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SEASONALITY AND TALK RADIO AUDIENCES
 
 
 
 
 
 
 
 
 
 
 
Jeffrey S. Wilkinson, Assistant Professor
Department of Broadcasting
The University of Tennessee at Knoxville
Knoxville, TN  37996-0333
(615) 974-4291  (fax: 974-2814)
Internet:  <a href="/cgi-bin/wa?LOGON=A3%3Dind9602A%26L%3DAEJMC%26E%3D0%26P%3D1231423%26B%3D--%26T%3Dtext%252Fplain" >[log in to unmask]</a>
 
August E. Grant, Associate Professor
Department of Radio/TV/Film
CMA 6.118
The University of Texas at Austin
Austin, TX 78712
(512) 471-6640  (fax: 471-4077)
Internet:  <a href="/cgi-bin/wa?LOGON=A3%3Dind9602A%26L%3DAEJMC%26E%3D0%26P%3D1231423%26B%3D--%26T%3Dtext%252Fplain" >[log in to unmask]</a>
 
 
 
 
March, 1995
 
 
 
 
 
 
 
 
 
        Paper submitted to the Media Management and Economics division of the
 
        Association of Educators in Journalism and Mass Communication.
 
 
 
 
 
 
Seasonality and Talk Radio Audiences
Abstract
        It is important for advertisers and radio station managers to understand
 
          the cyclical nature of audiences.  This study examined talk radio
ratings
 
          in all U.S. markets that are measured four times per year over a
 
  five-year-period in order to identify some trends and evidence of
 
   seasonality. The findings suggest that some dayparts are more seasonal than
 others, some seasons benefit certain dayparts over others, and talk radio
 
          is influenced by and influential with elections under some conditions.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
SEASONALITY AND TALK RADIO AUDIENCES
 
        The only constant about radio audiences is their inconsistency. Audiences
 
          fluctuate with changes in program, listener preferences, and even the
 
       seasons of the year. A great deal of research has been devoted to how
 
       ratings change as a result of changes in station behavior or listener
 
       preference, but almost no research has addressed the seasonality of radio
 
          ratings. This seasonality is especially important, because as a cycle,
 
        regular variations should be expected in radio ratings. The purpose of
this
 paper is to identify some of the underlying elements contributing to
 
       radio's seasonality.
        The problem with any such exploration is the tendency to treat radio as a
 
          homogenous medium, when it actually is comprised of a multitude of
formats,
 serving a variety of roles and goals for listeners. Rather than examining
 
          all radio formats, the focus of this paper is upon Talk Radio, because
it
 
          is designed to fulfill the broadest range of goals, simultaneously
 
    informing and entertaining listeners.
Seasonality and Cycles
        The variability in media consumption patterns reflects and is consistent
 
          with those found in nature and society (Zerubavel, 1981). For example,
 
        television viewing patterns have been found to be both seasonal and
 
     cyclical (Barnett, Chang, Fink, & Richards, 1991). Some of the seasonal
 
         factors that influence television viewing include weather (Gould,
Johnson,
 
          & Chapman, 1984) and number of hours of daylight (Gensch and Shaman,
1980).
        An understanding of the cyclical nature of audiences is important for
 
        advertisers, station managers, and researchers because broadcasting
 
     companies are especially sensitive to cycles.  Davis and Lee (1980) have
 
          reported that cycles exist for advertising sales, and sales are the
 
     lifeblood of the media--particularly broadcasting companies. Most if not
 
          all operating revenues for these organizations come from ad sales
(Lavine &
 Wackman, 1988).
        Because broadcast media are so dependent on advertising, and advertising
 
          is based on audience ratings, both advertisers and managers must know
 
       something about regular fluctuations in audience consumption patterns as
 
          reflected by ratings data. People have both weekly patterns of media
use as
 well as daily patterns. Two complimentary cycles are evidenced in daily
 
          television and radio use. For example, overall radio listening is
generally
 highest in the mornings, while television viewing is generally highest at
 
          night.
        Identification of degree of seasonality in radio ratings, as well as of
 
          factors that increase or moderate the effect, is important to both
 
    broadcasters and advertisers. In order to interpret ratings, broadcasters
 
          need to be aware of the extent of regular variations in listening
patterns
 
          for their station and their competitors.
        Understanding seasonality is probably most important for advertisers, who
 
          rely upon ratings data in the purchase of commercial time. Since
virtually
 
          all ratings data are measures of past performance by stations,
advertisers
 
          are forced to assume that current station performance can best be
estimated
 by past performance. Identifying the degree of seasonality for specific
 
          formats will help advertisers make more informed decisions, and
maximize
 
          their ability to predict the audience reached through a specific buy.
Radio is a vibrant medium
        Radio remains the most common and mobile form of electronic communication.
 There are well over 11,000 radio stations licensed in the U.S., listened
 
          to every day by 77% of the population.  Furthermore, approximately 95%
of
 
          all cars have radios in them, undoubtedly a major contributor to the
 
      estimated three-and-one-half hours daily listening time (Radio Advertising
 
          Bureau, 1993, cited in Bartlett, 1993).
        The radio industry can reap tremendous benefits from understanding cycles.
 Although eclipsed by television in terms of attention and dollars, radio
 
          is alive, vibrant, and growing.  Recent figures show that 1994 overall
 
        radio ad sales were up 11-12% over 1993 figures (Radio & Records,
January
 
          6, 1995).  According to Duncan's American Radio, total radio station
 
      revenues may have surpassed the $10 billion-dollar mark for the first time
 
          ever. The Radio Advertising Bureau has further noted that the industry
has
 
          enjoyed over two years of solid growth and sales increases
(Broadcasting &
 
          Cable, November 7, 1994), and many believe that this growth will
continue.
        There are some who believe that radio sales are more sensitive to
 
    fluctuations in the economy (Broadcasting & Cable, October 24, 1994), but
 
          little research has explored changes in audience beyond dayparts. The
 
       notion that "radio audiences are largest in the morning, smaller at
 
     mid-day, larger in the afternoon, and disappear at night" is well-known and
 supported by ratings figures.
        But if cycles have been identified for television viewing (Barnett et al,
 
          1991), it is logical that such cycles also exist for radio listening.
If
 
          these cycles also exist for radio, then it is important for
practitioners
 
          and researchers to identify and understand them. This information
could be
 
          used to help advertisers schedule messages, and even lead to
discussions of
 whether some message approaches work better than others, depending on what
 part of the slope the overall audience listening cycle is located. All of
 
          these issues are the rationale for investigating the seasonality of
radio
 
          listening.
The Rise of Talk Radio
        Radio was forced to adapt when television came on the societal scene 40+
 
          years ago. In order to survive, radio stations turned to niche
programming
 
          and the notion of "the format" was born. Today there are dozens of
formats,
 some of them virtually indistinguishable from the other.
        Radio listening patterns shifted dramatically in the late 70's and early
 
          80's. AM radio listenership plummetted, as listeners migrated to the
FM
 
         band. Despite roughly equal numbers for commercial AM and FM stations
 
       (roughly 5,000), the audience share for AM radio is at best one-fourth of
 
          the total listening audience (Keith 1993/1994).
        Not all radio stations have been created equal. Bates (1995) found that
 
          daytime-only AM stations are handicapped in terms of station value.
This
 
          handicap is estimated to reduce the value of those stations by
one-third to
 one-half that of comparable full-time AM stations. This effect was even
 
          more pronounced in large-market AM/FM combos, where it appears that
the
 
         daytime-only frequency contributes nothing to the overall value to the
 
        combination (p.22).
        Recently there have been some encouraging signs for AM stations.
 
   Listenership levels appear to be no longer dropping, and in fact, may be
 
          increasing. Talk Radio is leading the recovery for AM, and many
programmers
 point to the phenomenon of Rush Limbaugh as a prime factor (Radio Only,
 
          1994). Limbaugh is credited with turning many marginal operations into
 
        successes, and has been found to have brought a substantial number of
new
 
          listeners to the AM band (xxxxxxxxxxxx, 1995).
        The success of the Talk Radio format (which includes the hybrid News/Talk
 
          as well) on AM makes it of special interest to researchers. Talk Radio
has
 
          found a niche that links listeners to government, information, and
topics
 
          in ways that music formats have not or cannot.  Talk Radio is
extremely
 
         personal (Tramer & Jeffres, 1983), and involves its listeners to a
greater
 
          extent than other formats (Warner & Buchman, 1993).
        Talk Radio is also inextricably linked to political speech. In fact, one
 
          of the socially-defined seasonal cycles for Talk Radio stations may be
in
 
          their coverage of political activity. For example, talk show host Rush
 
        Limbaugh generated enough controversy for Congress to discuss the
possible
 
          reinstatement of the Fairness Doctrine. More recently, talk show hosts
 
        broadcast their programs from Capitol offices provided by House Speaker
 
         Newt Gingrich (Radio & Records, January 6, 1995).
        Of all the AM formats, Talk Radio may be arguably the most successful. In
 
          many of the largest markets, the highest-rated AM station offers a
Talk or
 
          News/Talk format (Keith, 1993/1994). In fact, this type of format is
 
      frequently the ONLY AM station ranked in the top-10 in terms of audience
 
          ratings. The successes of the AM Talk Radio format and the role of
 
    seasonality and cycles in listening are the focus of this study.
Hypothesis
        The hypotheses are based upon the notion that there are fluctuations in
 
          radio audiences as there are in television audiences. This seasonality
must
 be considered by managers and consultants because it directly impacts on
 
          estimated station worth and value.
        Although radio is a mobile medium and probably not dependent upon
 
    environmental factors in the same way television viewing is, Media System
 
          Dependency Theory suggests that the result will be the same.
According to
 
          this theory, people will turn to the media for help during times of
 
     ambiguity and threat (Ball-Rokeach, 1985).  Talk radio, by virtue of its
 
          political and opinion-driven content, probably fulfills this function
 
       better than other types of radio formats.
        Media system dependency also suggests that dependency relationships at one
 level of analysis will affect those at other levels. In this case, our
 
         focus is on the relationship of the individual listener to the talk
radio
 
          medium. In considering this relationship, we must also consider the
 
     macro-level dependency relationships, specifically between talk radio and
 
          the political system. Ball-Rokeach (1985) specifies that the media
system
 
          is dependent upon the political system for legitimation, judicial and
legis
 
          lative protection, and for "political decision makers' capacities to
 
      generate conflict and drama that is grist for the media mill."
          (pp.491-492).
        Therefore, summer months are typically a "slower" time in terms of
 
     political, economic, and even media activity. At the same time there is
 
         less activity among these institutions, personal activity also tends
toward
 increased leisure time which corresponds to greater available daylight
 
         time. More vacations are taken during the summer, which further breaks
the
 
          regular listening or viewing routines. All of these personal, social,
and
 
          natural factors result in decreased dependency on media, and
therefore,
 
         reduced media use during summer months. Therefore, our first hypothesis
 
         addresses this issue:
        H1: The seasonality in talk radio audiences follows the same pattern of
 
          television viewing in that warm weather listening (Spring and Summer)
will
 
          be least while cold weather (Fall and Winter) listening will be
greatest
 
          overall.
        A second consideration regarding talk radio audiences is the variable of
 
          market size. A functionalist approach would suggest that "big city"
talk
 
          radio listening may serve a different purpose from that of "small
town"
 
         talk radio. Media System Dependency Theory hints that the relatively
 
      unstable nature of the large, supposedly impersonal metro makes the media
 
          (and talk radio) more important to its consumers than the alleged more
 
        personal nature of living in a small town. If Talk Radio is more
important
 
          in the big city, then listeners will use greater effort to listen on a
 
        regular basis, resulting in greater seasonality.
        However, one may suggest the same argument could hold true for smaller
 
         markets.  This is based on the notion that, as the number of stations
in a
 
          market goes down, format duplication disappears and the station
assumes a
 
          different role in the community. In the larger markets, there may be
more
 
          than one talk, news, or newstalk station competing with dozens of
other
 
         signals. But in the smaller markets, there may be only one station
carrying
 this programming because Talk Radio is more resource intensive (expensive)
 than programming music. Since there is no direct competition for that
 
        audience, the small market Talk Radio station better serves as a local
 
        barometer for goings-on in the community. One may argue that this would
 
         result in higher dependence and therefore, greater seasonality based on
 
         regular listening cycles. Despite the competing notions of whether
large or
 small markets are subject to greater seasonality, this paper chooses to
 
          side with the media system dependency model rather than "conventional
wis
 
          dom" on this matter, suggesting that a second hypothesis would be:
        H2: Larger markets (those with more stations and presumably, more than one
 Talk or News/Talk station) will show MORE seasonality than smaller markets
 (with fewer stations and therefore fewer Talk or News/Talk stations). The
 
          larger the area population, the greater the change from season to
season.
        Within the larger framework of seasonality in ratings, listening patterns
 
          should also exhibit both daily and weekly cycles. For example, because
 
        listening is greatest in the morning, this time period should be least
 
        sensitive to events and social changes because of the greater numbers
 
       involved. Morning listening may be perceived as ritualized listening, and
 
          should therefore should remain relatively stable over the course of
time.
 
          Therefore, the next set of hypotheses focus on specific dayparts:
        H3a: Morning drive times will show least seasonality compared to mid-day,
 
          afternoon, or evening periods because morning listening is habitual
 
     listening.
        Another listening period that should show seasonality is evening
 
   listening. Talk radio listeners who listen at night have probably
 
   supplanted television viewing with this type of leisure activity,
 
   therefore:
        H3b: Evening listening will show greatest seasonality.
        A final area of interest would be to examine cyclical infuences from
 
       another sphere of social life. Every two years there is a major political
 
          election season, and every four years Americans elect a new President.
        Because Talk Radio has become an influential and popular outlet for
 
      political speech, it would make sense that these stations would become
even
 more popular during election periods. As mentioned earlier, the Rush
 
       Limbaugh program has brought new listeners to AM talk radio, and also
 
       helped revive interest in American politics (Lewis, 1993). Because this
 
         program airs during mid-days in most markets, it suggests a link
between
 
          the mid-day time slot and recent election-period ratings. This leads
to our
 final hypotheses;
        H4a: Talk Radio ratings overall will be significantly higher during an
 
         election season (which tends to occur during Fall of every other year)
than
 during the "off" years (odd-numbered years).
        H4b: Talk Radio ratings during mid-days will be the highest during the
 
         Fall season of election years.
Method
        The method of assessing radio listening hinges on secondary analysis of
 
          ratings data. Ratings information was obtained from the Arbitron
Rating
 
         Archive at the University of Georgia and from Arbitron's own archives.
 
        Ratings data from all U.S. radio markets that are rated four times each
 
         year were collected (N=94). This resulted in a data set comprised of
 
      ratings for each of those markets from Spring 1988 through Spring 1993
(the
 latest date for which data were available at the time of data collection).
 It is logical to believe that cyclical patterns in listening would be
 
        identifiable over a five year period.
        In addition to the ratings data, the variable of MSA (Metro Survey Area)
 
          was collected from the 1994 Broadcasting & Cable Yearbook. The MSA
figures
 
          were based on 1993 Arbitron data.
After this variable was matched to the ratings data, SPSS-PC+ software was
 
          used to test each hypothesis.
        Seasonality was conceptually defined as the degree of variation between
 
          the highest and lowest ratings period of the year. This variable was
 
      operationalized by computing the mean rating for each daypart across the
 
          five years, then computing the difference between the highest and
lowest
 
          rated of the four ratings periods (fall, winter, spring, and summer).
Results
        The first hypothesis proposed that seasonality in talk radio audiences
 
         will follow the same pattern as television viewing in that Spring and
 
       Summer ratings will tend to be lowest, while Fall and Winter ratings will
 
          tend to be highest. This hypothesis was supported. The maximum or
highest
 
          ratings for each individual station occurred during Fall or Winter
almost
 
          three-fourths of the time (73%), while Spring or Summer produced the
 
      highest ratings only one-fourth of the time.
        The second hypothesis suggested that the larger the market, the greater
 
          the change from season to season. This hypothesis was supported. MSA
 
      population as a surrogate measure of market (where more people indicates
 
          smaller market size) was negatively related to seasonality (r=-.29,
p<005).
 Further research was conducted to explore the relationship between market
 
          size and seasonality within each daypart. Strong seasonal effects were
 
        observed during the daytime (AM drive, r=-.30, p<.005; Midday, r=-.35,
p<
 
          .001; PM drive, r=-.24, p<.05), but market size was not related to
 
    seasonality of evening and weekend ratings.
        The third set of hypotheses suggested seasonality predictions for various
 
          time periods. Hypothesis 3a predicted that morning drive time will
show the
 least seasonality of the three day periods (morning drive, mid-day,
 
      afternoon drive). This hypothesis was not supported. Although morning
drive
 was significantly less than midday and evening time periods, morning and
 
          afternoon drive times were not significantly different.
        Hypothesis 3b predicted that evenings would show greatest seasonality.
 
         This hypothesis was supported. Evenings showed the greatest variability
of
 
          all the time periods analyzed (see Table 1).
        The fourth area of interest was talk radio listening during elections. It
 
          was hypothesized that overall ratings for talk radio would be
significantly
 higher during election years than non-election years. This hypothesis was
 
          not supported.
        The final hypothesis focused on the relationship between election seasons
 
          and the recent Rush Limbaugh phenomenon. Specifically, that Limbaugh
and
 
          the mid-day time period for talk radio would show significantly higher
 
        ratings during recent election seasons. This hypothesis was supported.
The
 overall means were significantly higher during election years for the
 
        mid-day time periods (t=2.57, df=92, p<.01).
Discussion
        This study sought to identify whether seasonality does extend to talk
 
        radio. The answer seems to be a qualified "yes" with several
implications
 
          for advertisers and station managers.  This study found support for
the
 
         hypothesis that seasonality and cycles exist with radio--specifically
Talk
 
          Radio--audiences. Market size is significantly correlated to larger
ratings
 figures and greater seasonality. Also, weekends and evenings tend to show
 
          more seasonality than the daylight time periods. This analysis was
unable
 
          to find clear evidence of cyclicality during the morning, midday or
 
     afternoon dayparts, and this bears further scrutiny.
        Examining arbitron ratings in the top 94 markets over a five-year-period
 
          does reveal some important things about talk radio listening in
America.
 
          First of all, the daytime radio listener is different from evening or
 
       weekend listening.  Daytime listening appears to be linked to social and
 
          political trends and events, while nighttime and weekend listening is
more
 
          ritualized. This suggests that evening and weekend talk radio
listeners use
 the medium in the same cyclical patterns as television viewers use tele
 
         vision.
        But talk radio listening during the day is something entirely different
 
          from these "off-hour" dayparts.  Apparently, talk radio during the day
 
        functions more as a barometer in people's daily lives, and is therefore
 
         subject to unpredictable fluctuations.  These fluctuations stem from
our
 
          involvement with our world, so political, social, and economic events
may
 
          trigger changes in our listening behaviors en masse.  With this in
mind, it
 seems this study took a series of ratings "snapshots" over a five-year pe
 
          riod to identify some key periods and trends in America (see graph in
 
       Figure 1).
        Throughout 1988 and up to the Summer of 1989, daytime talk radio was mired
 in a downward slope as fewer people were tuning in. The nadir for talk
 
         radio stations was the time roughly between Summer 1989 and Summer
1990, as
 across the country, overall ratings dipped to even lower levels than the
 
          year before. Judging from the downward slope, 1988 was not a banner
year
 
          for talk radio either.
        But nationally, Talk Radio showed a dramatic turnaround in the Winter
 
        1991. This may be explained by two factors, one political and one
social.
 
          The Gulf War riveted people's attention and evoked extreme feelings of
 
        partiotism and concern. Because of the ability of talk stations to
involve
 
          listeners (by entertaining AND informing at the same time), they
became key
 outlets for the community to express its sentiments about the war.  This
 
          political event translated into listeners (which in turn translated in
 
        higher ratings and therefore advertising dollars) much the same as CNN
 
        viewership skyrocketed during this period.
        But the Gulf War may have simply been what triggered Talk Radio's
 
    comeback.  While CNN viewership gains disappeared after the war (Zoglin,
 
          1992), Talk Radio ratings across the country continued to bounce back
to
 
          even higher levels.  This new acceptance and interest in talk radio
was
 
         spurred on by controversial hosts like Rush Limbaugh.
        It is suggested here that, although Limbaugh premiered in 1988, it wasn't
 
          until the Gulf War attracted so many people to "tune in" (as
dependency
 
         theory would predict) that many people (especially conservatives)
"found"
 
          their spokesperson. Once they tuned in, the behavior became a habit,
as
 
         Limbaugh successfully tapped into what these individuals desired in a
talk
 
          show. The past two years do not show an overall seasonality or
cyclical
 
         pattern for talk radio, in part because new listeners have been brought
to
 
          the AM band through Limbaugh and others. This would explain why the
overall
 slope continues upward rather than a relatively stable wave of ups and
 
         downs.
        The implications of this study are numerous, and further examination of
 
          other radio formats rating data is advised. Because evening and
weekend
 
         listening is ritualized media behavior, management should arrange their
 
         programming so that it matches audience needs. This is good news for
 
      syndicators and producers of shows with a track record. Evenings and
 
      weekends are not the best time for experimenting with new material,
because
 these times show great seasonality. While some change and experimentation
 
          is certainly unavoidable, programs that have become established with
their
 
          listener will be the most effective, because it's become habitual
media
 
         consumption. This brings a predictability to ratings that advertisers
have
 
          long sought. For example, if a campaign must be launched during a time
when
 audiences are traditionally smaller (such as spring or summer), this
 
       knowledge allows the advertiser to set more realistic goals for the
 
     effectiveness of their radio buy.
        Another implication of this study suggests that ratings services should
 
          consider weighting of ratings to take seasonality into account. This
would
 
          effectively "level the playing field" in that advertisers could
understand
 
          that differences in ratings periods can be independent of the station
 
       programming. What further study should attempt to do is identify how the
 
          ritualized listeners are different from the more "active" daytime
 
   listeners. Although the daytime audience tends to be much greater, they are
 not very seasonal and use the medium for surveillance rather than
 
    entertainment and leisure. This should suggest varying strategies for
 
       advertisers to appeal to the different needs of each audience group.
        In conclusion, it appears that talk radio is alive and well, and thriving.
 By finding evidence of different patterns of seasonality among various
 
         dayparts, this study suggests that radio audience fragmentation not
only
 
          occurs between formats, but with a given format as well. By better
 
    identifying the consumers of a given radio format such as talk radio and
 
          the functions it fulfills, station managers and advertisers may better
meet
 those listener needs.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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TABLE 1
 
 
 
 
Variable           Mean         SD              t-value  df      1-tail Sig
------------------------------------------------------------
 
Evening    2.16      1.899
AM drive     1.26           .926
                                                    4.96     93     p<.001
------------------------------------------------------------
 
Evening    2.16    1.899
Mid-day    1.69     .978
                                                       2.31     93     p<.05
------------------------------------------------------------
 
Evening    2.16    1.899
PM drive     1.12           .877
                                                       5.62     93     p<.001
------------------------------------------------------------
 
Evening    2.16    1.899
Weekend    1.36    1.126
                                                       4.74      93     p<.001
------------------------------------------------------------
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
FIGURE 1