Abstract
Managers and researchers alike suspect that the vast amounts of qualitative information in blogs, reviews, news stories, and experts’ advice influence consumer behavior. But, does qualitative information impact or rather reflect consumer choices? We argue that because message content and consumer choice are endogenous, non-random selection and conflation of awareness and persuasion complicate causal estimation of the impact of message content on outcomes. We apply Latent Dirichlet Allocation to characterize the topics of transcribed content from 2,397 stock recommendations provided by Jim Cramer on his show Mad Money. We demonstrate that selection bias and audience prior awareness create measurable biases in estimates of the impact of content on stock prices. Comparing recommendation content to prior news, we show that he is less persuasive when he uses more novel arguments. The technique we develop can be applied in a variety of settings where marketers can present different messages depending on what subjects know.
Recommended Citation
Aral, Sinan; Ipeirotis, Panos; and Taylor, Sean, "Content and Context: Identifying the Impact of Qualitative Information on Consumer Choice" (2011). ICIS 2011 Proceedings. 9.
https://aisel.aisnet.org/icis2011/proceedings/economicvalueIS/9
Content and Context: Identifying the Impact of Qualitative Information on Consumer Choice
Managers and researchers alike suspect that the vast amounts of qualitative information in blogs, reviews, news stories, and experts’ advice influence consumer behavior. But, does qualitative information impact or rather reflect consumer choices? We argue that because message content and consumer choice are endogenous, non-random selection and conflation of awareness and persuasion complicate causal estimation of the impact of message content on outcomes. We apply Latent Dirichlet Allocation to characterize the topics of transcribed content from 2,397 stock recommendations provided by Jim Cramer on his show Mad Money. We demonstrate that selection bias and audience prior awareness create measurable biases in estimates of the impact of content on stock prices. Comparing recommendation content to prior news, we show that he is less persuasive when he uses more novel arguments. The technique we develop can be applied in a variety of settings where marketers can present different messages depending on what subjects know.