Data scientists may consider themselves fish out of water when it comes to applying game-theoretic approaches to customer engagement. Nevertheless, it provides a valuable set of approaches for behavioral analytics.
>Customer engagement is a bit of a game, because, deep down, it’s a form of haggling and bargaining. Let’s be blunt: everybody has an ulterior purpose and is manipulating the other party in that direction. The customer is trying to get the best deal from you, and you’re trying to hold onto them and sell them more stuff at a healthy profit.
Customer engagement is not solitaire, and, unlike many online games, it always has very real stakes. By its very nature, customer engagement is an interactive decision process involving individuals and organizations, entailing varying degrees of cooperation and conflict in the course (hopefully) of a stable and mutually beneficial outcome.
Game theory is a modeling discipline that focuses on strategic decision-making scenarios. It leverages a substantial body of applied mathematics and has been used successfully in many disciplines, including economics, politics, management and biology. There has even been some recent discussion of its possible application in modeling customer-engagement scenarios to improve loyalty, upsell and the like.
Customer engagement modeling is a largely unexplored frontier for game theory. The literature on this is relatively sparse right now, compared to other domains where game theory’s principles have been applied. […]<
See on www.ibmbigdatahub.com