Before you can optimize your catalog, you need to understand it.
Audit, Score, and Enrich Every Listing
CatalogIQ’s Catalog Scoring engine analyzes every product listing across completeness, consistency, quality, and relevance, benchmarking performance and delivering AI-powered recommendations to strengthen content, fast.
Upload & map your catalog
CatalogIQ ingests your product catalog and prepares it for detailed scoring and enrichment.
Set rules & run analysis
Define how your catalog should be scored across 9 quality dimensions, then run CatalogIQ’s scoring engine.
Review scorecard
Explore in-depth insights and actions to identify where and how to improve catalog quality.
Apply fixes
Use AI to fill in missing data, correct errors, enrich product data, and improve low-scoring content.
A Stack that Measures What Matters Most
Give your team the clarity and confidence to act faster.
Quality Scorecard
Evaluate Every SKU.
Coverage
Verify that mandatory fields are populated to avoid syndication blocks and filter visibility suppression.
Accuracy & Completeness
Validate specs, measurements, materials, and compatibility details for completeness and traceability.
Relevance & Consistency
Measure how well your language matches real shopper queries and formatting rules across products.
Natural Language
Evaluate tone, clarity, and phrasing to resonate with the way people speak in voice search, chat, and generative AI.
Competitive Benchmark
See How You Stack Up.
SEO & Product Discovery
See how your structured data, keyword usage, and content relevance compare to organic and on-site searches.
Content Richness & Engagement
Compare your bullet points, images, and descriptions to top-performing product pages delivering clarity and coverage.
Category & Channel Standards
Align with the enrichment, taxonomy, and formatting norms for your industry, niche, and/or channel.
Mobile Optimization
Explore how your catalog layout, image scaling, and mobile readability perform across devices.
AI Insights & Actions
Go From Score to Solution in Seconds.
SKU‑Level Recommendations
Pinpoint issues across every SKU and apply clear, actionable fixes with contextual examples in a single click.
Content Optimization Suggestions
Ship better content faster with readable, editable, and publish-ready content suggestions.
Performance‑Driven Alerts
Catch declines before they cost you with notifications that alert when scores drop, content decays, or issues resurface.
Role‑Based Workflows
Send schema, SEO, and copy fixes to the right teams, tracked through a unified quality framework.

Quality Scorecard
A Clear Path to Higher Conversions.
Accelerate your go-to-market with generative AI and large language models that fill gaps, infer missing attributes, and elevate content quality.
- Import anything from anywhere
- Clean & normalize at scale
- Automate messy inputs into structured, channel-ready listings
Competitive Benchmarks
Templates That Structure, Style, and Ship Your Content.
Blueprint your way to perfect product content. Lock in structure, style, and compliance so every SKU meets your brand and marketplace standards from day one.
- Rule templates
- Voice/tone templates
- Visual templates
- Output templates


AI Insights & Actions
Build complete, structured, and ready-to-publish product catalogs in a fraction of the time.
Accelerate your go-to-market with generative AI and large language models that fill gaps, infer missing attributes, and elevate content quality.
- Import anything from anywhere
- Clean & normalize at scale
- Automate messy inputs into structured, channel-ready listings
Blog
Forecasting Attribute Performance with Search and Predictive Insights
Adding new product attributes to your catalog can drive big wins in search relevance, user experience, and conversions, but only if those attributes actually matter to your customers. Explore how forecasting the impact of new attributes with search volume analysis and predictive modeling helps teams avoid guesswork and scale what converts.
Knowledge Center
Leverage a growing library of best practices and FAQs.
Meet Our Team
The minds behind CatalogIQ!
Frequently Asked Questions
What is Smart Catalog Scoring?
Answer: Smart Catalog Scoring evaluates product content across multiple dimensions - like coverage, completeness, accuracy, and consistency - to identify areas that affect discoverability, search, and customer experience.
Why does catalog quality matter?
Answer: High-quality catalogs rank better in search engines, convert better on PDPs, and enable AI-driven platforms to understand, recommend, and surface your products more effectively.
How are the scores calculated?
Answer: CatalogIQ scores are calculated by evaluating attribute-level data against completeness rules, formatting norms, SEO patterns, and AI-tuned benchmarks for each dimension.
What dimensions does CatalogIQ score?
Answer: CatalogIQ scores against nine dimensions: Coverage, Accuracy, Completeness, Relevancy, Consistency, Natural Language Optimization, Structured Data, Content Quality, and Mobile Optimization.
How can I improve my CatalogIQ score?
Answer: Each scorecard includes targeted AI insights and recommendations - like filling missing fields, correcting inaccuracies, and improving formatting or keyword alignment - to drive up each score dimension.
What’s a good CatalogIQ score?
Answer: A score above 85 is considered strong. Scores below 70 often indicate critical data quality gaps that may hinder SEO, product discovery, or conversions.
Can CatalogIQ score different product types differently?
Answer: Yes. The system supports configurable attribute weights and scoring rules tailored to product types, verticals, and even channels.
Can I export scoring results for reporting?
Answer: Absolutely. Scores and detailed issue reports can be exported as CSVs or integrated into dashboards via API.
How often should I score my catalog?
Answer: We recommend scoring continuously or weekly, especially during seasonal updates, large imports, or new product launches.
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