Incentivized Social Sharing: Characteristics and Optimization

Abstract

Many modern digital platforms provide features for social sharing, thus increasing the reach of their products and services through person-to-person recommendations. Meanwhile, the question how monetary incentives for social sharing affect the behavior of users remains largely unexplored. The effectiveness of incentives is often hard to optimize due to the large space of incentive parameters and the inherent tradeoff between the incentive attractiveness for the customer and the return on investment for the company. Here, we present a case study in which we show how incentives can change the structural properties of social networks and shift the power-law curve of sharing. We distinguish between altruistic and incentivized shares, and we look at the impact of different incentive amounts on the sharing behavior of users. We propose a novel graph evolution model, Me+N model, which provides flexibility in exploring the effect of different incentive parameters on company’s profits by capturing the probabilistic nature of customer behavior over time. We look at a specific family of incentives in which customers get a reward if they convince a minimum, pre-specified number of friends to purchase a given product. Our analysis shows that simple monetary incentives can be surprisingly effective in social media strategies.