Department of Marketing & Entrepreneurship

Advertising effects can have substantial heterogeneity, and identifying the moderating factors is important. We study how own and rival retail advertising effects depend on consumer-store spatial relationships and ad content (promotion vs. non-promotion ads). We integrate TV ad viewership data with new large-scale microdata on mobile locations, which track consumer traffic to home improvement stores and their home census block groups. We find that customers' relative proximity to own store compared to rival store moderates their ad effects. This moderator is more important than customers'''' absolute proximity and suggests fierce geo-competition. The ad effect heterogeneity comes from differences in both visit frequency and ad responsiveness. While non-promotion ads expand demand, promotion ads steal rival traffic, especially among customers in proximity to both stores. The results are primarily driven by non-professional customers and not contractors. Our findings have implications for retail advertising targeting strategy and the equilibrium impact of improved targeting technology.

We study the effectiveness of influencer marketing in the video game industry. We construct a novel dataset on video game streaming by continuously monitoring Twitch.tv, the largest gaming platform in the world, once every 10 minutes. The high-frequency nature of the data allows us to leverage plausibly exogenous variation in within-day streaming schedules to estimate the effect of stream viewership on video game usage. We find a modest and short-lived elasticity of 0.033 of primarily organic streams, and that sponsored content is only 25% as effective—an elasticity of 0.007. Finally, using generalized random forests to examine heterogeneous returns to streaming, we find that Twitch influencers primarily benefit new games, games from small publishers, and games with mixed user reviews. These results suggest that, whereas streaming does not unequivocally benefit all firms, this new, low-cost marketing channel does help promote products that would otherwise face significant information frictions.

While prior research strongly suggests that performance-based, variable compensation improves sales performance, several companies have recently reduced the amount of variable compensation because they blame it for causing myopic selling behavior. However, the effects of such incentive reductions are not well understood. Therefore, we examine an industrial wholesaler that reduced the share of variable compensation for its sales force in one sales division (from 80% to 20%) while keeping it unchanged in another division. We differentiate between effects of the incentive reduction on salespeople's performance quantity and quality. While quantity reflects salespeople's effectiveness in terms of sales output, quality reflects how well salespeople advise their customers. Using difference-in-differences models, we show that salespeople's performance quantity declined after the incentive reduction while performance quality increased. The strength of these effects depends on the prior performance in the two performance facets: reducing incentives especially harms the performance quantity of salespeople with high prior performance quantity, while performance quality increases particularly for salespeople with low prior performance quality. Thus, managers contemplating the reduction of variable compensation need to carefully balance the trade-off between performance quantity and performance quality, given their sales force’s current performance.

Users of access-based services for digital information goods such as Spotify and Netflix are confronted with seemingly unlimited choice with thousands of movies and millions of songs. To help users navigate, platform operators offer curated selections. On music streaming services, for example, thousands of playlists, covering different genres, artists, and moods are available. This paper studies how the inclusion of a song on curated playlists affects this song’s demand and how content owners (e.g., artists or labels) can strategically use these lists as a marketing tool. To this end, we collect information about the weekly curation of more than 60,000 playlists from a major streaming service which we relate to weekly streaming data for a sample of 54,000 songs over a period of 3 years, for a total of 7 million observations. Overall, we find a strong positive playlist effect. Our analysis suggests stronger effects for playlists with more followers, featuring similar content from various artists, and with context-based curation. Furthermore, songs by less established artists and older songs benefit more from playlists. These playlist effects are stronger than the effects of traditional advertising, highlighting the vital role of curation in settings with abundant choice.