Marketing Bulletin, 2008, 19, Article 1
Page 1 of 19
New Measures and a New Model
for Television Network Loyalty (MOTNL)
Denny Meyer and Siva Muthaly
Network loyalty is of major interest to television program schedulers and advertisers. However, until
now there has been no method for measuring the loyalty of individual viewers. This paper analyses
People Meter data collected by Nielsen Media Research in New Zealand during July 2003.
provides information on minute by minute television viewing for 1067 individuals in terms of channel
and program genre. From this empirical data, new short-term and long-term measures of network
loyalty are calculated for each viewer. The short-term measure of network loyalty can be used to
monitor the frequency of channel switching within any 15 minute time slot, providing an essential
reality check for television ratings. The long-term measure of network loyalty can be used by network
schedulers to monitor performance. This data is used to test a postulated Model of Television
Network Loyalty (MOTNL) in which network loyalty is linked to viewer demographics, socio-
economic variables and viewing behaviour.
MOTNL has significant implications for network
executives in their programming choices as well as benefits for advertisers.
Keywords: channel switching, television ratings, network performance
Television consumers have a plethora of choice while switching from one television network
(channel) to another.
This behaviour has caused O’Keefe (2005) to ask “Is anyone watching
TV ads?”, suggesting that people indulge in frequent channel switching in order to avoid
advertisements. The network ratings, which are used to make advertising decisions, ignore
frequent channel switching behaviour. This research attempts to address this problem by
measuring and modelling an individual’s short-term and long-term network loyalty in relation
to preferred viewing time, network and genre, providing a tool which can be used to better
inform pricing and scheduling decisions for television advertising.
According to Shachar and Emerson (2000), an accurate television viewing choice model is a
critical working tool for both television network executives, who face difficult programming,
scheduling and marketing decisions, and advertisers, who want to get the most from their
spend. Shachar and Emerson claim that such a model can help television executives
maximise ratings by improving both the scheduling and the characteristics of their shows. In
addition it can help advertisers predict ratings and the demographic composition of the
audiences. Many researchers have developed such rating models (e.g.; Rust, Kamakura,
Wagner & Alpert 1992; Tavakoli & Cave 1996; Meyer & Hyndman 2006), however, the
usefulness of these models to advertisers is questionable when there is no accompanying
prediction of the frequency of channel switching as an indicator of reduced advertising
attention. In this study we develop a model which describes the frequency of channel