Survey Quota Controls

Quota Controls (or quota management as it is sometimes called) in online surveys allow the survey programmer to control the number of respondents who complete the survey by specified demographics and other criteria.
Control Gender to be Nationally Representative
A common example of quota controls in online surveys is limiting the number of interviews to be completed by gender. In a nationally representative survey of the UK, we would expect to receive approximately 48% Males and 52% Female (this is the proportion of of each gender in the national population). So in a survey of 100 people, if the sample fell out naturally we would expect to get 48 Men and 52 Women in the sample of 100 completes. Often panel samples are adjusted automatically to get the correct level of distribution. Online Panel Access ensures that the correct distribution of samples are invited to a survey, assuming a sample of 200 or more but the actual completes may not be exactly representative of the population. To ensure we definitely receive the exact number of completes by gender, we should set quota controls.
Control Gender Disproportionately
In other cases, we may want to adjust gender quota controls to be disproportionately higher for a particular gender. For example, a producer of salad leaves may want to survey potential customers. It knows that a higher proportion of women make the purchasing decision in weekly supermarket shopping and it is particularly interested in the views of Waitrose shoppers, because they are more likely to pay for premium salad products. The quota for women coud be set to 70% for example, and we could also control the number of Waitrose shoppers at say 20% (compared with its overall market share of perhaps 5%) by setting a quota from a question on the respondent's preferred supermarket for the weekly shop. We could also target Waitrose shoppers in a sample selection from the online research panel we are using.
Independent Quotas
Many online surveys of nationally representative populations use Independent Quota Controls. Each quota is controlled independently e.g. setting a control of 100 completes in 18-34 age bracket ensures a maximum of 100 completes in this age group. However, it does not ensure that the split between gender within the age group is correct. In all likelihood the gender split within the age group will be close to the natonal distribution (assuming the panel provider has responsive and representative panel membership), but it is not likely to be exact. If we have a series of independent quotas on age, gender and region, each quota individually can be set to be representative of the quota criteria individually.

The main advantages of independent quotas is that they are simple to set up, and more importantly, quicker, cheaper and faster to fill when respondents answer the survey. The disadvantage is that it is likely that the sample will not be representative of criteria within the quotas (e.g. representative of age and region within gender).
Interlocking Quotas
The key difference with an interlocking quota is that it enables full control over the sample by more than one quota control simultaneously. For example, age and gender together. That means controlling the sample of 25-49 year olds, for example, by gender as well as age so that the proportion of men and women within this age demographic reflect the true proportion of men and women by age group in the population.

The main advantage of interlocking quotas is that it is the only way to guarantee sample properly reflects the real population distribution. But there are important disadvantages, which are the opposite of Independent Quotas. They take longer to calculate and to program (all quota set ups require manual set up) and more significantly, will increase the fieldwork times (and possibly the cost) to fulfill the required sample responses.
What type of Quota Control is best?
Technically, Interlocking Quotas deliver the most representative samples. But from a practical sense, Independent Quotas are easier to use and more cost effective. First, it takes less time to calculate and set up Independent Quotas. Second, the time to fill Independent Quotas is much shorter than Interlocking Quotas. Although panel sample in developed digital economies, like the UK, are large and representative, there are still limitations. Setting Independent Quotas for age, gender and region, will always be easier to fill than Interlocking Quotas, especially when you consider some UK regions and countries have much smaller panels (e.g. Wales, Northern Ireland and Scotland). Our recommendation is that in many instances, Independent Quotas are simpler and fit for purpose for many, if not most surveys. 

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