How Pepe Jeans Scaled
Catalog Ads Profitably with BigAtom
Improving ROAS, reducing CAC, and growing catalog ads contribution with product-level intelligence and automation across Meta and Google.
Scaling catalog ads without losing efficiency
Pepe Jeans had strong demand but needed better control over product-level performance, inventory gaps, creative fatigue, and wasted spend to scale profitably.
Pepe Jeans is a globally recognised fashion and denim brand with a large product catalog spanning multiple categories.
While the brand had strong demand, scaling further required moving from campaign-level optimisation to a product-led performance system — making decisions at the SKU level to identify which products to scale, pause, refresh, or deprioritise.
High Dependence on Discount-Led Revenue
A significant share of revenue was driven by offers and discounts, making profitable scale harder to sustain over time.
Low Catalog Ads Contribution
Catalog ads contributed only ~20% of total revenue, leaving strong room for growth through smarter product targeting.
Wasted Spend on Poor Performers
Without automated product-level controls, inefficient SKUs continued consuming budget without delivering proportional returns.
Creative Fatigue at Scale
With a large product catalog, ad creatives became repetitive quickly, impacting engagement and campaign performance.
Product Performance Management
BigAtom moved Pepe Jeans from campaign-level optimisation to SKU-level decision-making — segmenting the catalog into four clear groups, each with a distinct performance strategy.
High Potential Products
Emerging categories like footwear and high-potential SKUs with strong conversion signals but insufficient budget to reach their ceiling.
Hero Products
Best-selling SKUs ready to scale — proven top performers protected from budget dilution and prioritised for dedicated campaigns.
Sale-Driven Products
Discount and promotion-led products needing visibility. Managed carefully to reduce discount dependency and protect margin.
Non-Performers
Low-performing products consuming budget without returns. Targeted for automated Stop-Loss pausing and inventory-based exclusion.
Five targeted strategies
SKU-level intelligence and automation across Meta and Google turned the segmentation framework into measurable, compounding performance gains.
Built SKU-Level Performance Visibility
BigAtom integrated data across Meta Ads, Google Ads, GA4, app analytics, and Shopify — creating a single unified product-performance view to identify which SKUs were ready to scale.
Automated Stop-Loss for Poor Performers
BigAtom’s Stop-Loss Automation removed inefficient products from catalog campaigns once they dropped below defined performance thresholds — cutting wasted spend and redirecting budget toward stronger SKUs.
Used Inventory-Based Automation
BigAtom connected with backend inventory data to ensure products with broken sizes or stock issues were not promoted — avoiding spend on unpurchasable products and improving both media efficiency and customer experience.
Solved Creative Fatigue with Automation
BigAtom enabled creative automation at scale — generating new creative variations, refreshing product visuals, and reducing repetitive ad experiences across large product sets to keep catalog ads fresh and engaging.
Improved Product Segmentation
Pepe Jeans’ catalog was segmented by performance, category, margin, and business priority — from best-sellers to emerging categories like footwear — reducing dependence on a few categories and building a more balanced revenue mix.
Product-led performance metrics
Moving to SKU-level decisions delivered measurable gains across ROAS, CAC, CTR, and catalog revenue contribution.
