Why surveys?

Our Surveys 101 series is fundamentally about the science of survey research as it has developed over the past century.

Its primary focus is to get you up to speed on the latest opinions of academics and practitioners about survey methodology best practices in questionnaire design, data analysis and, more recently, data visualising.

Whether you’re looking to find out how many friends will turn up for a dinner party, what your customers think about your latest product offering or how people will vote in the next election, surveys are often the best – and often also the only reliable way – to discover what people think and want.

People also conduct surveys out of a desire for ‘social comparison’, which drives us to learn about others, and surveys are the best way to get this information. After all, context is king.

There are at least four main reasons why people conduct surveys. We say “at least” because with more than 17 million customers, the SurveyMonkey platform is making ever-more-exciting uses of surveys possible.

Related reading: Survey vs. questionnaire: Key differences and use cases

In the news, surveys are used to elevate stories beyond the few people who may get quoted in an article. Stories have far more power if we know they reflect something that’s happening to a significant proportion of people rather than just a handful.

Similarly, in customer service surveys, you should know whether an angry customer is expressing a unique or common complaint. Also, just because a startup has one happy customer, this doesn’t mean that it’s on its way to a huge initial public offering (IPO). Surveys can help gauge the representativeness of individual views and experiences.

When done well, surveys provide hard numbers about people’s opinions and behaviours that can be used to make important decisions. Just as aspiring politicians are certainly more apt to win an election if they understand what voters really want, the manager of a grassroots football club is more likely to succeed if they are able to identify problems in a training programme by surveying coaches and parents.

Surveys are regularly used to make individual decisions, such as whether to run a particular advertising campaign or create a new service, but they become even more powerful when repeated over time.

There’s a common saying among survey researchers: “Trend is your friend.” After all, repeatedly asking the same question at different points in time gives a clear vantage point on how things are changing.

The UK census, which is a survey itself (albeit a massive one), is particularly powerful at cataloguing the major demographic changes in the country, such as the ethnic makeup of the UK. Although a company’s NPS score may not be particularly meaningful in isolation, a major dip in its score in the second quarter would justifiably send its executives scrambling for an explanation and a fix.

Related reading: The risks and disadvantages of data silos

‘Big data’ is currently all the rage. But there are also big limits. The term largely refers to implicit data, or data that are derived from observing and analysing your and others’ behaviour both online and elsewhere.

There is an ever-increasing amount of these data – and yes, ‘data’ are plural – but there are some flaws. Consider for a moment the Amazon recommendation engine. Since it can’t distinguish between whether Eileen, a grandmother, added the latest EA Sports FC video game to her Amazon basket for herself or as a birthday gift for her grandson, it pollutes her recommendations with video games such as EA Sports F1 25 and NBA 2K25.

To discover why Eileen added the EA Sports FC video game to her Amazon basket, explicit data is needed to complement what Amazon’s algorithms reveal. Explicit data is just that: information that’s fully revealed or expressed without vagueness or ambiguity.

Explicit data are insights that are taken directly from the individual, generally using survey methodology. They are inherently more reliable when it comes to understanding the motivations behind actions. If Amazon were to collect some explicit data by asking the simple question “Are you buying this product as a gift?”, they could avoid providing unhelpful recommendations for their customers.

The importance of surveys is perhaps best demonstrated by a book that’s not about surveys. In his classic book ‘Exit, Voice, and Loyalty’, Albert Hirschman, an economist at Princeton University in the US, examined the main ways people react when facing a poorly performing organisation: they can either “exit” and take their business elsewhere or “voice” their concerns and try to change things from within. How loyal people are to a cause or a company affects whether they choose to vote with their feet and exit or voice their opinions and speak up.

Hirschman points out that, in general, people and businesses rely on exit to identify an issue. For example, do we have fewer customers than last month? But by the time you see this, it may be too late. Exit is a lagging indicator.

Organisations of all types succeed when encouraging voice rather exit. Engaging your customers to voice their concerns helps with engagement and decreases the likelihood that they will decide to spend their time or money elsewhere.

In other words, voice is your canary in a coal mine.

So let’s get surveying to gather hard numbers, benchmarks, uncover the why and give our respondents a voice.

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