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Response rates are among the hottest topics in the research industry. Panel research, in particular, is directly confronted with the effects of declining response rates. In the Netherlands, one of the hardest groups to get co-operation from is young people. This paper focusses on attempts to raise response rates of diary research among groups aged 18 - 29 years. It presents results of a number of tests performed in the Dutch radio diary panel. This paper analyses the relevant factors influencing response rates and the effect of motivational calls during the fieldwork period, reminder cards, and specific incentives. The possibilities of an interesting innovation, the e-Diary, are discussed.
This paper describes the results of a parallel test of two methods of collecting radio tuning data with different diary designs. One diary design uses a pre-printed quarter hour approach where there is a row for each quarter hour in the day and the respondents are asked to draw a line across the quarter hour blocks when they listened. The other diary allows the respondents to write in the exact time they started and finished listening. The comparison focused on return rates, tuning and reach analysis, and a profile of the respondents between the two diary methodologies. The aim of the test was to determine whether the different diaries were better at gathering tuning information or elicited a better response.
This paper discusses the method developed by Nielsen Media Research to gather out-of-home television viewing for children in daycare, school and other situations. Utilizing a personal diary data collection tool, information was gathered from families with children about their viewing both at home and away from home. In addition, viewing was collected directly from the out-of-home child-care providers for those same families in order to provide a validation for the out-of-home viewing ported by the children. The paper explores the extent to which children view TV in out-of-home locations that are not residences.
The number and success of radio stations are strongly linked to station format. Listener demographics are linked to the station formats. Thus, separating the effect of station format from listener demographics is difficult. The bigger formats are âcountryâ, âoldiesâ, and ânews/talkâ in terms of both number of stations and total audience. Stations with formats that attract certain listening groups (such as âadult contemporaryâ and âoldiesâ) tend to have a high ratio of revenue to audience. Stations that include the station name in their format tend to be the more successful stations in terms of size of audience and revenue. Although many stations include their format as part of the station name, and format has a strong influence on the success of a station, very few listeners write station format in their diary entries. One could conjecture from the data that the station format attracts its listeners, but the listeners rarely identify the station by format.
This paper reports on an investigation of the relative performance of one, two and four week diaries for radio audience measurement. A special four week diary study carried out in 1992 by Research Services Limited for RAJAR has been re-analysed to evaluate the trade-offs between respondent fatigue, the performance of the extended reach model, sample efficiency and relative cost.
RAJAR, the new joint industry measurement system for UK radio, was launched in 1993. As in the past, the RAJAR survey uses a one-week self-completion diary and a model is required to estimate station or schedule reach beyond seven days. Changes in the radio market have led to changes in listening habits and a consequent need to update the extended reach model. The new model is probability based and has been validated using a one-off four week diary study. The published station reach build curves are used by several bureaux as a basis for providing the advertising industry with a practical system for schedule reach and frequency analysis. Two bureaux - IMS and Telmar - collaborated to ensure consistency in their approach to the estimation of schedule reach. However, each system offers several ways in which the base data can be used, essentially depending upon whether a schedule is being planned in broad time segments or using exact spots. These permutations are seen to generate greater inconsistencies in estimates of frequency rather than reach. Without an understanding of how each bureaux system will interpret an analysis specification, buyers and sellers of airtime could well be negotiating with inconsistent and misleading reach and frequency results.
Every researcher is asked the question: how big should the sample be? And every researcher has the same standard buck-passing answer: it depends on how accurately you want to measure what you measure. But given the amount of money that is traded on ratings numbers, it is important for the user to know what's real and what's statistical bounce in the surveys and therefore what the size of the sample should be to reduce this bounce to acceptable levels. The trouble is that the simple textbook formula we all know Vpq/n doesn't apply to the complex sample design and estimation procedures generally used in radio rating surveys. But techniques are available to estimate sampling errors empirically. BBM studies using such techniques show that there are two main influences on the size of sampling error and that they pull in different directions. The use of more than one respondent per household common in diary surveys tends to increase sampling error, and to increase it more, the wider the demographic. The use of average quarter-hour estimates tends to decrease the sampling error, and to decrease it more, the longer the time block being averaged. Generally, the latter effect dominates the former, meaning that the rating estimates are more reliable than the user might perhaps think. The details of sample design do matter too i. e. things like stratification, estimation procedures and particularly, the weighting scheme. We provide a case study of how attention to small technical details can pay off in increased precision just as much as an explicit increase in sample size: technique is as important as size.