Online Markets and Auctions

Over the last decade we witnessed the emergence of online e-commerce and content platforms that fundamentally disrupted traditional industry verticals. These platforms not only it easier for producers to reach a large-scale audience, but they also dramatically reduced the cost of entry for market participants. This led to a “democratization’ of the market that allowed small producers to reach the same audience that typically was only reachable by large, established producers. Examples of online e-commerce platforms are “app” stores such as iTunes and Google Play, online book stores such as Amazon Books and Kobo Writing Life; examples of online content platforms are SoundCloud (for music), YouTube (for videos) and Twitter (for news updates). This transformation created tremendous opportunities for smaller producers; in particular producers that focus on serving a particular niche market. Because of this, the number of producers, as well as the number and variety of available goods, has dramatically increased on these e-commerce and content platforms. However, this increased size and breadth of the market also made it more challenging for producers to identify the consumers that are potentially interested in their goods, as well as for consumers to find the goods that they are interested in. This problem is particular challenging for producers that newly enter an online e-commerce or content platform as they have very little information available about consumers who are potentially interested in their goods, and how they should price their goods.

The goal of this research is to overcome these challenges by developing advanced data analytics to efficiently connect producers and consumers in online markets, as well as advanced decision tools to help producers with product placement and pricing. Although online marketplaces collect large amounts of data about producers as well as consumers, there is currently very little research that aims to make this data actionable for producers. Creating such a system will have a tremendous impact, and fundamentally transform existing online e-commerce and content platforms. To achieve this, the data analytics and decision tools have to be easy to use and understand, and automate most of the decision process by requiring only very limited input and manual configurations from its users.

Creating such tools has the potential to fundamentally transform how producers engage in online markets, and lead to a major breakthrough in making online markets more efficient and easier to use for producers.