AI-Driven Retail Engine
Driving 3x growth in customer checkouts using hyper-personalization, predictive recommendations, and intelligent checkout paths.
The Challenge
An international retail brand suffered from low digital sales conversion rates and high cart abandonment. Traditional rules-based recommendation engines failed to deliver contextual, personalised suggestions to diverse customer demographics — resulting in generic experiences that didn't drive purchase intent.
Our Solution
We built and integrated an AI-powered predictive recommendation engine using TensorFlow. The system analyses user search intent, purchase history, and real-time browsing behaviour to serve hyper-personalised product listings. Automated checkout discount prompts were triggered at key abandonment moments to recover at-risk transactions.
The Results
Customer checkouts increased by 3x within four months of going live. Cart abandonment dropped by 35%, and Average Order Value (AOV) saw a substantial boost across all digital channels — delivering measurable ROI within the first quarter of deployment.
Stack & Expertise
“We'd been stuck in a conversion plateau for nearly two years. Cyberbeak's AI personalisation engine broke that ceiling completely — checkouts tripled and cart abandonment dropped 35% in the first quarter. The ROI paid for the entire project within six weeks of launch.”