Auctions have become the standard way of allocating resources in electronic markets. Two main reasons why designing auctions is hard are the need to cope with strategic behavior of the agents, who will constantly adjust their bids seeking more items at lower prices, and the fact that the environment is highly dynamic and uncertain. Many market designs which became de-facto industrial standards allow strategic manipulation by the agents, but nevertheless display good behavior in practice. In this thesis, we analyze why such designs turned out to be so successful despite strategic behavior and environment uncertainty. Our goal is to learn from this analysis and to use the lessons learned to design new auction mechanisms, as well as fine-tune the existing ones. We illustrate this research line through the analysis and design of Ad Auctions mechanisms. We do so by studying the equilibrium behavior of a game induced by Ad Auctions, and show that all equilibria have good welfare and revenue properties. Next, we present new Ad Auction designs that take into account richer features such as budgets, multiple keywords, heterogeneous slots and online supply.