Brand Background
House of India (HOI) is a leading retail brand with 26 stores across India and a strong international e-commerce presence, offering a fusion of ethnic and modern styles. It delivers a range of thoughtfully designed collections that combine heritage craftsmanship with contemporary fashion.
Challenges
1. Inefficient Ad Spend on Low-Converting Products
High-budget SKUs were consuming a significant portion of the ad spend but failed to generate proportional revenue, leading to inefficient budget utilization.
2. Lack of Smart Product Targeting
Ads were promoting random products instead of focusing on proven best-sellers or high-potential items—diluting overall campaign performance.
3.Missed Opportunities with New Arrivals
New collections, which delivered higher ROAS and better margins, weren’t being prioritized dynamically in campaigns, resulting in missed revenue opportunities.
4. Learning Phase Disruptions
Frequent manual SKU updates forced Meta and Google Ads back into the learning phase repeatedly, stalling performance and reducing optimization effectiveness.
Solutions
1. Eliminating Ad Spend Waste with Automated Stop-Loss Controls
BigAtom implemented automated ROAS and spend-based rules to pause underperforming SKUs daily. This ensured budgets were redirected toward high-performing products, resulting in a 30% reduction in wasted ad spend and improved overall profitability.
2. Smarter Targeting Through Dynamic Product Sets
Using New Arrivals Segmentation, BigAtom dynamically identified and prioritized fresh SKUs based on real-time product age. This allowed HOI’s most relevant and high-converting products to be consistently featured in ads—boosting ROAS and accelerating scale.
3. Scaling Efficiently Without Disrupting the Learning Phase
BigAtom’s Quadrant Analysis powered auto-refreshing product sets that continuously showcased top performers without resetting the ad platform’s learning. This strategic automation reduced Learning Phase disruption from 70% to just 30%, significantly enhancing campaign stability and efficiency.
Key Results
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