  Negotiation is a complex activity involving strategic reasoning, persuasion,
and psychology. An average person is often far from an expert in negotiation.
Our goal is to assist humans to become better negotiators through a
machine-in-the-loop approach that combines machine's advantage at data-driven
decision-making and human's language generation ability. We consider a
bargaining scenario where a seller and a buyer negotiate the price of an item
for sale through a text-based dialog. Our negotiation coach monitors messages
between them and recommends tactics in real time to the seller to get a better
deal (e.g., "reject the proposal and propose a price", "talk about your
personal experience with the product"). The best strategy and tactics largely
depend on the context (e.g., the current price, the buyer's attitude).
Therefore, we first identify a set of negotiation tactics, then learn to
predict the best strategy and tactics in a given dialog context from a set of
human-human bargaining dialogs. Evaluation on human-human dialogs shows that
our coach increases the profits of the seller by almost 60%.
