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What are Catalog Sales?

Catalog sales are purchases generated by catalog (product) ads. Learn how to structure, measure, and improve them.
Brief Definition

Catalog sales are purchases driven by ads that dynamically show products from your feed.

Understanding Catalog Sales

Catalog sales rely on a healthy product feed and clear templates that dynamically render product information like price, reviews, and availability. Product-level videos and review/price overlays typically raise CTR and CVR by adding motion and social proof without manual editing. Clean feeds with enriched attributes (sale_price, ratings, custom_labels) improve targeting relevance and creative quality. Segment your catalog using product sets to control which SKUs appear in prospecting versus retargeting, or to promote high-margin items during key periods.

Catalog sales work across platforms—Meta, TikTok, Pinterest, Snap, and CTV—giving you multi-surface reach from a single feed. Structure campaigns by objective (prospecting vs. retargeting) and product set (new arrivals, sale items, best sellers) to isolate learnings. Exclude low-performing SKUs automatically using rules or custom labels so budget flows to winners. Track performance by SKU and product category to inform inventory decisions, pricing strategy, and creative updates. Catalog sales turn your feed into a scalable growth engine when feed quality and creative clarity are strong.

Why Catalog Sales matter

Catalog sales matter because they let you cover your entire catalog without creating manual creatives for each SKU. They improve efficiency by showing the right product to the right person based on behavior and intent. Multi-platform reach ensures your products appear across Meta, TikTok, Pinterest, Snap, and CTV from one feed.

  • Scale: Cover your entire catalog without manual creatives.
  • Efficiency: Show the right SKU to the right person.
  • Resilience: Multi-platform reach (Meta, TikTok, Pinterest, Snap, CTV).

How Catalog Sales work

Catalog sales work by connecting your product feed to ad platforms that dynamically generate ads based on user behavior, product attributes, and your campaign settings. Platforms read the feed, apply product sets and audience rules, then render ads using templates that pull in SKU-specific data like title, price, image, and reviews. Retargeting shows products users viewed or added to cart; prospecting uses signals like category interest or lookalike modeling to find new customers. Creative templates ensure brand consistency while personalizing at the SKU level. Monitor performance by product set and exclude underperformers to keep spend efficient. Refresh your feed daily or faster to reflect price changes, stock-outs, and promotions in real time.

Key Takeaways

  • Catalog sales campaigns promote products dynamically from your feed, showing relevant items to each user.
  • Use enriched feeds, product sets, and templates to improve relevance and creative quality.
  • Catalog sales work for both prospecting and retargeting with product-specific personalization.
  • Track performance by SKU and product category to optimize inventory prioritization.
Related Terms
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FAQs
How do I attribute catalog sales?
Attribute catalog sales using platform-reported conversions, and run holdout tests where possible to gauge incrementality beyond last-click.
Do catalog sales cannibalize brand ads?
When structured cleanly with proper exclusions and segmentation, catalog sales complement brand ads by adding product-level relevance and intent.
What feed quality is needed for catalog sales?
Catalog sales require complete required fields (id, title, price, image, availability) and benefit from enriched optional fields like reviews, sale_price, and custom_labels.
Should I run catalog sales for prospecting or retargeting?
Run catalog sales for both—retargeting recaptures warm traffic with relevant SKUs; prospecting scales reach using interest and lookalike targeting.
How do I improve catalog sales performance?
Improve catalog sales by enriching your feed, building better templates, excluding low-performers, testing product-level video, and segmenting by product set.

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