Understanding Radio RatingsBy admin
Radio was the first telecommunication medium, and thus was the first to require audience estimates. Radio ratings are therefore the oldest form of telecommunication ratings. To understand radio ratings, you must be familiar with the following terms and concepts.
AUDIENCE ESTIMATES: All telecommunication ratings are estimates of audience participation. These estimates are based on audience surveys. The limited number of people sampled in ratings surveys accurately represents the larger total audience only if the survey methods are statistically valid. This means they must comply with the mathematic rules of random statistical sampling. Their accuracy (and margin of error) depend on the methods used.
INDIVIDUALS AS UNITS: Because radio has become primarily an individual medium (people participate more often alone than in groups), individuals are the measuring unit for radio ratings. Radio ratings measure the number of individual persons in the audience for each radio station.
LOCAL AUDIENCE: Since the 1950s, radio has become largely a local medium. That is, most radio programming does not originate at the network level. Local broadcasters assemble music, news, talk, and other forms of entertainment at a single local studio and transmit them to a local audience. National radio ratings do exist, but are insignificant to a basic understanding of radio ratings. Radio is essentially a local phenomenon in America. The implication for ratings (of this local orientation) is that only local ratings are taken regularly. Arbitron specializes in local radio ratings, as does Birch Radio.
STATION DAYPARTS: Radio programming (and therefore, radio ratings) are divided into dayparts lasting several hours each. An example is Morning Drive, which might last from 6:00am till 10:00am, and encompasses that period of time in the morning when people are driving to work. An announcer (sometimes more than one) is assigned to host a given daypart on a daily basis, Monday through Friday. Weekends have unique dayparts of their own.
RATINGS DAYPARTS: Daypart names, times, and lengths differ from station to station, and may or may not be the same as the daypart definitions used by the ratings service(s) which measures the audience.
CUME: This term is an acronym for “cumulative,” and identifies a particular type of radio audience statistic. The CUME statistic measures the number of individual persons who tune into a given radio station in a calendar week. An individual listener will be counted only once in the CUME statistic, regardless of how many times (s)he listens during the week, or for how long.
AQH: This term is an acronym for “average quarter hour,” and identifies another type of radio audience statistic. Most radio ratings services divide each broadcast hour into four quarter-hours (15-minute segments) for measuring purposes. For each quarter- hour, within every hour of every day, an audience sample is taken. Any listener who tunes into a given radio channel for a minimum of five (5) minutes during a quarter-hour segment, is counted in the AQH statistic for that quarter-hour. Listeners are counted for any and every quarter-hour in which they participate. For example, if an person listens for 30 minutes, (s)he will be counted in the AQH for the first quarter-hour, and then again in the AQH for the following quarter-hour. The “Average Quarter Hour” statistic is calculated by averaging all the quarter-hours in a given daypart. For example, if Morning Drive is from 6:00am to 9:00am, there are three hours involved (making a total of 12 quarter-hours). The number of listeners counted in each of those 12 quarter-hours are added together and divided by 12 to come up with an average number of listeners in Morning Drive quarter-hours. This is the AQH statistic. It represents the average number of persons listening to a given station at any given moment in time, within a given daypart.
Each radio ratings service determines the boundaries for its own survey area(s). But they are usually divided into at least two types:
METRO SURVEY AREA (MSA): The metropolitan area served by the radio stations being measured. In Utah, this would normally include the largely urban areas encompassed by Salt Lake City, Ogden, Provo, and those suburban cities which lie in between.
TOTAL SURVEY AREA (TSA): The entire geographic area which can be reached by the radio stations being measured. In Utah this would usually include the entire state of Utah, plus some adjoining counties in Nevada, Idaho, and Wyoming.
The Problem With TSAs: Some stations who do not do well in the metropolitan survey area will quote statistics for the total survey area. This is somewhat misleading, unless the intended advertiser is interested in and capable of serving listeners in a wide, multi- state area.
If a station reaches 5,000 people state-wide, but only 1,000 people in the immediate metropolitan area, the local hamburger restaurant may not be getting full value if the station quotes listener statistics based on an area far beyond the restaurant’s natural marketplace. Ethical professionals are careful about quoting TSA statistics.
TYPES OF STATISTICS
RATING: Either the CUME or the AQH may be expressed as a “rating.” While this term is often used in a general way to talk about the entire “radio ratings” process, it actually has a specific meaning. The rating is the CUME or the AQH statistic, expressed as a percentage of the total potential audience (all the persons living in the survey area who belong to the specified gender and age group). In other words, it is the percentage of all those living in the area, whether or not they listened to radio that week. Some examples follow:
SHARE: Either the CUME or the AQH may also be expressed as a “share.” The share is the CUME or the AQH statistic, expressed as a percentage of all the persons listening to radio in the survey area who belong to the specified gender and age group. In other words, it is the station’s share of those in the defined gender/age group who actually listened to radio (any channel) during that week (CUME) or that quarter-hour (AQH). Some examples follow:
Ratings and Shares statistics each tell us something about the audience. But they are more useful when we combine them and critically analyze the result. For example:
TIME SPENT LISTENING (TSL): Listener loyalty can be directly measured by calculating the amount of time which an average listener spends listening to a particular station. To compute this, you need to know the following formula:
The number of quarter-hours is determined by the daypart selected. Let us assume that the daypart is Morning Drive (6:00am-9:00am). In those three hours there are 12 quarter-hours per day. In the week there are five days. This makes a total of 60 quarter-hours in the week, and that is the number used in calculating Time Spent Listening during the week. If the statistics quoted in the Example #1 above (AQH=100, CUME=20,000) were for this three-hour Morning Drive daypart, we could then calculate the TSL as follows:
Remember that this .3 answer is expressed as quarter- hours, not as hours. Since a quarter-hour consists of 15 minutes, we are looking here at .3 X 15 minutes, or 4.5 minutes. This means that the average listener to this station listens for less than five minutes per week during Morning Drive time. This is pretty dismal.
Example #2 had a much more loyal audience (AQH=2500, CUME=10,000). We would expect the TSL to be much higher, and it is:
These 15 quarter-hours equal 45 minutes, meaning that the average listener to this station listens 3 hours and 45 minutes per week during Morning Drive time. This is much better, and more likely to produce results for an advertiser.
AVERAGE FREQUENCY: Advertising professionals appreciate loyalty, but they know something more. Listeners who need or are prone to buy a product will not respond to an ad for that product until they have been exposed at least three times to the advertisement’s message. This is called a frequency of three. An ad must be placed on a station enough times so that the average listener (who tunes in and out throughout the week) will hear its message at least three times.
To determine how many times a commercial must be played in a week on a given station, so that the average listener will hear it at least three times, we must know the formula for calculating the Average Frequency:
Using simple algebra, and assuming that we want an Average Frequency of three (3.0), we can then determine the following formula:
Example #1 above described a station with a low level of listener loyalty (AQH=100, CUME=20,000). This is reflected in the number of radio spots which would have to be purchased in order to obtain a frequency of 3:
Example #2 had a much more loyal audience (AQH=2500, CUME=10,000). This is reflected in the relatively few number of radio spots which would have to be purchased to obtain a frequency of 3:
Knowing the Time Spent Listening (TSL) and Average Frequency (AF) is essential to understanding audience loyalty and the number of spots which need to be purchased to produce results in an advertising campaign. But those statistics are insufficient if not combined with data about the cost of advertising on each station.
In the highly competitive radio broadcasting business, salespersons are sometimes misleading in their claims about costs. One salesperson may say, “I’ll sell you my spots for $3.00 each!” Sounds like a bargain. Another may charge as much as $50.00 each. Sounds much higher. But is it?
COST PER THOUSAND (CPM): To compare the cost of advertising on one station with the cost of advertising on another, we need to know more than the cost per spot. We need to know the cost per thousand persons. In radio, this is always based on AQH statistics. The formula looks like this:
Dividing the AQH by 1000 gives you the “number of thousands” being purchased. Dividing that result into the cost per spot gives you the cost per thousand.
Example #1: Suppose that the station which charges $3.00 per spot is the one above with an AQH of 100 persons. The CPM would calculate as follows:
Example #2: Suppose that the station which charges $50.00 per spot is the one above with an AQH of 2500 persons. The CPM would calculate as follows:
The $50.00 per spot station charges only 2/3 as much to reach a thousand people as does the $3.00 station.
COST PER POINT (CPP): A more useful comparison takes into account the loyalty of the audience, and also accounts for the cost per spot. This comparison is called the cost per point. It is calculated by determining the AQH rating points of the station, and then dividing the cost per spot by those rating points:
The formula below the line calculates the AQH rating points for the station. This is divided into the cost per spot to determine the cost per point.
Example #1: If our first example station above (the one with an AQH of 100 and a cost per spot of $3.00) were in a market where 100,000 teens reside, the CPP would look like this:
Example #2: If our second example station above (the one with an AQH of 2500 and a cost per spot of $50.00) were in the same market of 100,000 teens, the CPP would look like this:
Comparisons are fine for determining which stations are most efficient in delivering an appropriate audience. But once these determinations have been made, we must combine cost information with the Average Frequency (AF) statistic to determine the total budget needed for minimum advertising effectiveness (a frequency of three). Our two stations looked like this:
|Category||Example #1||Example #2|
|Spots needed for a frequency of 3||600||12|
|Cost per spot||$3.00||$50.00|
|Minimum Effective Budget||$1,800||$600.00|
The minimum effective budget is determined by multiplying the number of spots needed for a frequency of 3.0 by the cost per spot. From this we can see that the first station, which proudly announces it will sell spots for $3.00 each, is actually a very expensive buy. It requires $1,800.00 of advertising to achieve a frequency of 3.0. The second station appears on the surface to be more expensive ($50.00 per spot), but actually costs only 1/3 as much ($600.00) to achieve the same frequency of 3.0. Based on these data, which station would you buy? The answer should be obvious.