Posts Tagged ‘ MAPOR

Media Viewership in the Connected World: A Big Data Case Study

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

A Panel Examination of Over-the-Top Audience

Abstract:

The new reality for consumers is they not only have access to more content than ever before, but they can also select the content they want, when they want, and watch in the device they want. One such device that has become increasingly popular for media consumption is Over-the-Top (OTT) media players. These are devices that deliver video content via the internet to television sets. Today, there exists an ever-growing number of various OTT devices from Roku players, the Apple TV, the Amazon Fire TV box, Chromecast, and game consoles. However, with this increased availability of choice comes the growing fragmentation of consumer time and attention. This leaves advertisers with the complex task of breaking through the clutter of advertisements and finding a way to reach the OTT device-specific audience. However, reaching an audience behind an OTT device requires a thorough understanding of the viewers. To date, there has been no study examining the differences between various types of OTT device owners and their viewing behaviors. Read more

Who’s on Netflix vs. Hulu vs. Other? A Panel based examination of SVOD users

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

David vs. Goliath? Is Over-The-Top Challenging Traditional TV? A Case Study

Abstract:

Over the past few years, we have witnessed an expanding range of viewing devices and new content offerings by online streaming services (such as Netflix, Amazon and Hulu) through over-the-top (OTT) devices. Nearly 20% of U.S. households own at least one OTT device, such as a Roku, Amazon Fire TV, or Apple TV (Park Associates 2015). As these trends keep increasing, there have been debates on whether online streaming will replace traditional (or cable) TV in near future. Furthermore, questions have been raised around whether OTT viewing, via Apps, is cannibalizing or complementing network oriented TV viewing. Does multiple layers of ownership/access (ex: device, App, etc.) in OTT viewing play a role in their viewing/usage behavior to be different from traditional TV viewing? Does these two forms of TV viewership different in terms of types of programs watched, when they are watched, and how often they are watched? These are all questions of great importance to online publishers and advertisers, and, in general, to researchers working with large volume and variety of TV viewing data. Answering these questions is at the heart of this study and analysis. Read more

The Use of GIS Information as Auxiliary Data for Nonresponse Bias Analysis

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

Humanizing the Internet Cookie? Key Learnings from an Online Panel

Abstract:

The Online advertising is booming. Companies are increasingly relying on Internet cookies to target online ads to consumers and track ad exposure and website click-through rates. Cookies are also used for survey targeting of specific Internet user groups, for measuring ad effectiveness, and for political polling. Companies use the cookies they have dropped as proxies for the consumers they are ultimately trying to reach. However, this approach of humanizing cookies suffers from several measurement errors, due to cookie deletion, blocking cookies, multiple people in the household using the same browser, or one person using multiple browsers. Read more

Catch Them When You Can: Speeders and Their Role in Online Data Quality

Abstract:

The role of panelist engagement on survey data quality in online panels has been a subject of discussion and commendation by industry and academic leaders (see Baker et. al. 2010). While there are many indicators of data quality in online surveys such as item nonresponse (Rao and Gravelle 2008) and breakoffs (Peytchev 2009; Heerwegh and Loosveldt 2006), one in particular has gained some attention in recent times: survey completion time. Read more

A View from the Top – A Comprehensive Analysis of Post-Recruitment Factors in a Consumer Panel Operation

Abstract:

In a recent study involving a mixed-mode experiment to recruit members to a consumer panel, Rao, Kaminska, and McCutcheon (2010) investigated the effect of various response-inducement techniques such as advance letters, monetary incentives, and telephone follow-up on panel recruitment. The experiment was successful in demonstrating that a combination of recruitment mode and one or more response inducements can maximize recruitment rate and minimize recruitment cost. Read more

Dealing With Extremely Long Response Lists in a Mixed-Mode Survey Environment

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

The Role of Survey Response Timing on Web Survey Results: Cross-Sectional and Longitudinal Analyses

Abstract:

Decreasing survey response rates are a growing concern in survey research, principally because survey estimates may be biased by selective nonresponse (Kypri, Stephenson, & Langley, 2004). One of the methods of assessing nonresponse bias is to compare those who respond late to a survey with those who respond early, in terms of the topic of interest. In this paper, we draw upon data obtained from multiple panel surveys conducted by the Gallup Panel in order to examine whether early, intermediate, and late respondents differ significantly – either in terms of demographics or in terms of the answers that they provide to survey questions. Read more