7 MIN READ

Surveys - The Life-Blood of Quantitative Insights?

Emily James

Are Your Stakeholders Asking the Right Questions?

“Tell me something I don’t know”

8 MIN READ

Emily James

There is a reason why surveys come to mind whenever anyone mentions market research. Surveys are the staple of the insights industry, for insight professionals, stakeholders and customers, even before focus groups. But it is becoming increasingly clear that ‘surveys’ have become synonymous with ‘quantitative research’. While there are a select few other tools out there, most of the more developed and used methodologies include using surveys, and thus, surveys have become the life-blood of quantitative insights.

As with any customer-facing aspect, sometimes the most anyone (consumers, stakeholders, and even some insight professionals) outside of the industry sees of market research is a survey. If there are any more research methods recalled by the masses, it would probably be a focus group, but that’s always an option at the end of a survey to get more in-depth insights after the initial questions have been asked.

So really, the more important question we should be asking is: what impact does this synonymity have on the current and future state of quantitative research?

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Short answer? Yes, surveys are the life-blood of quantitative insights. But what impact does this have on the future of quantitative research?

How Surveys Got So Popular

According to a number of sources, the first era of survey research as a scientific field of study was developed in the 1930s-60s with basic survey data collection components were designed, and the tools to statistically analyse the data gathered were made. However, the first documented census occurred in Babylon in 3800 BCE, where the Empire counted the quantities of livestock, butter, honey, milk, wool, and vegetables. While this is a far cry from the surveys we conduct today, the premise of learning about the lives of the public was the same.

The goal of surveys is to collect quantitative data that leads to conclusive, objective answers, so it’s no wonder why the logical nature of survey data and analysis has drawn the attention and admiration of statistical minds for decades; providing a level of certainty that can be relied upon for the most part when it comes to decision-making and insight generation. The relativity surrounding the conclusions drawn means then even of the accuracy is somewhat off, the general direction of consumer trends can be worked with to an extent until a more accurate answer appears.

Even though survey data doesn’t account for deeper reasoning behind participant answers, until the last couple of decades, there also wasn’t enough stakeholder interest in why participants acted or answered the way they did – stakeholder interests stopped at the logical answers provided by logical data that signposted the way to success.

Only now are we starting to embed qualitative and behavioural science principles into quantitative tools like surveys in order to gain more insight into the reasoning behind the surface answers. Tools like our own SurveyMR with video and qualitative capabilities are slowly innovating the industry, and proving to stakeholders to value of well-rounded insights.

Surveying the Growth of Quant

Survey research has long been an attractive method of keeping track of public life, but because of its longevity, it has become synonymous with quantitative research and almost stunted the growth of both new and existing quantitative research methods because of this association.

However, this isn’t to say that there hasn’t been any innovation in survey research. As the years have gone by and insight teams collected survey data, they realised that there were better ways to ensure they collected better survey data by shortening the surveys they sent out, sending them out at certain times of day to certain people, and more frequently to increase participant engagement. The tactics we use today in survey research have been honed after years of trial and error and are what largely make survey research successful today.

But there are still a number of limitations and weaknesses when it comes to quantitative research, and focussing on surveys is largely a reason why this has gone unrectified. If focussed on the wrong group of respondents then an accurate representation of the target population is in jeopardy, and the wrong decisions are likely to be made based on the data gathered from this incorrect sample.

When responding to a survey, sometimes the respondents aren’t creating or can't create the right environment to record the best results. For example, some surveys depend on respondents answering within a certain timeframe, or as they’re going through a certain scenario in order to get the most accurate data, but if respondents aren’t completing the survey in the required circumstances, then that data could be rendered inaccurate or even redundant.

Survey data lacks the necessary context to really provide an in-depth understanding of the participant’s experience they’re being surveyed on. NPS surveys have a text box for participants to write more detail in, but how many people actually use it if not to complain about grievances? It’s hard to get a well-rounded contextual look into the experience without asking follow up questions to find out the truth.

Statistical data analysis isn’t exactly a piece of cake either for those who don’t have much of a mathematical background. It’s a very scientific discipline that requires training and a logical mindset to complete with any degree of accuracy.

Qualitative research had the same issue for a while with focus groups becoming synonymous with qualitative research, but the association wasn’t as strong, and thus more creative qualitative research methods emerged through dedicated innovation. Off hand, there aren’t many people who can come up with non-survey based quantitative methodologies as easily as they can non-focus-group-based qualitative methodologies.

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Because of the longevity of the survey, surveys has become synonymous with quantitative research. Has this synonymity stunted the growth of the quantitative research field?

Alternative Quant Tools and Tactics

Surveys are indeed the life-blood of quantitative insights. So, while discounting the survey entirely would be hugely problematic for all insight teams, stakeholders and participants, we should now ask what other quantitative tools and methodologies are there to use alongside surveys in order to mitigate any consequences and boost the accuracy of quantitative insights?

  • Quantitative Interviews – researcher asks a fixed set of questions to every participant in a formal structured pattern to gain numerical data. Basically, an in-person survey? But with opportunities to provide more in-depth information (surveys lack context). But they’re time consuming going one on one. Any more participants and it’ll turn into a focus group.
  • Observation – this is a systematic way to collect data by observing people in natural situations or settings. Mostly used for qual data collection, this can be used to collect quant data too. Simple observations are typically numerical (how many cars pass through an intersection, etc.)
  • Quick Polls – the short single-question multiple-choice survey to gather instant insights. We are starting to see these more and more on social media platforms, using the platform of already convened public voices to comment on a wide variety of topics and trends.
  • Manipulating Existing Data – stakeholders can use governmental and NGO sources, even data warehouses in your own organisations filled with past research projects and insights to inform current and future decisions.

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