Swiggy Uses 350+ Features and Multi-Task MLP to Predict Customer Lifetime Value

InfoQ (AI, ML & Data)
Read full post
Swiggy developed an in-house predicted lifetime value (pLTV) model using over 350 features and a multi-task multilayer perceptron to estimate new customers' long-term value before their first order. This model helps optimize advertising bids by predicting customer value despite sparse early data and skewed order distributions.

More in Machine Learning

Machine Learning3 min read

Nvidia and Palantir fine-tune a 30B Nemotron model for Nvidia’s supply chain. It beats a model 18 times its size.

Covered by 3 sources
Machine Learning6 min read

CoreWeave Puts Field Engineers Inside Customer Teams for Physical AI

Covered by 2 sources
Machine Learning2 min read

Weatherwatch: AI model beats standard methods at predicting cyclones

The Guardian