Customers often buy single items without knowing what matches, reducing cart value and slowing decision-making.
solution
Our Solution
We built an AI recommendation engine that suggests décor bundles (sofa + cushions + coffee table) or matching sets (curtains + rugs + lighting) based on design themes and past preferences.
Tools we used
Approach
Step-by-Step Workflow
Step 1
Analyze product browsing and purchase history.
Step 2
Identify design themes (modern, rustic, minimal).
Step 3
Recommend complementary products in real-time.
Step 4
Present as “Styled Looks” or “Frequently Bought Together” bundles.
Quantifiable Benefits
Increase in average order value
%
Higher cross-sell revenue
0%
Faster decision-making by customers
%
Stronger brand differentiation with curated shopping
0%
Who’s Using This
Wayfair, West Elm, Urban Ladder
D2C home decor startups
Furniture eCommerce marketplaces
Why It Matters
AI bundles not only boost revenue but also inspire customers, making shopping for an entire look as easy as buying one item.
case studies
Real Results. Real Impact.
See how these use cases helped industry leaders transform operations with AI & XR.