Improving web-catalog design for easy product search
Building intuitive web sites is important for online businesses as positive experiences toward the virtual storefront could translate to customer goodwill and repeat visits. Streamlining web-site navigation is further motivated by the availability of comprehensive site-visit traces such as shopping carts and click-stream logs. We incorporate such sales and browsing patterns for the autonomous design of web catalogs by reducing the expected click count it takes to find related items. We first model catalog design as a task of placing items onto catalog pages, leading to a quadratic assignment formulation. For a more extensive redesign, such as when the number and location of links on each page are also decision variables, we propose a two-stage optimization procedure to ensure that click-count reduction is not achieved at the cost of excessive page cluttering. Our analysis reveals that an optimized catalog is robust against shifts in browsing behavior and that simplistic interfaces are preferred for users at either end of the experience spectrum. Using genetic algorithms, we find catalog designs that significantly outperform those found with a traditional greedy heuristic.
catalog design genetic algorithms network design quadratic assignment problem electronic commerce