Personalisation Engine for a Leading Online Grocer
The online grocer delivers to residences and offices in the New York City metropolitan area. They custom-package groceries and meals for its customers and are popular for their distribution of organic food and locally grown items, as well as items that consumers see in supermarkets daily.
- The current system relied on simple rules and algorithms to drive recommendations
- Used only basic customer and product attributes and transaction history
- Limited manual override capabilities
- Limited business scenario support.
- Limited real-time personalization capabilities
Improving customer experience with hyper-personalization across all channels – StoreFront, Mobile, Customer Support with a recommendation engine for a leading online grocer
- Advanced Machine Learning & Neural Networks to drive product ranking and personalization
- Personalization cockpit to support manual inputs and overrides
- Utilize much broader customer and product attribute sets like Geographic, Demographic, Life Events, Weather, Browsing history to drive recommendations
- Support for real-time inferences and personalization across channels.