Scaling Women Ethnic Brand
with ROAS Improvement
How Aza Fashions leveraged BIGATOM to automate 250,000+ SKUs and achieve a 27% ROAS uplift across Meta & Google.
“With BIGATOM, we finally had product-level visibility across our entire catalog. Automations like stop-loss helped us reduce wasted spend and scale confidently, both during BAU & high pressure sale periods.”
Gaurav Shapariya
CMO, Aza Fashion
Critical Scaling Obstacles
Aza Fashions faced four primary blockers preventing profitable growth across their 250k SKU catalog.
Zero Visibility
Managing 250k items manually led to zero clarity on product-level ROAS and Page Views.
40% Budget Drain
Over-spending on low-potential products due to lack of real-time performance data.
Scaling Efficiency Loss
In-ability to scale total spend without seeing a drastic drop in blended ROAS.
Traffic Pulling Blindspots
Non-visibility of “Assist Products” that drive traffic but trigger conversions elsewhere.
The BIGATOM Solution Stack
A specialized infrastructure built to solve multi-SKU luxury scaling.
1. Product Analytics
With a catalog of ~250K products, the brand required clarity on product-level insights and KPIs such as product-level ROAS, Ad Spends, Page Views, and Conversion Rates.
BIGATOM integrated Aza’s complete marketing ecosystem—including Meta, Google, Snapchat, and TikTok Ads, GA4, App Data, and Backend Inventory—to analyze performance at a product level to find exactly which items to promote, which to stop, and identify the most popular channel for every SKU.
Native Assisted Revenue Feature: Aza identified products contributing indirect revenue—where users land on Product X but ultimately purchase Product Y. This intelligence protected “traffic pullers” from being accidentally paused, maintaining high-quality site traffic volume.
2. Product Segmentation
Aza used BIGATOM to achieve strategic marketing goals like giving dedicated budgets to new inventory or high-margin collections.
Segmented products are automatically pushed to Google’s Product Groups and Meta’s Product Sets directly from the platform.
From High Potential Groups vs. General Product Sets
3. ROAS Stop-Loss Automation
Using BIGATOM’s Stop Loss Automation, Aza Fashions saved 19% of their ad budget by automatically pausing products that didn’t meet performance standards.
Exclusion rules were set at different categories & sub-categories, removing items that hit a performance plateau or failed after reaching a target spend limit.
Platform-Specific Exclusion: Products performing well on Meta but poorly on Google were removed only from the underperforming platform.
Auto-Inclusion: Products auto-resume promotion based on signals like improved conversion rate or organic order count.
Monthly ad spends saved via automation as budget is recaptured from product-level non-performers.