How ASC Consolidation Scaled a Large Product Catalog

Challenges

The client was old school and understandably cautious. Their preference was to run bespoke static ads featuring specific products, prices and URLs, updated weekly or fortnightly to match EDMs and organic social.
They were initially untrusting of the BAU ASC catalog strategy. The concern was that Meta would show a random spread of products from a huge catalog, rather than the specific items the business wanted pushed. At one point, it looked like the ASC strategy may be rejected entirely, which would have locked the account into constant weekly static ad refreshes.

Strategy & Execution

We did not simply hand Meta the full product feed and hope for the best. We used the client questionnaire, onboarding notes and product priorities to identify which products were likely to create the strongest commercial value.

• The client prioritised cookware, knives, dinnerware, glassware and higher-value product sets.
• They specifically believed sets were stronger than individual low-value items.
• We therefore built custom Commerce Manager product sets using category, price, brand, product type and stock filters.

Key Product Buckets Built

• Cookware + Knives: Scanpan, Global, Chasseur, cookware sets, knife blocks, knife sets, pots and pans.
• Tableware + Glassware: dinnerware sets, drinkware, serving sets and entertaining pieces above higher price thresholds.
• High Ticket / High RRP Markdown: premium items with strong perceived value and large price gaps.
• Daily Deals / Promo Products: products aligned to weekly or fortnightly promotional pushes.

The Side-By-Side Test

To get buy-in, we agreed to test both approaches side by side rather than force the ASC strategy through. This gave the client the control they wanted while allowing us to prove whether the algorithm-led structure could compete.

• Manual static product campaign: bespoke product graphics, closer to EDM and organic social style.
• BAU ASC catalog campaign: custom product sets, algorithm-led delivery and dynamic product matching.
• Retargeting: layered in to recover add-to-cart and checkout users, then later paused as the ASC consolidation performed more efficiently.

After roughly one month, both the static product campaign and ASC were performing strongly at around 11x to 12x ROAS. The static campaign proved the client’s promo-led approach could work. However, the ASC campaign produced comparable performance with far greater scale and less manual work.

The Budget Pivot

Once we had enough data, we made the key decision to move budget away from the manual TOF/products campaign and retargeting activity, then concentrate more spend into the BAU ASC catalog campaign.

This paid off. The ASC campaign continued to improve as Meta received more conversion signals. After the pivot, ROAS climbed and has held strongly, with current performance sitting comfortably around 16.5x+.

Why It Worked

• Fewer overlapping campaigns gave Meta cleaner signals.
• Budget concentration allowed the best-performing campaign to learn faster.
• The curated product buckets kept Meta focused on commercially valuable products.
• Stopping retargeting reduced audience saturation and appears to have improved overall efficiency.
• The market seemed sensitive to being overloaded with too many ads, suggesting there is a delivery sweet spot for this client.
  
  

Key Results

All-Time Campaign Results
All-time Meta results from the campaign export show the ASC catalog campaign as the clear scalable winner.

• 14.20x blended ROAS across the account
• 15.29x ROAS on the BAU ASC catalog campaign
• 12.12x ROAS on the static product / TOF promo campaign
• 10.23x ROAS on the retargeting catalog test
• 8.98x ROAS on full-catalog retargeting
• 8,301 total purchases delivered across all campaigns

Key Learning: Trust The Algorithm, But Control The Inputs

The client’s concern was that ASC would behave like a random catalog campaign. The result showed the opposite. Once the product feed was structured into meaningful buckets, Meta was able to find the right buyers and deliver the right products at the right time.

The manual static campaign had strong creative control, but the ASC campaign had stronger scalability. It did not need new individual ads, URLs and graphics every week to keep performing.

The stronger outcome came from combining human strategy with algorithmic delivery: we chose the right product universe, then let Meta optimise within it.

Retargeting Learning

Retargeting was profitable, but it did not outperform the core ASC campaign. When retargeting was paused and budget was concentrated into ASC, overall ROAS increased again. This suggests the audience may have been sensitive to being hit by too many overlapping ads.

For Victoria’s Basement, there appears to be a sweet spot in delivery. More campaigns and more retargeting pressure did not automatically mean better performance. A cleaner structure with more budget concentrated into the strongest campaign performed better.

Conclusion

Victoria’s Basement started with a large catalog and a client who was sceptical of algorithm-led catalog advertising. The account could easily have become a high-touch weekly static ad build. Instead, we structured the feed, tested the client’s preferred approach against ASC, then made the call to concentrate budget into the winner.
The decision to move budget into the BAU ASC catalog campaign paid off. Performance improved after consolidation, retargeting proved less necessary than expected, and the ASC campaign continued climbing from around 12x ROAS after one month to roughly 16.5x+ in current views.
The clear lesson is that Meta’s algorithm can be highly effective for large ecommerce catalogs when the product feed is properly structured. The right move was not to avoid automation, but to guide it with the right product buckets and then give it enough budget to work.