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Ever launched a survey, and wondered to yourself who might answer it? Not being sure how many responses you'll get, or how representative of your audience they'll be, isn't a great way to conduct business-critical research. Bring quality and consistency to your research with the help of quotas.
Have you ever launched a survey, and wondered who might answer it? Clearly, not being sure how many responses you might get, or how representative of your audience they will be, is not a great way to conduct business-critical research.
And if you’ve ever picked through a survey’s results only to find that 70% were students (while they make up under 3% of the population); or a disproportionate number were from a particular income bracket/gender/geography/age etc. and that it invalidates any insights you might glean from them…you’ll know just how frustrating the whole process can be.
Quotas are a vital component for gathering representative, accurate survey results from your consumer research.
Read on to discover what quotas are, how and where to use them, and how to easily set up quotas for your next research project with Attest.
Quotas are a specific number or percentage that the survey needs to meet, by screening in participants that meet the requirements. They are typically set based on demographics. For example you might want 51% female and 49% male responses. Or five age brands, with the survey made up of 20% from each.
By setting quotes you’re sure to collect just the right amount of data you need, from across the full spectrum of opinions you want.
As such, quotas allow you to have confidence in your data, that it represents the population you’re most interested in understanding.
Quotas are vital for three forms of consumer intelligence: representative research, consistent research and useful research.
Why Are Quotas Important for Representative Research?
If the goal of your survey is to gather information that can be trusted to be indicative of the views of the wider (unsurveyed) population, then the data must accurately represent each meaningful group within that population.
In this case, you don’t want to make strategic business decisions based on the views of a minority who all feel a certain way, when this viewpoint isn’t representative of the rest of the population whom you require buy-in from. You’ll want your business decisions to be based on information from across the board, so that you can successfully optimise for all expected consumers of your product or service.
Using quotas will therefore ensure the viewpoints gathered represent the whole population, giving unbiased and actionable results.
How to Use Quotas to Gather Representative Research
In order to set up quotas you’ll need to understand the makeup of your population, which can be sourced multiple ways; if the population is an objective fact (national representation of the UK, or representation of London for instance) then there is 3rd party data available online (the Office of National Statistics is a great place to look), or if the population is specific to your company, this can be sourced from current customer sales data.
You’ll need to then calculate the percentage of the audience which is made up by each demographic, ensuring the segments are mutually exclusive in order to reach 100%; one participant shouldn’t be able to screen in to two or more quotas from one quota set (for example age brackets 18-25 and 21-31), however they might be present in two or more different quota sets (e.g. aged 18-25 and female).
These percentages are then applied directly to the sample you are surveying; if your audience is 49% male and 51% female, then the sample that’s surveyed should also exhibit that split. Meaning a 1000 person survey would have 490 males and 510 females.
[If you need help selecting a statistically significant sample size, read our recent article here.]
As we’ve already established, it’s important for your survey data to represent the population surveyed so that your business decisions are optimised for the entire audience. However, it’s also important to establish quotas for the sake of consistency through research projects.
An example will show why:
You survey 1000 people in October 2017 for a brand health check, where the results show a company Net Promoter Score (NPS) of 60. In April 2018 you do a second dip with the same brand health questions, to gauge changing sentiments over the preceding 6 months. This time, your NPS returns as 30. What has your brand done to warrant such a downturn in NPS? In fact, nothing. In October the survey sample consisted of 75% females, 25% males, while in April the sample was 25% female and 75% male. The difference in NPS wasn’t caused by changes in the sentiment of your audience, but because by changes in the inherent nature of the sample.
To be able to attribute changes in survey results to actions your brand has taken, the sample which is surveyed needs to remain constant, through the use of quotas.
Sometimes your audience is narrow, only encompassing one age bracket or gender, for instance. So conducting representative research is not necessary. However other age brackets or genders aren’t totally uninteresting, they might still have insightful data to offer.
In this case, quotas can be used to skew the sample towards the audience you’re most interested in, while not totally disregarding alternative audiences whose data might be useful for points of comparison.
Setting a high quota for the population you’re most interested in will allow you to toggle results for that demographic on and off in the Attest results dashboard, giving an easy and visual comparison tool.
For example, if you were selling a feminine hygiene product, you might want 80% female and 20% male respondents, acknowledging that the primary decision maker is very likely to be female, but helping you to understand how men also might play into the decision, and view your category.
Your sample size for the main population will remain high enough for you to dive deep into their important sentiments, while you’ll still be able to recognise genuine points of differentiation from other consumers.
To make your life easier, Attest’s dashboard already has several representative quotas built and ready for use, including Nationally Representative samples for multiple countries, UK Millennials, London Millennials and London Gen Z consumers.
Setting up your own quotas, however, couldn’t be easier.
Attest can help you better understand your consumers, including the differences between sub-sectors of this audience. Adding quotas to your next consumer intelligence project is totally free of charge. Then, once the results are gathered, you can easily toggle between demographics to see shifts in attitudes and behaviour.
To be able to base your strategic business decisions on data that represents the entirety of your audience, is consistent across projects, and genuinely useful to your brand, get in touch with Attest today.
Our in-house marketing team is always scouring the market for the next big thing. This piece has been lovingly crafted by one of our team members.
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