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TemplateFREE⏱️ 45-90 minutes

Product Catalog Specification Template

Free product catalog specification template for e-commerce PMs. Covers data models, taxonomy, attribute management, and a filled example for a...

Updated 2026-03-04
Product Catalog Specification
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Frequently Asked Questions

How many levels should the category tree have?+
Three levels is the practical sweet spot for most e-commerce catalogs. Two levels is too flat for filtering and navigation. Four or more levels creates confusion for both shoppers and content teams. If a subcategory has fewer than 10 products, it probably does not need its own node. Use attributes (size, material, style) for finer segmentation instead of deeper nesting.
How do I handle products that fit multiple categories?+
Assign one primary category and allow secondary category references. The primary category determines required attributes and the canonical URL. Secondary categories enable the product to appear in additional browse paths. Avoid duplicating the product listing. Instead, use soft references so updates propagate from a single source of truth.
What image specifications should I require?+
At minimum, require a primary image at 1200x1200 pixels on a white background. This ensures consistency across search results and category pages. For apparel and home goods, require 4-6 images including detail shots and lifestyle context. Define maximum file sizes (typically 2-5 MB) and accepted formats (JPEG, WebP, PNG). Enforce these requirements in the upload API, not through manual review.
How often should taxonomy be updated?+
Review quarterly, but only change when data supports it. Track search queries that return zero results, filter usage by category, and category page [bounce rates](/glossary/prioritization). These signals reveal where taxonomy gaps exist. Major restructuring should happen at most once per year, with a migration plan that includes URL redirects and seller notification.
How do I manage catalog data quality at scale?+
Implement automated quality scoring that runs on every product create and update. Set a minimum score threshold (e.g., 70/100) that blocks publication. Track quality scores by seller, category, and attribute to identify systemic gaps. Review the lowest-scoring listings weekly and feed patterns back into seller education and validation rules. The [product analytics approach](/analytics-guide) applies here: measure, identify patterns, and fix the system, not individual listings. ---

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