Conversion increased by 19% and average order value rose 14% through real-time recommendations.
A multi-brand retailer had strong traffic but weak conversion. Product discovery was generic, recommendations were rule-based, and campaign targeting had low relevance across user segments.
We implemented a machine-learning personalization engine that scores products in real time based on behavior, intent, and inventory context. The engine powers home feed ranking, cart upsell, and campaign segmentation.
Overall conversion rate increased by 19%
Average order value increased by 14%
Email campaign click-through rate improved by 27%
Recommendation API latency kept under 120ms
“Our storefront finally feels intelligent. The personalization rollout paid for itself within the first quarter.”
VP of Growth
Retail Group
