Diving into the Sample Survey to Understand Your Target Market

A sample survey is an effective method of collecting data on a larger population and making inferences about it via a sampling of it. It helps market researchers and business owners examine their target market, no matter how immense it is, by surveying a subset that accurately reflects the whole. 

An essential method of data collection, businesses can apply it to a number of market research campaigns to make deductions about their target market.  

This article explains how to use a sample survey to understand your target market.

Defining a Sample Survey

A sample survey is a means for collecting data on a targeted population to make inferences and predictions about the population. This method is primarily used to extract customer data on a business’s target market. 

As such, sample surveys gather information from a target market sample to make inferences from a subset of the target market members. In this way, researchers can perform market segmentation on their target market, to identify smaller segments. They may also learn more about their already identified segments, as part of their ongoing market research efforts.

A sample survey provides valuable audience insights that help you keep your customers satisfied, improve their customer experience and build their customer lifetime value

The Benefits of a Sample Survey

The main benefit of sample surveys is their ability to estimate a population’s characteristics from a small subset of the population. It’s a good method for making inferences on a large target market where you can’t possibly survey every member. 

As a business owner, your chief concern is keeping your customers satisfied. Here are some benefits of using a sample survey:

  1. You get the ability to estimate a population’s characteristics from a small subset of the population.
  2. You can make inferences on a large target market where you can’t possibly survey every member.
  3. Sampling smaller sections of your audience provides insight into the behavior of individual audience subsets, which you can use for more narrowed targeting. 
  4. You’re able to identify customer pain points and improve the customer experience
  5. It helps you foster customer lifetime value by consistently tracking the needs of your most valuable customers, providing insights that help you improve the customer journey. As its name indicates, CLV is a statistic that measures the value of a customer in relation to a business. This metric does not merely gauge a customer’s value by their purchases; rather it measures their worth during their entire relationship with the company.

Types of Survey Sampling

There are two types of sampling methods in the sample survey: non-probability sampling and probability sampling. They are used in different situations; non-probability sampling is rarely used to reflect a target market, while probability sampling is used to reflect the target population and is more useful in survey sampling.

Nonprobability Sampling

In non-probability sampling, the sample of the population to be surveyed is not determined by chance. This type of sampling is nonrandom and cannot be used to reflect the target market, using non-random sampling to make inferences about a population is problematic. Some non-probability techniques include convenience sampling, snowball sampling, quota sampling and purposive sampling.

Probability Sampling

Probability sampling is when participants for sample surveys are chosen by chance. Each person in the target market has a known, non-zero probability of selection. This method provides an accurate description of the entire target market, making it the optimal type of survey sampling. 

Sample Survey Methods

Here are the three methods of probability sampling that can be used to determine characteristics and make inferences about a target market. 

Simple Random Sampling 

Known as the most fundamental survey sample method, simple random sampling acts as the foundation for a variety of  sampling methods. In cases of simple random sampling, each possible sample size of n carries the same probability of being selected. 

For this method, elements are chosen one at a time, so that each element has the same probability of being selected– this is what creates a simple random sample. 

Stratified Simple Random Sampling

Stratified simple random sampling is a variation of simple random sampling where populations are divided into homogenous groups (called strata). The groups are called strata and a simple random sample is selected from each stratum. In the next step, results are aggregated from the strata so that inferences can be made about the target market. Inferences can also be made about the subpopulations identified through each stratum. 

Cluster Sampling 

Cluster sampling also divides the population– unlike stratified simple random sampling, though, the target market is divided into groups called clusters that are heterogeneous, not homogeneous.

Within cluster sampling, there is single-stage cluster sampling and two-stage cluster sampling. For single-stage cluster sampling, a simple random sample of clusters is selected. Data is then collected from each unit in the sampled clusters. For two-stage sampling, a simple random sample is first selected and then a simple random sample is selected from the units in each sampled cluster. 

Avoiding the Sampling Error

A sampling error is the discrepancy between a population parameter and the statistic you’re using to estimate it. The difference between a population mean and a sample mean is an example of a sampling error. 

Sampling error happens because a subset of the target audience is surveyed, rather than the entire audience. The size of the sampling error can be studied through probability sampling methods. 

While some sampling error is almost inevitable, you can reduce its occurrence with better audience targeting. The more targeted surveys you complete, the better you’ll understand the demographic mix of your audience. Audience targeting can also be used to divide the population into groups. You can reduce sampling error by testing subsets.

How Surveys Support the Sample Survey

Surveys– especially those made through a solid survey platform– can take a sample survey to the next level. Survey platforms with detailed audience targeting are key to reducing sampling error by identifying a population subset that represents your whole target audience. 

Understanding how a sample survey works and the survey sampling methods available is the first step to better understanding your target market, but the work doesn’t stop here. Applying these strategies for a successful strategy can be difficult without the right tools. Using a strong online survey platform to conduct your sample survey will have you predicting the reactions of your target market with ease.