By
PIET SMIT
Technical Advisor (SAARF)

There is a general danger that users of Market Research data will misinterpret results and thereby create confusion in the minds of interested parties. It is also possible for surveys to be conducted in such a manner that the results will not provide data that can be reliably used for their intended purpose. This scenario is especially true for Radio Audience Research and therefore SAARF has been asked to produce a summary of Best Demonstrated Research Practice that can provide authoritative guidelines to the marketing industry.

The need for such a document has increased in recent times. When SAARF was formed in 1974, there were less than 10 licensed radio stations; currently this number varies between 130 and 140. The increase is partly due to the arrival of community radio and partly to the so-called ‘opening up of the airwaves’ by privatizing some of the SABC stations, which for years operated almost all radio stations in South Africa. New licenses were also provided to commercial enterprises.

The above developments created the potential for much more fragmented radio audiences than hitherto. Naturally each station wishes to determine the size and demographic characteristics of its audience and therefore it is vital that not only the credibility of SAARF's Radio Audience Measurement Survey (SAARF RAMS®) is maintained as the "currency" for buying and selling of radio advertising time, but also that the many newcomers to the radio industry are made aware of the many pitfalls when conducting their own market research. These guidelines were written as many radio stations, in particular community station owners, have commissioned research that does not meet recommended technical criteria.

The RAMS® diary samples were originally designed to measure national and regional audiences down to the provincial level. Most of the community stations' footprint areas are more localized, and consequently, more than one of the RAMS Diary fieldwork waves are rolled together to measure them. Before the licensing of community radio stations, SAARF had required a minimum of 200 AMPS diaries in the reception area of a regional radio station. In an attempt to report information for as many community stations as possible, this criterion has for the interim been lowered to a minimum of 140 diaries. A further criterion is that at least 40 respondents should claim at least one quarter hour’s listening during the seven-days for which the AMPS diary is kept, before demographic details of the audience can be published. To further assist these stations to provide at least a total audience estimate, it was decided that, irrespective of the number of listeners, a total audience figure will be reported.

The current structure of the RAMS® diary sample is sufficient to measure most of the community stations on two combined samples, the way in which audiences are normally reported. However, some of them do not qualify for full reporting but only for a total audience figure. A new approach for reporting by combining more than the mentioned two fieldwork waves to provide larger samples for smaller stations is being investigated.

For the stations for which the RAMS® diary sample is too small, but there is a high incidence of listening to that station, SAARF monitors the audience levels over time and if the information indicates that a station could probably be reported if the sample was large enough, and if it is economically justifiable to increase the sample, it is increased to qualify. Due to this reason the sample has been increased in some areas from time to time.

Because it is essential for all radio stations to have an in-depth knowledge of their audiences, SAARF strongly recommends that all stations should do their own research to learn more about the preferences and needs of their listeners. It is not recommended that radio stations try to do their own research in order to try and establish the number of people that listen to them due to the cost and complexity of such research.

SAARF's aim with this document is twofold.

Firstly to provide a basic understanding of how radio audiences are estimated and secondly to provide some advice to radio stations that would like to do their own research in order to improve their offerings to their listeners.

Where station owners want to plan and conduct their own research, SAARF would also like to invite them to consult with us before finalizing their research brief.

The 7-day leave-behind and self-recording diary method (such as the RAMS® diaries) is used commonly around the world to estimate radio audiences. Many countries which do not have a television peoplemeter system also use the diary method to measure television audiences. The main difference between a diary-method and other methods (excluding peoplemeter systems), is that the diary monitors actual behaviour rather than recall of past behaviour.

Respondents are requested to record their listening for each station they have listened to, by quarter hour. Because respondents have to fill in the diary themselves, it is essential that diary-keepers should be literate. Not withstanding the relatively high incidence of illiteracy, particularly in rural areas of South Africa, the use of diaries is a very effective way of gathering the required information. The lack of literacy can be overcome by using a literate household member, a neighbour, a friend or a teacher to assist the diary respondent in completing the diary.

Appendix A shows examples of RAMS® diary pages.

As mentioned earlier, the diary does not rely on recall of past behaviour. Recall errors and the effect of memory decay are therefore reduced.

Because respondents provide information for a seven-day period, weekly cumulative audiences and weekly reach and frequency can be calculated.

Separate and comparable information is available for each day of the week, i.e. Monday, Tuesday, through to Sunday.

Since the first SAARF RAMS diaries were introduced in 1976, the same respondents that are selected for the SAARF All Media and Products Survey (AMPS) interview were also used to fill in a diary. This synergy significantly reduces the combined cost of AMPS and RAMS.

From 2004, SAARF has extended this synergy by using all adults in the selected household in large urban areas*, and not only the AMPS respondent. This procedure is referred to as household ‘flooding’ and is based on the fact that in most large urban households there is a radio for almost if not all adult members. The large incidence of radios reduces the possible effect of ‘communal’ listening that can bias the results to unacceptable levels.

By introducing flooding, the large urban sample has been more than doubled which makes it possible to report on more stations and to analyze the data in more detail. SAARF will in the near future investigate whether flooding can be extended to small urban and rural areas as well.

The research relies on the cooperation of respondents to enter their listening correctly and promptly. However, in practice it is known that late entries and forgetting to enter data may occur. Nevertheless, because the respondent is aware that he/she has to record the time and station, the impact is minimal.

To reduce the impact of atypical events on audience levels, it is advisable to balance the fieldwork across a number of weeks. The RAMS® diaries usually cover at least six-weeks, and from 2004 onwards, the six fieldwork waves span the entire year, excluding only a part of the July and December/January school holidays.

From 2008, fieldwork for the first half of the year will commence mid-January and will end mid June, and for the second half it will take place from mid-July to mid-December.

*Cities and Towns with a total population of 40 000+

Telephone research is an acceptable method for obtaining radio audience information, but it has certain limitations. Next to diaries, it is the most commonly used method in countries where there is a very high penetration of landlines. In South Africa however, the penetration of landline telephones in private households is low and thus it cannot be used to represent the entire population.

Cellular phone penetration has passed the 50% mark in 2006 and might be a proposition for the future. However, as the different cellular networks do not have a regional code in the number, it is not possible to stratify area-wise which is important for radio with its many regional/local stations.

Telephone interviewing relies on recall and it is not advisable to expect from the respondent accurate recall for more than one day (‘yesterday'). Experience has shown that respondents tend to rather recall habitual than actual behaviour. It is also difficult to get 15 minute data as accurately with telephone interviewing, as with a diary.

It is cheaper than personal interviewing. However, because of the limitation that recall is not advisable for a seven day period, surveys which use telephone interviewing should use balanced samples for each day of the week. Consequently, seven interviews are required to obtain seven-day information that can be obtained with one diary and to obtain an effective sample comparable to a diary sample, the sample must thus be 7-times as large as the diary sample.

A telephone survey can be completed in a relatively short time. However, to reduce the impact of atypical events, interviewing should be spread across a number of weeks to obtain an average figure as opposed to a one week only estimate.

The reliance on telephone penetration has already been pointed out, as well as the larger sample requirements. It is also recommended that the duration of telephone interviews should not exceed 15 minutes.

The lack of the opportunity to use prompt material is an important factor to keep in mind when telephone interviewing is done. Together with the reliance on recall, the researcher is obliged to rely on unprompted recall or to read out all the possible stations. In certain areas it would be almost impossible because of the large number of stations. Prompted recall has proved to be the more reliable method.

This research method entails mailing questionnaires to a sample of ‘potential' respondents. It is relatively inexpensive, assuming a sufficient response rate is obtained.

Possible interviewer biases do not exist.

The geographic distribution of the sample does not affect the cost. Mail surveys can reach a geographically dispersed sample at the same cost that would apply to a smaller area.

As has been mentioned already, mail surveys are an inexpensive way to collect data.

The universe is limited to respondents with a reasonable degree of literacy.

The most important shortcoming of mail surveys is a low response rate. Furthermore, it is usually almost impossible to determine the representativeness of the response because of possible differential response rates, even if information about the universe is available. There is no way to determine whether respondents and non-respondents are similar.

Because the questionnaire is the only means of communication, misunderstandings can easily occur. The physical appearance of the questionnaire, its format, layout and the wording of the questions are extremely important.

One is reliant on the efficiency of the postal service and there are a number of areas with no or only a rudimentary postal service.

In most of the queries which SAARF receives from radio stations regarding their audience levels, reference is made to the number of listeners taking part in their competitions, the number of telephone calls or letters received from listeners, or the number of people who made financial or other contributions.

All these indicators are based on self-selected samples and cannot be grossed up to the universe or generalized. Such samples are statistically known as non-probability samples and conclusions can only be made for that sample. For instance, it is valid to conclude that people who entered a competition were listening when the competition was announced. Whether they were listening at other times and on other days cannot be deduced from the fact that they have entered the competition. The same applies to people who phoned in or wrote to the station.

Because of the invalidity of such sources as the above to estimate audience sizes, this problem is discussed at almost every international media audience research conference. Even for more qualitative purposes such as views expressed regarding the quality or liking of programmes, the results cannot be generalized. In other words, it is the views of those listeners that contacted the station only and cannot be generalized to include other listeners. At best, letters, phone calls and competitions can be used to assist in the design of research.

Another source of concern is that audience estimates are sometimes based on unproven, unrelated or unclear assumptions. One such example is to obtain information about the population size, then assume that a certain percentage would listen to a station.

Surveys such as the SAARF RAMS® survey need large and representative samples, and are very expensive to carry out. However, it is necessary to quantify your audience in numbers as it is important for the buyers of advertising. Quantifying your audience is important, but is just one element to determine the attractiveness of your station. Listeners are normally tuning into a station because they like it, not only because it is a popular station.

SAARF would like to suggest to radio station owners to, not only focus on the size of the audience, but also on the profile and quality. Ask yourself whether you would like to reach businessmen, housewives, students, etc.

Also inform yourselves on how to learn more about your audiences in a more cost effective way, for instance by using focus groups.

Furthermore, from the enquiries SAARF receives from many radio stations, it is evident that the concept of ‘margin of error’ which is a reality of all sample surveys (such as RAMS) is not taken into account when comparing audiences.

For any research for which a sample is used to estimate certain aspects of the population, it is essential that the universe which is researched be defined and described. Before this step has been executed, it is impossible to design a sample which represents that population.

Many sources of information on the South African population exist. The most detailed source is the latest Population Census of Statistics South Africa (StatsSA). However, population censuses in South Africa are not conducted every year, and normally take place only every five to 10 years. Furthermore, it takes at least two years after the census to release the first top line results. Because of population growth, deaths and migration, the information becomes outdated quickly.

Institutions such as the Development Bank of Southern Africa (DBSA), the Human Sciences Research Council (HSRC), the Institute for Future Research (University of Stellenbosch), the Bureau of Market Research (BMR of Unisa), market research agencies, and many others regularly update population estimates by using mortality, fertility, and migration trends as well as changes in the structure of the population. Some of them also correct for the impact of HIV/AIDS. The BMR, for instance, annually publishes a report entitled: "Population Estimates for the RSA by Magisterial District", which provides demographic information for each district. All AMPS surveys use the BMR population data for universe purposes.

It is recommended that the different available sources of estimates of the population be investigated, and the best one be selected to obtain details for a specific target market. Such information would make it possible to not only define the population which forms the target market, but also describe them by means of demographic and geographic characteristics. Such information will make it possible to design a sample with high precision to the population.

Apart from the size of the sample, the way in which it is designed is extremely important. In this regard, it is important that a reliable and credible source or sources of population information be used to design the sample. When detailed information is available on the universe or population that forms the target market, it is possible to design a sample which can be grossed-up to estimate the listenership of the defined population in total and to a specific station(s).

There are a variety of standard sampling methods available which can be used for this purpose. In statistical terms they are referred to as probability samples. A probability sample implies that each person in the universe should have a fixed probability, which can also be calculated, to be included in the sample.

Other techniques, commonly referred to as non-probability sample designs, should be avoided when the aim of the research is to estimate, or quantify the audience. Quota sampling is one such a method that cannot be grossed up to reflect the entire population. Such samples only reflect the characteristics of the sample that was used.

The following probability sampling methods can be considered, either separately or in tandem.

A random sample is basically a sample which is selected by chance. The principle involved is the same as when competition entries are placed in a container and winners blindly drawn.

Statistical handbooks or computer programmes can be used to generate random numbers. If a sample of 1 000 has to be drawn from a universe of 10 000, then 1 000 numbers which fall between 1 and 10 000 are randomly drawn after each unit in the population has been numbered. The units which each of these numbers represent are then identified and they form the sample.

Although this method is statistically regarded as a probability sampling technique, it does not guarantee perfect representativeness, in particular when there is lots of variation in the population. The representativeness of the sample can be improved by using stratification or systematic sampling, which is described below.

If it is known (or expected) that listening levels will or may be different among different sub-populations, for instance in different towns, cities, suburbs, or for different demographic sub-groups, e.g. males and females or different age groups, then the incidence of such variables can be controlled to coincide with their incidence in the population. For example, if the geographical distribution of the target market of a city/town is known, the sample can be designed to represent these suburbs proportionately. Or, if 40% of the population is in the age group 16-24 years, the sample can be designed in such a way that 40% of the sample also falls in this group. This procedure is known as stratification.

More than one variable can be used simultaneously or interlaced to stratify the sample, in which case it is referred to as multistage-stratification, such as in the fictitious example below.

In the above example that covers four suburbs, 10% of the universe lives in Suburb A and is in the age group 16-24. When stratification by suburb and age is used, 10% of the sample will also be 16-24 years old and live in Suburb A, and so on. More variables can be added to the above matrix, in which case the number of cells will increase. The number of cells is determined by the product of the number of categories which is used for the individual variables. In the above example, 4 suburbs and 4 age groups are used and provide a matrix with 4 x 4 = 16 cells. Note that there are certain statistical minimum requirements such as preferably you must have 20 (but not less than 10) respondents in each cell, while the ratio between the smallest and largest cell should not exceed 2:1. In other words, if the smallest cell has 10 respondents, than the largest one should not have more than 20.

Systematic sampling is another way to ensure that the sample is spread evenly across the entire population, and not biased towards certain sub-populations and under-representing others.

If a systematic sample of 1 000 has to be drawn from a universe of 10 000, the following procedure will be followed:

Determine the sampling interval:

If 1 000 numbers have to be drawn from 10 000, every 10th number (universe divided by the sample, in this case 10 000 ÷ 1 000 =10) has to be used to ensure that the sample is spread evenly/systematically between 1 and 10 000. The sampling interval in this case is 10.

Choose a random starting point:

For the above example, the sampling interval is 10, which means that every 10th number must be selected, starting from a random starting point from 1 to 10. This point is chosen as is described under random sampling (throw the numbers 1 to 10 in a box and draw one).

Selecting the sampling points:

Say that 7 is selected as the starting point, then numbers 7, 17, 27, 37 .through to 9 997 will be used, resulting in 1 000 sampling points, the intended sample.

In formal areas the Nielsen Geoframe is used to select the addresses to be included. All addresses in urban areas (total population 500+) in the universe are included in this computerized geographic information system (GIS). From this source it is possible to identify the required addresses (in our example those that correspond to the above numbers 7, 17, etc).

In rural areas with a population of less than 500 people, including the dispersed farming population, the sampling points are selected by using maps obtained from the Surveyor General’s office in Pretoria. The coordinates (North/South and East/West) of each sampling point are then provided to the interviewers as well as an electronic Global Positioning System (GPS) device that is used to guide them to the specific point. Strict instructions are given on how to select an address closest to each point. GPS technology is also used in squatter camps in urban areas where no identifiable physical addresses are available.

Cluster sampling is usually used for economic reasons. If any of the previous three methods are used alone, particularly if a large geographic area has to be covered, the sampling points will be spread individually across the entire area which would increase the cost. Cluster sampling can be used in such cases to reduce the cost of travel and accommodation.

Cluster sampling implies that fewer than the required points be selected and that more than one address is selected in the vicinity of each point. Such points are referred to as clusters.

However, it should be remembered that cluster sampling decreases the precision of the sample to the universe.

When it is important to obtain a large enough sample for separate analysis of one or more small sub-populations, for instance to report separately for a community radio station with a relatively small footprint area, that area can be over-sampled.

Before reporting the results, such over-sampling should be down-weighted to reflect the correct proportion in the total population. To retain statistical validity, the level of over-sampling should not exceed a ratio of 2:1, as was also mentioned under stratified sampling.

There is a general misconception that the size of the sample is determined by the size of the universe and that large populations can only be researched by using large samples.

Statistically, there is no direct relationship between the size of the universe and the size of the sample required to estimate certain aspects of that universe accurately.

The size of the sample is determined by the following factors:

· The number of factors that can cause variation in the results. If it is, for instance, expected that everybody in the population will respond more or less the same, a small sample will accurately estimate this response. However, if it is expected that males and females will respond differently, a larger sample is required. If it is expected that males and females as well as people of different ages will behave differently, an even larger sample will be required.

· The level of detail to which the results will be reported. If the aim of the survey is only to report the behaviour of the total population, it can be done relatively accurately by using a small sample. If, however, it is important to report details of certain sub-populations separately, e.g. geographic regions, demographic sub-groups such as gender and age, a much larger sample is required.

· The level of accuracy of the results which is required. Because there is an inversely proportional correlation between the size of the sample and the accuracy of the results, a large sample should provide more accurate results than a smaller one.

Given the above, the following minimum requirements are usually set:

· Each weighting cell should preferably contain at least 20 respondents.

· The ratio of weights should not be more than 2:1 if disproportionate sampling is used.

· Each reporting cell should have at least 40 respondents that claimed positively to the question, in the case of radio audience estimates, at least 40 listeners.

For a variety of reasons, it always happens that not all the initially selected respondents will form part of the final sample. Some respondents will refuse to participate, whilst others might be difficult to contact. To compensate for this and to ensure that the final sample size and structure will be the same as the selected sample, substitution can be used. However, if the level of substitution is high and if it is not controlled properly, it can bias the results. The following requirements are usually set:

· Substitutes must be selected by using a probability sampling technique, similar to the procedures which were used to select the initial respondents.

· Substitution should only be allowed when it is absolutely certain that the initially selected respondent cannot be included. This implies that every attempt should be made to include persons who are difficult to contact. For SAARF surveys, the original visit plus three call-backs on different days of the week and at different times of the day are required before substitution is allowed.

· When reporting the results, the level of substitution should be provided and, if it is high, the possible effect on the results should be indicated.

Finally, it is recommended that a statistician be consulted.

A questionnaire which is used to collect valid information is more than just a list of questions. Therefore, it is important that attention be given to not only the formulation of every question, but also to how they are arranged to ensure a logical, simple, understandable and unbiased interview. Furthermore, it is important that the questionnaire be tested and improved using a mini-sample before it is used in the final survey. The following guidelines can be used:

· Use the language of the target group. This does not only imply that the interview should be conducted in the respondent's language of preference, but also that the level of the language should be simple and easily understandable. Researchers frequently tend to communicate using marketing language rather than common language.

· Keep the questions - and the questionnaire - as short as possible. Avoid asking ‘nice to know' questions which do not really contribute to the aim of the survey.

· Bias through ‘leading' questions must be avoided. Even a simple statement such as "I am doing this research on behalf of ..... (name of a radio station).." can bias the results.

· Care should be taken to avoid general research problems such as over-claiming on certain questions, under-claiming on others, the probability of a rotation effect, and many others. Consultation with experienced researchers in media audience research will help to reduce such possible biases.

Data collection is the most crucial aspect of all research, because mistakes which are made when collecting the information, very often cannot be corrected afterwards. Therefore, it is important that:

1. Interviewers be properly selected during recruitment to ensure that they have the abilities which are required to do high quality work;

2. All selected interviewers should be trained properly in the basics of scientific data collecting;

3. Interviewers should be briefed in the application of every specific questionnaire, and pilot interviews should be done before they commence with the real interviews;

4. Strict control measures should be applied to ensure that respondent errors, interviewer mistakes, misunderstanding of the questions and situation errors (for example the telephone or door bell rings, food that is burning, a baby that is crying, etc.) are limited.

5. To ensure a high level of accuracy of the results, a minimum of 10% of all interviews are usually checked back. During the back-checking, both the selection of the sampling point (where applicable correct substitution) and of the correct respondent must be checked, as well as that the information in the questionnaire has been recorded accurately. The check-backs should include the work of all interviewers.

5.6.1 Data editing

In addition to controlling fieldwork standards and back-checking as outlined in paragraph 4.4 above, manual and computerized editing should also be done to ‘clean’ the results. For this purpose, as many as possible logic checks are used on the raw unweighted data. Some examples follow:

· If there is no cell phone in your home, you are not suppose to claim to own a cell phone;

· If there is no water in your home or on your plot, you are not suppose to have a flush toilet;

· If you don’t have electricity, you cannot claim having a microwave oven or other electric appliances;

· A male is not supposed to use sanitary protection.

If you run through all the questions in your survey and evaluate them critically to determine impossibilities, you will be astonished to see how many similar cases than in the above examples you will find.

The final check normally is to make sure that the total of all the response options add up to the total sample, or if there was not an option for ‘don’t know/unsure, the responses can be lower than the total sample size, within acceptable margins.

5.6.2 Weighting of the data

It was stated in Paragraph 4.2.2 that ideally the sample must be designed in such a way that it reflects the characteristics of the population. In practice, even if this principle is applied, due to refusals, substitution and other factors the realized sample will not be the same as the selected sample. Therefore, weighting has to be applied to correct for any deviations from the characteristics of the population. This also applies when over-sampling is used in which case the results will have to be down-weighted to the correct proportions in the population.

The current SAARF RAMS® survey is post weighted by using the so-called cell weighting method. The simplified grid in Paragraph 4.2.2 using 4 suburbs and 4 age breaks demonstrates the principle of cell weighting.

RAMS is currently weighted by the following variables, all interlaced (the number of categories for each variable are shown between brackets:

Province, all nine (9)

Community size, metro; city/large town; small town/village; rural (4)

Gender, male, Female (2)

Age, 16-24; 25-34; 35-49; 50+ (4)

It was also mentioned in Paragraph 5.2.2 that the total number of cells in your grid is the product of the number of categories to be controlled. In the above case:

9 provinces x 4 community sizes x 2 genders x 4 age breaks = 288

(In reality it is a few more as some provinces has more than one metro – Gauteng has the most namely three i.e. Pretoria; Johannesburg/Rand and Vaal).

Similarly to how the sample ratios were determined in Paragraph 4.2 the weighting ratios are determined. It entails that the population in a cell be divided by the number of respondents in that cell to determine the weight that each respondent in that cell will receive.

Example (Metro: Johannesburg in Gauteng, male, 16-24)

The above example namely 16-24 year old males in Johannesburg in Gauteng is one of the cells. Take the number of 16-24 year old males in Johannesburg and divide that by the number of respondents in the same cell. The answer gives the weight that will be allocated to every male respondent 16-24 in Johannesburg.

As indicated in Paragraph 4.2.2, each cell must have preferably 20 but not less than 10 respondents, while the ratio of the largest to the smallest weight should not exceed 2:1. This means that the more cells are used the larger the required sample, which is one of the important limitations of cell weighting.

For more sophisticated weighting procedures such as the reiterative method (RIM) weighting, the above is not a complete limitation. Variables are separated into so-called RIMs and isolated from other variables, and weighted separately after a number of independent iterations all variables are either balanced or closely balanced. However, more than one variable can be included in a RIM, e.g. age and gender. Consequently, RIM weighting is a combination of interlaced and independent variables.

RIM weighting allows for the inclusion of more variables (such as LSMs) which are not included in the current RAMS® weighting matrix.

SAARF already implemented this procedure in SAARF TAMS® and possible implementation in RAMS® is under investigation.

The following audience measures are used in the RAMS® diary reports:

The average ¼-hour audience is an arithmetical average (an ordinary average) across more than one ¼-hour. It is calculated by adding-up the audiences of the quarter hours to be reflected, and dividing by the number of quarter hours for which the numbers were added. This measure is usually used to estimate advertising channel audiences (e.g. for 30 min, an hour, etc time slots) which can be used in determining advertising rates for different times of the day and days of the week. This figure is also used to estimate the potential audience which would be reached if an advertisement is placed in that time slot.

The net audience reflects the number of different people who listened during a specified time period. In the advertising industry this is referred to as the ‘reach' or ‘coverage'. To calculate the net reach, persons who listened during two or more quarter hours during the time under consideration, are counted only once. The net audience is, thus, an unduplicated audience

The gross audience of a channel or programme is the sum of the relevant quarter hour audiences, irrespective of duplication of persons. The same person is counted once for each quarter hour that he/she listened to during the channel or programme. If this figure is divided by the net audience, the average duration of listening is obtained.

When audiences are calculated across more than one day, for instance Monday to Friday, it can either be done by calculating the arithmetical average, or by calculating a cumulative audience. The cumulative audience is the net audience of the first day in the calculation, plus new listeners on the other days. It is, in other words, the net or unduplicated audience across more than one day.

The above audience measures are related. For instance, if there is no flow of audience during a time-slot, in other words if all persons who listened at the beginning still listen at the end, and no new listeners enter, the average ¼-hour audience and the net audience will be the same. If the net audience is twice as large as the average ¼-hour figure, then the average listener has listened for only half of the total time.

When audience estimates are quoted, it is essential that the measure used also be mentioned. The average Monday to Friday and Cumulative Monday to Friday audiences usually differ. Similarly, the average daily audience will differ from the net daily audiences; the average 7-day and cumulative 7-day audiences will differ, etc. Without knowing which measure is referred to, it is impossible to correctly interpret the data.

The main aim of media planning basically is to select those stations which reach as many of a specific target market as possible a given number of times (called the frequency) in a certain time period (e.g. seven days). Research which does not provide a reach and frequency estimate will be of little value for buying and selling advertising time.

When a seven-day diary is used, the daily reach can be calculated for every single day (or quarter hour or combination of quarter hours in that day), and for any combination of days (or quarter hours or combination of quarter hours within the day or days) up to seven days. The frequency is the number of days on which a person listened at a given time/times. This information is also used to calculate how many people you will reach with a campaign on any given number of days and a selection of quarter hours on each day, as well as what the average frequency will be.

The gross rating points or GRPs are the total number of opportunities to hear (OTS) or potential exposures created by a campaign. This can be calculated by multiplying reach and frequency.

When telephone interviewing is done and recall of only ‘yesterday' listening is used, the frequency of listening across more than one day cannot be calculated.

All research for which samples are used to estimate the behaviour, attitudes, etc., of the population is subject to sampling (or statistical) errors. If probability samples such as the samples which are described in Paragraph 4.2 are used, the size (or margin) of the error can be calculated. The margin of error can be calculated for different levels of accuracy, but in most research, including SAARF RAMS®, the 95% confidence level is used. If the margin of error is calculated at the 95% confidence level, it means that if 100 similar samples are used, the error for 95 of them would be within the relevant margin, whilst 5 could fall outside this figure.

Two variables determine the size of the margin of error, namely the size of the sample and the degree of unanimity of the response. The latter refers to the ratio of the proportion of the sample who responded positively (in this instance the listeners) and those who responded negatively (non-listeners).

The formula for calculating the error is:

s = √ p x (100-p) x 1.96

n

Where:

s = Standard Error

p = Penetration (% who listened)

n = Sample Size

As in many other countries, the South African Market Research Industry strives for a high standard of research, as well as to protect the interests of the different stake-holders. Most of the leading researchers are members of the Southern African Market Research Association (SAMRA). SAMRA is a professional association and has a code of conduct, to which its members subscribe.

The stakeholders are the general public who provide the information, the client who pays for it, and the researcher.

Furthermore, there is an umbrella body to which many of the large research providers belong. The Association of Market and Social Research Organisation (AMSRO).

Individual researchers who are members of SAMRA and research providers who are members of AMSRO are obliged to the best of their ability, to ensure that the research practitioner(s) with whom they are associated and the people conducting research on their behalf adhere to this Code of Conduct. More information on SAMRA can be obtained from them at:

P O Box 1713

RANDBURG

2125

Tel: (011) 886 3771

Fax: (011) 886 9721

The South African Advertising Research Foundation was founded in 1974 as a non-profit industry body. SAARF was formed because of a need in the marketing and advertising communities for a comprehensive, unbiased, reliable, regular and technically excellent media audience and products survey. Its purpose is to provide information about the population's use of the media, products, services and brands as well as their characteristics and demographic composition so as to enable reliable targeting for advertising purposes.

The data is in such a format that it is used, among others, for the buying and selling of advertising time and space in the media and for strategic editorial and programme planning.

Over the years, the SAARF All Media and Products Survey (SAARF AMPS®), the SAARF Radio Audience Measurements Survey (SAARF RAMS®) and the SAARF Television Audience Measurement Survey (SAARF TAMS®) have established themselves as reliable, valid and credible research vehicles.

Apart from commissioning the above surveys, SAARF® also assists media owners, advertisers and advertising agencies in a series of other areas such as offering training courses and the development of segmentation instruments such as the SAARF Universal Living Standards Measure (SAARF SU-LSM®).

SAARF's mission is to serve its members, and other interested persons and people are invited to liaise with SAARF about any aspect relating to media audiences, products, services and brands as well as target marketing and segmentation tools.

a. AMPS Diary Technical Report, South African Advertising Research Foundation (SAARF, Johannesburg, 1994).

b. RAMS Diary Technical Report, South African Advertising Research Foundation (SAARF, Johannesburg, 2007).

c. Guidelines for Market Research, Advertising Research Foundation (ARF), New York, (August 2003).

d. SAMRA Yearbook, Southern African Market Research Association, Johannesburg, 2006.

Please check with saarf@saarf.co.za as most of the above publications can be consulted in the SAARF Library.

Examples of RAMS® diary page