When personalization became the missing link
An online arm of a global fashion and grocery brand had a clear vision: convert more walk-ins into repeat digital buyers.
But there was a challenge. Their e-commerce platform lacked smart personalization.
The offers felt static. Discovery was hit-or-miss. Most importantly, users weren’t finding what they truly wanted.
To boost conversions and engagement, they needed a better way to serve personalized recommendations at scale.
Turning insights into action
Netscribes built a robust deep learning recommender system designed to serve relevant, timely product suggestions.
Using learning to rank models, the system learned from every customer click, view, and transaction.
We trained it using TensorFlow and Keras on AWS EC2.
Then deployed it live using REST APIs across both mobile and web.
It pulled metadata, purchase history, and browsing data to personalize every interaction.
The result? Personalized recommendations that felt intuitive and timely, because they were.
Real impact. Real returns.
Within weeks, the retailer saw results:
- 3% revenue uplift, driven by better engagement and bigger carts
- Seamless backend integration across the AWS stack
- Real-time recommendations fine-tuned to individual behaviors
- A scalable system built to grow with the business
And most importantly, customers stayed longer and bought more.
Why it worked
This was not just a plug-and-play solution.
The deep learning recommender system was built to evolve with user behavior.
Personalized recommendations were no longer based on broad segments—they were tailored, one-to-one.
By applying learning to rank algorithms, the model continuously improved itself with each interaction.
The shopping journey became smarter, faster, and far more relevant.
Reinvent your e-commerce experience
Want to move past basic suggestions? Let personalized recommendations drive your next growth curve.
Whether you’re scaling digital channels or optimizing conversions, we help you make each click count. Transform with our data analytics solutions.
Download the full case study to see how ML-powered personalization turned insight into revenue.
