What Can Television Networks Learn from Search Engines? How to Select, Price and Order Ads to Maximize Advertiser Welfare

Abstract:     
Television advertising revenues are falling after years of growth, due in part to digital video recorder proliferation. We consider the television network’s problem of how to optimally select, price, and order advertisements in order to maximize audience value. We propose that television networks should shift from managing and selling time to managing and selling viewer attention, in order to eliminate negative externalities among advertisers within a break. We show there is no optimal advertisement ordering heuristic when the viewing audience contains multiple segments. We propose the Audience Value Maximization Algorithm (AVMA), a computationally feasible second-best solution that considers many possible advertisement orderings within a dynamic programming framework. AVMA can be extended to accommodate advance selling, audience bundling, and branded entertainment.

Keywords: Television, Advertising, Marketing, Algorithms, Auctions

Working Paper Series