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Catalog Quality Scoring

Audit, Score, and Optimize Every Listing — With AI Precision

CatalogIQ scores your catalog against 9 key dimensions and recommends smart fixes for inconsistent, incomplete, or off-brand content — before it reaches the buyer.


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Before you can optimize your catalog, you need to understand it. CatalogIQ’s Catalog Quality Scoring engine analyzes every product listing across 9 dimensions — from completeness and consistency to content quality and relevance. It benchmarks performance, surfaces gaps, and delivers AI-powered recommendations to strengthen product content, fast.

HOW CATALOG QUALITY SCORING WORKS

Audit, Score, and Enrich Every Listing - With AI Precision

CatalogIQ quality scores your catalog content against 9 key dimensions and recommends smart fixes for inconsistent, incomplete, or off-brand content — before it reaches the buyer.

ASSESS

Upload & Map Catalog for Scoring

CatalogIQ ingests your product catalog and prepares it for detailed scoring and enrichment.

  • Upload full or partial catalogs in any format
  • Map catalog attributes to standardized field definitions
  • Identify product types and category-level metadata
  • Flag incomplete or unsupported data fields before scoring.
SCORE

Set Rules & Run Quality Analysis

Define how your catalog should be scored across 9 quality dimensions, then run CatalogIQ’s scoring engine.

  • Choose default or custom scoring rules by category
  • Evaluate completeness, consistency, accuracy, and more
  • Automatically benchmark against industry standards
  • Generate an overall Catalog Quality Score and dimension-level results
DIAGNOSE

Review Scorecard & AI Insights & Actions

Explore in-depth scorecards with AI-generated insights to identify where and how to improve catalog quality.

  • View detailed performance by dimension, attribute, and product type
  • See error types, data gaps, and off-brand issues
  • Receive prioritized suggestions with estimated impact
  • Drill into low-performing SKUs for guided triage
ENRICH

Apply Fixes & Optimize Content

Use AI to enrich product data and improve low-scoring content at scale

  • Accept or modify AI-generated content recommendations
  • Auto-fill missing data and correct errors
  • Standardize formats, terms, and field consistency
  • Re-run scoring to measure quality gains after enrichment

The Catalog Quality Scoring Stack That Measures What Matters

Quality Scorecard in 9 Dimensions

Measure What Matters Most

Evaluate every SKU across key quality factors like accuracy, coverage, completeness, and structure. Build a data-driven roadmap for improvement across all product lines, brands, and catalog segments.

Competitive Catalog Benchmarking

See How You Stack Up

Compare your catalog quality to peers and industry leaders across key scoring dimensions. Identify gaps, surface strengths, and prioritize where your team should focus to improve performance and stay competitive.

AI-Powered Insights & Actions

Turn Scores Into Solutions

Get SKU-level recommendations, prioritized fix lists, and action plans tailored to your catalog’s weaknesses. Eliminate guesswork and go from diagnostics to execution - fast, scalable, and fully actionable in just one click.

Turn Insight into Action

Before you can improve your product catalog, you need to understand it. CatalogIQ’s Catalog Quality Scoring engine evaluates your product content across nine essential dimensions - then layers on competitive benchmarks and AI-powered recommendations to turn diagnostics into decisions.

Whether you're struggling with inconsistent data, declining performance, or unclear priorities, our scoring system gives your team the clarity and confidence to act—faster.

Frequently Asked Questions for Catalog Quality Scoring

What is Catalog Quality Scoring?

Answer: Catalog Quality 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.

Know Your Score. Fix What Matters.

Get instant insight into your catalog’s health - then act with confidence.


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