# CatalogSignal > CatalogSignal is the company behind the Commerce Eligibility Index (CEI), a proprietary benchmark that scores how ready a brand's product catalog is to be found, understood, trusted, and recommended by AI shopping assistants, on a 0 to 100 scale. CatalogSignal turns the index into product-level evidence and a prioritized fix plan. Powered by Bubo AI. ## About CatalogSignal is the company; the Commerce Eligibility Index (CEI) is its proprietary AI catalog-readiness benchmark index, scored from 0 to 100. CatalogSignal measures how AI shopping assistants (ChatGPT, Claude, Gemini, Perplexity, and others) read a brand's catalog, then helps make it legible, trustworthy, and recommendable to AI. It is not an SEO tool, not an AI shopping assistant, and not a consultancy. CatalogSignal is powered by Bubo AI, the applied-AI platform of its parent company, Wise Owl Collective. Founders: Mark Wilcox (Head of Strategy), Darcy Bevelacqua (Head of Growth), Kevin Lyons (Head of Data & AI). ## Products CatalogSignal's products are the three CEI tiers: - CEI Diagnose: scores catalog AI-readiness across the CEI's 16 signals, with an executive report, competitive benchmark, and a prioritized action plan. - CEI Activate: generates per-product fix artifacts (structured data / JSON-LD, attribute-gap files, terminology maps, description briefs). - CEI Protect: a pre-publish quality gate that validates new and updated products against brand norms before they go live. ## The CEI framework Five pillars, each a question an AI system implicitly asks before recommending a product: - Foundation: can AI read the catalog? (attribute completeness, terminology consistency, visual quality, video discoverability) - Differentiation: can AI tell products apart? (differentiation strength, tradeoff density, cluster separability) - Retrieval: can AI find the right product for a real query? (retrieval quality, constraint satisfaction) - Integrity: can AI trust the claims? (claim consistency, evidence coverage, owned-review sentiment) - Authority: does the wider internet vouch for the brand? (independent-review sentiment, brand-mention density, AI-assistant discoverability, video authority) The signals describe what the CEI checks. Because AI needs every dimension to work, CEI is weighted so a strong pillar cannot paper over a weak one: the lowest pillar pulls the score. ## How a brand is scored For each brand, CatalogSignal generates about 100 realistic shopping queries from the brand's own product vocabulary (constraint searches, comparisons, use-case and compatibility questions) and puts them to the live assistants directly: ChatGPT, Claude, Gemini, and Perplexity. The test is simple and unforgiving: how often does each assistant actually recommend the brand when a shopper asks a real product question? Run across every assistant and repeated sampling rounds, a single brand's assessment adds up to more than 1,000 queries, enough to tell a stable signal from a lucky or unlucky one-off. ## The technical checks (pass / fail) Before any pillar can score, CEI runs the gate checks an AI agent runs first: bot accessibility (can AI crawlers reach the pages at all?), schema markup (is product data machine-readable?), content structure (is the page parseable without a browser?), FAQ presence, citation optimization, UCP readiness (the agentic-commerce manifest AI agents look for), and ACP readiness. Video today is measured by presence and coverage; deeper video-content grading, such as transcripts and caption alignment, is in development. ## The CEI Benchmark CatalogSignal runs the CEI Benchmark, a proprietary, monthly longitudinal study of AI catalog readiness. It spans 100 brands across ten consumer-retail verticals, scored on all 16 CEI signals, from more than 100,000 AI shopping queries each cycle, and growing. The verticals: Beauty & Cosmetics, Consumer Electronics, Drugstore & Discount Retail, Fashion & Apparel, General Merchandise & Marketplaces, Home & Furniture, Home Improvement, Jewelry & Accessories, Pet Supplies, and Sporting Goods & Outdoor. It establishes per-vertical baselines and tracks how AI readiness shifts over time, so a brand's CEI score can be read in competitive context rather than in isolation. ## Key pages - Home: https://www.catalogsignal.com/ - Problem: https://www.catalogsignal.com/problem - Products: https://www.catalogsignal.com/products - Methodology: https://www.catalogsignal.com/methodology - Proof: https://www.catalogsignal.com/proof - Insights (research and white papers): https://www.catalogsignal.com/insights - Blog (field notes): https://www.catalogsignal.com/blog - FAQ: https://www.catalogsignal.com/faq - About: https://www.catalogsignal.com/about - Contact: https://www.catalogsignal.com/contact ## Contact Email: mark@catalogsignal.com