Design of a Bundle Shopbot

The increasing proliferation of online shopping and purchasing has naturally led to a growth in the popularity of comparison-shopping search engines, popularly known as “shopbots”. We extend the one-product-at-a-time search approach used in current shopbot implementations to consider purchasing plans for a bundle of items. Our approach leverages bundle-based pricing and promotional deals offered by online merchants to extract substantial savings. The problem of choosing the cheapest cost to purchase a bundle of items is modeled as a set covering problem and is shown to be NP-Hard. Interestingly, our approach can also identify “freebies ” that consumers can obtain at no extra cost. We develop heuristic approaches that can be employed when the number of items is large or when the real-time nature of shopbot applications dictates quick response rates to consumer queries. A detailed illustration with real-world data from major retailers suggests that optimal solutions to the proposed models can result in significant savings for bundle purchasing consumers, and frequently identify freebies for consumers. The heuristic approach also performs extremely well and is thus practical for shopbot implementation. Design of a Bundle Shopbot