How Sephora Improved ROAS While
Scaling Beauty Commerce Across Meta & Google
Powered by BigAtom’s product-level intelligence, targeted Product Sets, and Stop-Loss Automation across a 300+ brand beauty catalog.
Scaling beauty commerce with a 300+ brand catalog
Sephora needed deeper product, brand, and category-level visibility to bring Meta and Google performance in India closer to other geographies.
Sephora is a global leader in prestige beauty retail — operating across skincare, makeup, haircare, fragrances, and 300+ curated brands in India through a robust e-commerce platform and physical stores.
With both online and offline presence, the brand needed a more connected approach to performance marketing — moving from manual, siloed reporting to a product-led system built for scale across Meta and Google.
Limited Product, Brand & Category Insights
Performance data was spread across Meta Commerce Manager, Google Merchant Center, and e-commerce systems — making it difficult to track product-level KPIs efficiently.
Limited Control Over Spend by Category
As a beauty marketplace with multiple brands and categories, Sephora needed better control over which brands, categories, and products received ad visibility.
Ad Spend Leakage on Poor Performers
Around 25% of ad spend across Meta and Google was being wasted on poor-performing products, reducing efficiency and limiting scale.
Product Performance Management
BigAtom segmented Sephora’s 300+ brand catalog into four performance-based groups — enabling sharper ad spend decisions at the product, brand, and category level.
High Potential Products
Profitable brands and SKUs receiving insufficient visibility — emerging categories and trending beauty products with strong conversion signals but underleveraged budgets.
Hero Products
Top-performing SKUs across skincare, makeup, and fragrance — proven bestsellers prioritised for dedicated Product Sets generating 13× ROAS.
Low Discoverability
Brands and products with limited exposure needing controlled testing before confident budget allocation across Meta and Google campaigns.
Non-Performers
SKUs consuming 25% of budget without returns — automatically excluded via Stop-Loss Automation, freeing spend for profitable brands and products.
Three targeted strategies
Product-level analytics, targeted Product Sets, and automated stop-loss rules combined to build a scalable performance engine for Sephora’s beauty catalog.
Built Product-Level Performance Visibility
BigAtom’s Product Analytics gave Sephora a 360° view of performance across ad spend, conversion rate, ROI, and revenue — helping the team identify which products were ready to scale and which to deprioritise.
Created Targeted Product Sets
BigAtom built Product Sets focused on truly profitable SKUs and brands — including Anastasia, Makeup Forever, and Huda Beauty — promoted across Meta and Google with strict performance filters generating 13× ROAS from April to June 2024.
Automated Stop-Loss for Non-Performing Products
BigAtom enabled Stop-Loss Automation across Meta and Google catalog ads — automatically excluding non-performing products based on defined rules, so budget was never wasted on SKUs failing to deliver returns.
Product-led performance metrics
Shifting to product-level precision delivered compounding gains across revenue, orders, ROAS, and ad spend efficiency.
