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  • DETERMINING TELEVISION ADVERTISING RATES

    By

    Benjamin J. Bates Paper presented at the 33rd International Communication

    Association conference, Dallas TX, May 1983. A revised version was published as:

    Bates, Benjamin J. "Determining Television Advertising Rates." In R. N. Bostrom (Ed.), Communication Yearbook 7 (pp. 462-475). Beverly Hills: Sage, 1983.

    Contact Info: Benjamin J. Bates School of Journalism & Electronic Media University of Tennessee Knoxville, TN 37996-0333 bjbates@utk.edu

    ABSTRACT Previous work has identified various factors as

    contributing to the setting of television rates, without giving indication or empirical verification of the manner or size of such effects. This study proposes that such quantification of effects upon television spot advertising rates can be achieved through the development of a predictive model for such rates over time. Using multiple observations from the period 1973-1981, the development of such a model provided strong evidence that the identified factors, and the factor of inflation, did affect the setting of spot rates. In addition, the examination of rates over time permitted the application of analysis of covariance techniques which indicated that the effects of certain factors had significantly changed over that period.

  • DETERMINING TELEVISION ADVERTISING RATES Commercial television stations are, for the most part,

    supported through the sale of a part of their broadcast schedule to advertisers. This time is sold primarily in the form of short spots interspersed among the stations' entertainment programming. As the supply of these spots is fairly constant, the rates which stations charge for these spots in their schedule are quite dependent upon the demand among advertisers for those spots. Since the aim of advertising is to convey a message to an audience effectively, and television is essentially a medium to reach an audience, the demand for advertising on a station will be dependent upon the audience that advertising message reaches.

    That is, since advertisers are actually purchasing access to an audience, it is expected that the price that advertisers would be willing to pay for that spot will depend upon that audience. Therefore the price that stations are able to get for their spots will depend on the audience that stations can attract for those spots. In previous studies over the last fifteen years, a number of audience factors have been identified as contributing to the determination of prices for broadcast time on television.

    In 1967, W. T. Kelley undertook a survey of broadcast managers in the Philadelphia area, and found that market size and quality, station coverage, and competition were all major factors which were considered in the rate-setting process. Kelley did not, however, provide any evidence or proposals as to the manner in which these factors contributed to the determination of rates. In an 1976 article, S. M. Besen attempted to fill this gap in part by deriving an empirical model for the value of television time. Using pure, or block, time rates as the dependent variable, Besen's model included measures of market size, competition, network affiliation, and

    the station's broadcast frequency. While providing empirical evidence of effects, the work was limited in that the model did not directly consider advertising spot rates and was limited to the examination of a single year. French & McBrayer (1979), in a qualitative article looking at the factors which determine station spot rates, found local market rates to be strongly influenced by three major factors: demand, competition, and ratings. And demand, they stated, was largely determined by the size of the market and local economic conditions.

    This study will involve the empirical verification and measurement of those factors cited in the previous studies, namely the size of the market, the quality of the market, local economic conditions, the direct competition from other commercial stations in the market, differences in station coverage, the network affiliation (if any) of the station, and the broadcast band in which the station operates. It will refine the cited factors where appropriate, define reasonable measures, and then examine the possible effects of those measured factors upon the rates for television spot advertising.

    It is not the goal of this project to provide a deterministic model of the rate setting process and proclaim its validity. The actual manner in which rates are set are too indistinct, relying more upon instinct and response to market forces rather than specific models or formulae. However, such processes are likely to involve non-concrete consideration of certain key factors. By modeling the apparent relationship between these factors and rates, it is possible to provide hard evidence in support of the role such factors play in the determination of advertising rates. The goal of this research is to provide such evidence.

    METHOD As the factors that this study addresses are considered to be

    determinants of spot rates, it was decided to base empirical

  • analysis upon predictive modeling procedures. These would primarily involve the development of linear or essentially linear models using a combination of real and categorical (indicator) variables. As the various studies made no proposals or predictions as to the nature of effects, this modeling process would not be directed towards the determination of a single predictive model for advertising spot rates. Rather, through the model building process and the consideration of alternative models, those factors having a general significant impact can be identified, and general indicators of the particular effects determined. The appearance of effects of similar size and type across models would, in fact, reinforce the significance and validity of a factor in the setting of rates.

    It was also decided to model this process over a period of time. Consideration of the factors and rates over time would allow for the reliable examination of the general significance of the factors without restricting the validity of the procedure and the results to a single period. In addition, the presence of multiple observations from a single station could allow for the direct consideration of a factor's effect as well as reflect the possible presence of additional explanatory factors. Further, the examining of rates over time would allow for consideration of possible changes in the size or significance of the various factors' effects over time, and the possible identification of trends.

    The measures used for this analysis were constructed to take advantage of data which are generally available. For the basic dependent factor of rate, or the price of television spots, it was decided to use the highest rate quoted for a thirty second (:30) television spot, as reported in the annual editions of either the TV Factbook or the Broadcasting Yearbook. As these rates were to be collected and analyzed over a period of time, only those rates which could be reliably determined to be valid at a

    particular point in time were used, and were noted in conjunction with that date. The associated date was then used to match the rate information with other dated measures.

    A second dependent variable was constructed by adjusting the rate data for the effects of inflation. The adjustment was made through the use of the Consumer Price Index (as advertising spots were considered to be finished goods) in an attempt to render the rates collected over time comparable. As will be pointed out in the analysis section, this attempt was only partially successful.

    The measurement of some of the cited factors as independent variables was quite straightforward. Reports of the network affiliation and broadcast frequency of stations were obtained from the TV Factbook and Broadcasting Yearbook. A simple nominal measure was constructed to indicate whether a particular station's frequency, or channel, assignment was in the UHF or the VHF bands. A nominal measure was also constructed to indicate the primary network affiliation of the station, if any.

    A consideration of the factors cited by the three studies reveals the need for the refinement or addition of another factor, as the size of the audience for a message or station is not directly considered. The factor of audience size would seem to be the single most important factor in differentiating audiences, and thus the demand for broadcast spots, yet it is not directly cited in those three previous studies. It would appear, however, that indirect consideration was given to audience size in the inclusion of the market size factor, though reliance on that measure alone presumes that all stations in the market cover that market both fully and equally well. Both of these assumptions are generally suspect, leaving an audience size measure of questionable reliability and validity. Some of the studies attempted to rectify this condition with the added

  • consideration of the factor of station coverage differences, removing major problems, but still leaving the consideration of audience size to indirect means.

    Thus, it would seem appropriate to include the factor of audience size among the potential factors affecting television spot rates. This factor's inclusion in the analysis is not only theoretically indicated, but it should also provide for a more reliable analysis and relieve any confounding of those factors which vary with station coverage.

    It was decided to measure audience size through the use of the Average Daily Circulation (ADC) for the station for a given season, as measured by Arbitron and reported in the TV Factbook. While not giving a specific measure of absolute audience at any given time, the ADC is a reasonably valid and reliable indicator of the number of households who can, and do, watch that station regularly over a period of time. Thus, it can be considered a good measure of the potential (or likely) audience for any station.

    The measurement of several other factors depended to a certain extent upon the specification of television broadcast markets. For the purposes of this study, it was decided to base market definitions upon those used by Arbitron, as reported in the Broadcasting Yearbook, only treating Arbitron's "supplemental" markets as separate markets. From this basis, the factor of market size was measured relatively by the rank of the market as reported by Arbitron for a season in the middle of the data collection period, resulting in an ordinal measure. Unranked markets were arbitrarily assigned ranks falling below the lowest of the ranked markets.

    The factor of direct competition from other stations was measured by the number of commercial television stations licensed and operating in the market at the given date. Noncommercial stations were not included as they did not

    provide competition for broadcast spots, although they did provide some competition for audience. The station's competition in the market, however, will also affect audience size, as it reflects the number of stations which must share the potential audience. That is, the actual audience for a station will be a share of potential audience, and that share is determined in large part by the competition a station faces.

    This leaves only the rather ill-defined factors of market quality and local economic conditions which had been cited in earlier studies. One aspect of both factors which should also be of particular interest to potential advertisers would be the wealth of the market; the ability of those in the audience to actually purchase the advertised goods or services. One widely available measure of this ability to buy is the Effective Buying Income (EBI) measure, as developed and reported by Sales & Marketing Management, Inc., in their annual Survey of Buying Power. For this study, a scaled, relative measure based upon the median market EBI was constructed. This market quality measure segmented the median market EBI as to whether it was, in comparison with the national median, over 20% above, between 5-20% above, within 5%, between 5-20% below, or over 20% below.

    A second measure of market quality was included, in the form of the forecast growth rate for the market. These forecasts, in the form of the projected growth in households in a market, were also obtained from the annual Survey of Buying Power volumes, and the rates scaled and segmented in the same manner as the EBI measure. It should be noted that the precise market definitions used in the Survey of Buying Power measures did not always precisely match those of Arbitron, although in all cases the major population center(s) were in accord.

    All measures were obtained on an annual basis where

  • needed to match the dependent variables obtained for commercial stations within the continental United States over the period 1974-1981. It should be noted, however, that valid rates were obtained from these sources for earlier periods, and those rates reported for 1973 were also included, along with the corresponding measures of the independent variables. An additional variable was then constructed to denote and label the stations for which data were collected and included for analysis. The resulting data set was then restricted to those data from stations for which at least four observations of rates were reported over the collection period. This yielded a set of 856 observations from a total of 164 stations for preliminary analysis. Later, the data set was expanded to include observations from other stations in the same markets as those in the initial set of observations. This second, expanded data set included a total of 1068 observations from 232 stations.

    ANALYSIS The analysis for the significance of the cited factors began

    as an exploratory data analysis leading to the development of predictive models for spot rates. First, the data sets were examined to identify the significant predictive factors for television spot rates. Note was taken of the different types of measures used to derive the various independent variables, and those initial measures were treated or transformed where appropriate to fit the kinds of effects or relationships revealed in these exploratory procedures.

    The analysis began with an examination of the cross-correlation matrix among the ten variables. Several of the measures evidenced a correlation with the dependent variables of spot rates (RATE) and the spot rates adjusted for inflation (ADJRATE). Those correlations greater than 0.1 are listed by factor in Table 1. A highly significant correlation was evidenced between the audience size measure (ADC) and

    the dependent variables, tending to confirm the importance and significance of this factor in the setting of television spot rates. High correlations were also found for the initial variables measuring the factors of mar...