Choosing the correct optimization objective is key to the success of a search engine. Unlike traditional web searches, where clicks are clearly the main objective to optimize, many emerging search engines like product search may require a different goal to achieve, such as more conversions, revenue, and higher quality. Selection of a good metric may depend on many factors such as query type (transactional vs. navigational vs. informational), and goal of a business (profitability vs. growth). For example, a typical product search engine may focus on maximizing the number of transactions and total revenue, while navigational search may aim at minimizing the total number of clicks. In this talk, we will investigate factors needed to be considered when we design objective functions of a product search engine, and we will also walk through a case study based on a particular business, including how an objective can be selected, mathematically defined, and optimized with a machine learning framework.
Liang Wu, PhD
Machine Learning Data Scientist | Airbnb