field, inconsistent sizing labels, and a vague description — and still figure out what they're looking at. Humans infer. Humans tolerate ambiguity. Humans fill in gaps.
AI agents cannot.
When an AI shopping assistant evaluates your catalog, it needs structured, consistent, unambiguous data. If your product descriptions contradict each other, the AI loses confidence. If your attributes are incomplete, the AI can't match your products to specific queries. If your terminology is inconsistent — calling the same fabric "microfiber" in one listing and "ultra-soft poly blend" in another — the AI treats them as different things.
The result: AI systems quietly bypass your products in favor of catalogs they can interpret with higher confidence. You don't get an error message. You don't get a notification. Your products simply don't appear in the recommendation.
We call this the invisible shelf problem. And until now, there was no way to measure it.
Who We Are
The Commerce Eligibility Index™ (CEI) was built by three co-founders who saw the same problem from different angles — and realized no one was solving it.
Darcy Bevelacqua, Head of Strategy. Darcy brings over fifteen years of management consulting experience at firms like Accenture, with deep relationships across the retail landscape. She knows how brands actually operate — the procurement cycles, the internal politics, the gap between what a digital team wants to do and what the organization will fund. Darcy owns client sourcing, pricing strategy, and delivery quality assurance. When we say our reports are board-ready, it's because Darcy makes sure they are.
Kevin Lyons, Head of Data & AI. Kevin spent two decades building machine learning systems at the intersection of commerce and data — including nearly a decade at Nielsen, where he led R&D teams that classified over two billion digital interactions daily using self-learning models. Before that, he built the ML infrastructure at eXelate (acquired by Nielsen) and led analytics services at Acxiom. Kevin designed the 16-signal scoring engine that powers the Commerce Eligibility Index and owns all product and platform decisions.
Mark Wilcox, Head of Growth. Mark has a deep command of how search, discovery, and visibility are evolving — from the old world of SEO to the new world of AI-mediated commerce. He builds the CFO-level business cases that translate catalog gaps into revenue exposure, and he leads the executive storytelling that makes our findings actionable in the boardroom. When a CMO needs to understand why their brand is invisible to AI shopping assistants, Mark delivers that readout.
Together, we combine operations and retail credibility, ML engineering and product architecture, and go-to-market strategy. CatalogSignal exists because we each saw the same gap from our respective vantage points: brands have data, but they don't have data that machines can use — and most don't know the gap exists until it costs them.
We founded CatalogSignal because we saw this gap widening as AI-mediated commerce accelerated, and we realized no one was measuring it. Plenty of tools audit your SEO. Plenty of tools analyze your ad spend. But nobody was answering the fundamental question:
If an AI shopping assistant looked at your product catalog right now, could it understand and recommend your products?
That's the question The Commerce Eligibility Index answers.
What We Believe
Measure, don't guess. Every finding we deliver is computed from your actual catalog data using repeatable methods. No surveys. No subjective assessments. No opinions dressed up as insights.
Every claim has receipts. When we tell you that 340 of your 1,100 SKUs have structural problems, we show you exactly which products, what the problems are, and what to fix first. Product-level evidence, not abstract scores.
Fix what moves the needle. Not all catalog improvements are equal. We prioritize recommendations by impact and effort, so you know which three changes will move your score the most — and which ones can wait.
Transparency about what we don't know. Our reports explicitly disclose what was measurable versus what wasn't. If we couldn't evaluate a signal because the data wasn't available, we say so. We'd rather be honest about our confidence than inflate a score.
Why This Matters Now
The window for getting ahead of AI-mediated commerce is closing. Early movers who structure their catalogs for machine reasoning will capture disproportionate share of AI-driven recommendations. Brands that wait will find themselves invisible on the AI shelf — competing not just against other brands, but against the structural quality of those brands' data.
This isn't about AI hype. It's about data quality meeting a new distribution channel. And like every channel shift before it — from print to web, from desktop to mobile — the brands that adapt their data first will win.
We built The Commerce Eligibility Index to help you measure where you stand, understand what to fix, and track your progress over time. Because in the age of AI commerce, your catalog isn't just a product listing.
It's your most important competitive asset.
The Commerce Eligibility Index is an AI readiness diagnostic for retail product catalogs, powered by Bubo AI™. Learn more at catalogsignal.com.