Case Studies and Solutions


Recommendations are algorithmic suggestions made by Machine Learning models that automatically showcase relevant products for customers to buy. Through targeted recommendations, one can greatly increase user engagement and conversion

Potential Applications: User Engagement, Ad Revenue


Since every user has a different set of likes and dislikes, Personalization helps you keep your audience engaged and involved with your content. On e-Commerce websites, personalization can be used in targeted messaging, ad targeting, and product placement

Potential Applications: Ad targeting, User Engagement, Targeted Messaging

Price-Point Optimization

Price point optimization uses machine learning models to determine how customers will respond to different prices of a product or services through different channels. It aims to maximize profitability by using market and consumer data to find a balance between value and profit.

Potential Applications: Retail, e-Commerce, Airlines, Hospitality, Insurance

Inventory Optimization

Inventory optimization uses machine learning models to determine the right amount of inventory required to meet forecasted demand, and keep logistics and storage costs low, while avoiding stockouts. The aim is to reduce the storage, maintenance, and leftover costs, while ensuring customer satisfaction is not impacted.

Potential Applications: Supply Chain, Logistics, Lean Manufacturing