Internet Application Development

← Back to Dashboard

Problem Statement

Problem 1) Refer to Lab 1 (Problem 2), you have to incorporate business intelligence in your PVFC order processing system by adding a recommendation system.

Recommendation System

A recommendation system for an order processing system analyzes historical order data, user behavior, and item characteristics to predict and suggest products that a customer is likely to purchase next.

These systems:

• (i) Improve customer experience
• (ii) Increase Average Order Value (AOV) by identifying purchasing patterns and offering personalized recommendations.

Recommendation Techniques

• Collaborative Filtering (CF): Recommends items based on similar user behavior. If user A and B have similar order histories, the system suggests items purchased by B to user A.
• Content-Based Filtering: Suggests items similar to those a user has already purchased or viewed, based on item attributes (e.g., category, brand, or price).
• Hybrid Systems: Combines collaborative and content-based filtering to overcome limitations like the "cold start" problem (new users/items with no history).
• Association Rule Mining: Identifies items frequently bought together, ideal for "frequently bought together" bundles or upselling complementary items.

Assumption: Sufficient numbers of orders are present in database.

Functionalities to be added

1. Display recommendation messages during Product Selection and Order Placement: "Customers who bought this also bought..."
2. Reordering suggestions for customers.
3. For employees/managers of PVFC: forecasting demand for secondary items when a primary item's sales increase. (Inventory Management)

← Back to Dashboard