Welcome to my Thinking World…

Abstract:

U.S. consumers are adding time to their media day and making time to connect with their favorite content, no matter where it exists (Nielsen 2014). But how they’re consuming media is ever-changing thanks to the continued proliferation of technological devices, 24/7 availability of the media content, ease-of-access, and economics. Whether streaming or satellite, over-the-air or over-the-top, understanding how consumers are consuming media is more important than ever, particularly for companies providing these services since advertising is their major source of revenue. For researchers, this consumption ecosystem has given rise to big datasets consisting of millions and millions of viewing records to mine thru in order to discover trends, viewing patterns, and relationships. In this study, we are attempting to do just that. Read more

Abstract:

The media industry is in a state of flux with continued fragmentation of consumer time and attention around media and across various devices and services. One such service that is popular among consumers today is SVOD (Subscription Video On-Demand) which enables on-demand access to both native digital content and TV-produced content. Forty eight percent of US homes have access to at least one SVOD service from providers such as Netflix, Amazon Prime and Hulu, up from 42% a year ago, according to Nielsen’s report. As consumers are shifting from live viewing to SVOD consumption, researchers are interested in understanding the underlying behavioral changes that are differentiating SVOD service providers. For instance, are consumers watch similar programs between Netflix and Hulu? Are there overlaps and/or uniqueness in consumer behaviors across these service providers? Answering these and many other questions is at the heart of this study and analysis. Read more

Abstract:

The Nielsen Company, like most other market research firms, is concerned with falling response rates and the threat of nonresponse bias. The challenge in understanding and adjusting for nonresponse is always the lack of information about the non-responding cases. In recent years, researchers have considered the use of paradata, interviewer observations, and aggregate Census information to provide information about the non-responders. This study introduces and evaluates the use of a new type of GIS-based data, called POI (Points-of-Interest), as a potential auxiliary data source for nonresponse bias analysis. Read more

Abstract:

In some surveys, respondents are confronted with selecting a response from an extremely long list of response options. For example, in the National Survey of College Graduates (NSCG) mail survey, respondents are asked to select the job code that best describes their work from a long list of job codes (listed on a different page) that are categorized and arranged alphabetically to facilitate easy selection. While various aspects of the findings from this survey have been published, for instance, the effect of previously sent token incentives on subsequent contact rates (see Dillman (2007), page 241), little is known about the measurement error aspect of using extremely long response lists. Read more