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Mastering Survey Sampling Methods for Consumer Intelligence

Survey sampling methods are a crucial part of the survey research process, as the aspect of sampling is more than just a data collection practice.

This is because in order to glean any valuable insight from surveying, the respondents must be as representative of the study’s target population as can be. The correct survey sampling method can make this possible.

When conducting survey research, there are several sampling methods researchers can leverage. In order to apply the correct method, there are certain things you need to establish. This article delves into survey sampling methods, including the considerations to take before settling on a sampling method for your research needs.

Defining Survey Sampling Methods

Survey sampling methods denote the types of techniques used to select participants from a target market (or any target population) to take part in a survey sampling pool.

In survey research, the sampling pool is the group, or “pool” of targeted respondents who participate in a survey study. This sampling pool must accurately represent the targeted subject population.

It is important to have a group of people who will participate in the survey and be able to represent the whole target population. This group is called a “sample".

Settling on the proper sampling pool is known as sampling, which is critical to surveys, as it makes up the foundation of the survey campaign.

Why Survey Sampling Methods are Necessary

The main goal of surveys is to gather accurate information about a particular population. As such, they would be futile if they insufficiently accounted for the participants that they’re set on studying.

Survey sampling is necessary, as sampling provides a potent means of extracting and analyzing a targeted subset of a population. Even when researchers zero in on a subset, it is still virtually impossible to study the entire population of a targeted group.

The reason is twofold and fairly straightforward: not all members of a particular population will be exposed to a survey, and out of those that do, most will not be willing to spend time filling out a survey.

As such, researchers turn to survey sampling methods, so that their sampling pool best represents the population of researchers’ interest. With the right method, researchers can make well-informed inferences about their targeted population.

Sampling reduces the sampled respondents, which lessens both the workload and costs associated with a particular survey study. However, researchers have to find the correct balance of participant involvement to accurately ascertain associations between variables.

Determining Your Target Population: The Precursor to Survey Sampling

Effective survey sampling occurs when the researchers have established the population subset which they intend to study. As such, you should begin any survey sampling campaign by defining your targeted population.

If you need to conduct surveys for a business, you should always aim your studies on your target market (when not observing your competitors). This is because the target market is the group of individuals most interested in your sector and most likely to buy from you.

In this regard, it is also important to conduct market segmentation of your target market, as your target market is made up of several consumer segments. Surveys are a powerful tool for segmenting your target market.

But again, you must properly sample your population before conducting any survey research. There are several ways to approach survey sampling.

Probability (Random) Sampling Vs. Non-Probability Sampling

There are various kinds of survey sampling methods, which fall under two main classifications: probability and non-probability sampling. Businesses, governments and other entities can apply either one or both of these methods for their research needs.

Before navigating the multitude of survey sampling methods, it is key to be able to differentiate the two main categories of sampling. This will put the subcategories, i.e., the specific sampling methods into sharper perspective.

The following explains the core aspects of the main types of sampling methods.

Probability Sampling:

Also called random sampling, this category initiates with a full sampling of all the individuals qualified to be in your sample. This main method grants all eligible participants the chance to be used in the sample. In this way, your sample will be able to allow you to make generalizations from your survey results.

The methods that fall under probability sampling can be more expensive and take up more time than their non-probability sampling counterparts.

The main advantage of using probability, or random sampling is that the chosen sample is more representative of the target population. As such, this kind of sampling fosters credible statistical conclusions.

There are five main types of probability sampling methods: simple random sampling, stratified sampling, cluster sampling, multistage sampling, and systematic random sampling.

Simple Random Sampling: The most common form of probability sampling, random device sampling involves each member of the population receiving an equal chance of being selected in the sample pool. True to its name, the respondent is chosen by chance. This method reduces selection bias and allows you to calculate the sampling error.
Stratified Sampling: This method involves dividing the population into subgroups. Known as strata, these groups are divided based on a shared characteristic. This method is used when there is reason to believe the variables will differ between each subgroup. Populations can be stratified by gender, age, location, interests, habits, etc. The study sample is acquired by taking either equal or unequal sample sizes from each stratum. This method enables all categories within the population to be represented in the sample.
Cluster Sampling: This form of sampling assigns every member of the population to a single group called a cluster. Then, a sample of clusters is chosen, typically via simple random sampling. Contrary to stratified sampling, which includes elements from each stratum in the sample, cluster sampling uses a sample with elements only from the sampled clusters. As such, it is more exclusive. This method can be efficient when it comes to studying a wide geographical area, as it’s easier to contact many members of one area than a few members of various regions. The disadvantage includes an increased risk bias when chosen respondents are not representative of a population, which yields sampling errors.
Multistage Sampling: This technique relies on selecting a sample by way of combining different sampling methods. As such, this method involves different stages, wherein Stage 1 may use random sampling, while Stage 2 may use stratified sampling. This method allows researchers to merge different styles of sampling, as a means to study various variables and draw conclusions through different focuses.
Systematic Random Sampling: This method is used when a given population is logically homogenous. It involves enumerating all members of the given population on a list. When all members of the list are compiled, the researchers select the first sample element from the first several elements on the list at regular intervals. The advantage in using this method is its relative ease of use, in comparison to simple random sampling. Also, since simple random sampling may involve clusters, systematic random sampling offers a contrast: evenly sampling the population.

Non-Probability Sampling:

Also referred to as non-random sampling, this chief method does not start with a complete sampling pool, as some participants will not have a chance to be selected in the sample. Instead, it relies on the researcher's judgment.

As such, researchers can’t assess the effect of the sampling error. Additionally, there is a higher risk of using an unrepresentative sample, which harms the chances of reaping generalized results.

On the other hand, non-random sampling methods are less costly and are easier to conduct, making them conducive for exploratory research and formulating hypotheses.

There are four main types of non-probability sampling methods: convenience sampling, quota sampling, judgment (purposeful) sampling and snowball sampling.

1. Convenience sampling: Known as the simpler non-random sampling method, convenience sampling selects respondents based on their own availability and willingness to participate in the sample. Although researchers can amass valuable information, this method carries a greater risk of volunteer bias, as those who wish to take part may be significantly different from those who don’t. Thus, the sample may not be representative of certain characteristics, such as habits, age or geographical location.
2. Quota sampling: The most pertinent non-probability sampling method for market research, as respondents are chosen based on quotas. For example, a survey study may require 100 adult men, 100 adult women and 200 children. The quotas used would need to represent the characteristics of the studied population. The benefit in this method is the potential to be highly representative. However, respondents may not be representative of characteristics that were not considered, which is one of the general drawbacks in non-random sampling.
3. Judgment Sampling: Also referred to as purposeful, selective or subjective sampling, this method involves exercising the researcher’s own judgment when choosing sample participants. Therefore, they may decide on a representative sample, one that exhibits certain characteristics. Oftentimes, media outlets use this method when surveying the public on qualitative research.
4. Snowball sampling: This method is named based on the analogy its methodology puts into practice. Typically used in surveying groups that are difficult to reach, respondents are tasked with calling on more respondents (the ones they know) to take part in the sample. This is how the sample of an otherwise hard-to-recruit group increases, or snowballs, in size. This method is productive for bringing on individuals that can be difficult to study, but it risks selection bias, as is the case when choosing a large group of people with similar traits to the original respondent).

Survey Sampling Size, Bias & Other Considerations

When undertaking survey research, aside from understanding your target population and what kind of data to derive from them for your survey research, researchers need to decide on a sample size. This does not necessarily need to occur before deciding on the best survey sampling methods for an investigation.

Instead, it is apt to start with an approximate number of respondents in your sample, while identifying an exact size after you settled on a sampling method. This is because researchers may come upon factors that change the proper sample size for their studies. Additionally, facets such as budget and availability come into play.

Researchers also ought to note that both probability and non-probability sampling methods run the risk of developing a survey bias. These biases take place in various situations. These include omitting respondents from hard-to-recruit groups, straying from sampling rules, replacing already opted-in individuals with others, low response rates and others.

Another critical issue to consider is that your survey vehicle, the tool you will use to design and deploy your survey. A strong online survey platform can help you avoid biases and will offer a modern survey sampling method. One of the latest and most potent techniques is RDE (Random Device Engagement), which can reach a massive sample and incorporate several of the methods listed above.

Businesses and researchers in other industries should therefore consider using this survey sampling method.

Frequently asked questions

What is a survey sampling method?

The survey sampling method refers to the technique used to choose individuals to participate in a survey.

Why are survey sampling methods necessary?

In order to gain accurate information about a population, researchers must select participants who provide a good representation of that population. Survey sampling methods provide a way of selecting participants that will best represent the targeted population.

What is a target population?

A target population is a narrowly defined group of people that will be studied in order to draw conclusions about a wider population.

What is probability sampling?

Also called random sampling, probability sampling is a sampling technique in which participants are chosen at random from a larger population.

What is a survey sample size?

A survey sample size is the number of individuals who have been chosen from the target population to participate in a survey.

by lorraine

Survey Research Methods: A Deep Dive

Although survey research methods are just one tactic under the enveloping market research field of study, they too are administered in a number of ways.

That is because much like market research, there is no single or universal technique when it comes to survey research. Instead, there are various survey research methods, those that only pertain to the survey aspect of market research.

Survey research methods include different sets of classifications, from types of surveys, to data organization and more. It is key to become familiar with all of them to determine which is most suitable for your market research needs.

This article will navigate all the nuances that pertain to survey research methods.

Surveys for Quantitative vs. Qualitative Research

Market research relies on both primary and secondary research; surveys fall under the former and have several classifications. The first major one conveys the duality within survey research methods: that of quantitative and qualitative research.

Quantitative research surveys:

Quantitative research involves gathering quantitative, or numerical data. Surveys amass this data by asking questions that quantify attitudes, opinions, feelings and behaviors. The point of this kind of survey research method is to form generalizations.

Quantitative research surveys therefore use a larger sample size in order to crunch numbers on different issues and variables. This survey research method is highly dependent on using and creating mathematical and statistical data.

These surveys use this data to identify patterns in a target market, find averages, make predictions and test relationships.

Essentially, this survey research method uses respondents to understand the “what” and “how much” of a studied subject.

Qualitative research surveys:

Qualitative research zeroes in on experiences, ideas and opinions, instead of focusing on statistical or quantitative results. Instead, this survey research method seeks to holistically interpret an issue, occurrence or phenomenon.

As such, qualitative research seeks to perceive an issue in more depth, find the cause of an occurrence, create inferences, find solutions to problems and uncover trends.

This research method is centered around the “what” and even more so, the “why” of a research subject.

Unlike quantitative research, qualitative research uses a smaller sample size for a deeper understanding of causes, motivations and sentiment.

This kind of survey research method uses open-ended and exploratory questions in natural environments, in which respondents freely discuss their opinions to help researchers identify the “why” behind an issue.

Understanding the “why” is then used to make decisions on how to resolve the issue or how to improve on an existing productive situation.

Survey Panels Vs Random Sampling

The second main classification of survey research methods is categorized via the sampling pool. There are two main types of sampling pools, i.e., the type of respondents that take part in a survey.

Market Research Panel:

A market research panel is a pre-recruited group of survey respondents who have agreed to take part in online surveys. This method is most commonly employed by market research panel companies, which require the panelists to share personal information about themselves.

This includes the information you’d find at the screener section of a survey tool such as demographics, but can also include behavioral data. The panel can be used for more than one survey; this way is convenient for market researchers who require long-term survey campaigns such as longitudinal surveys.

Random Sampling Pool:

A random sampling pool is a group of survey respondents who have not been recruited to take part in a survey. Instead, this method involves, as the name suggests, a random group of participants. They take a survey once they reach a publisher’s website or app, which is triggered by an online survey tool. As such, they take a survey due to their being real-time users on a site or app in which the survey has been launched.

Any business can take this automated approach, which does not require seeking out participants manually, as a market research panel would. Although the pool of respondents has been gathered randomly, the qualifying participants are not random.

This is because the survey software used to launch this survey includes screening questions and demographic requirements that respondents must meet to take the survey. As such, researchers still get the exact kind of participants they seek to survey. This survey research method includes probability and non-probability sampling.

Survey Research Methods Based on Campaign Type & Macro Applications

Survey research methods can be further divided based on the type of macro application (or discipline) you need the data for. They can also be categorized into different campaign types, which can fall under the macro applications, or exist as their own application.

You should understand these purposes before you choose the proper survey type for your research needs. Here are the major campaigns and applications to base your survey method on:

Marketing: A broad term that includes a wide variety of processes to raise awareness and demand in your company, promote it and understand your target market.
Advertising: One of the key practices in marketing, advertising refers to communication using overtly sponsored messages to promote or sell a product or service.

Branding: The development of a brand’s reputation and image, along with increasing the recognition of your company.

Market Segmentation: Facilitates targeting those most likely to be satisfied customers of your company or content. It involves splitting your target market up into smaller groups of people with similar characteristics.

Competitor Analysis: It is the process of identifying and assessing your competitors based on their strategies to unearth their strengths and weaknesses relative to your brand.

Employee Satisfaction: The degree to which employees are content and fulfilled with their jobs, including their schedule, work environment and banter with fellow employees.

Customer Satisfaction: The measurement of how happy customers are with a company's products, services, experiences and interactions.

Types of Surveys

Finally, we arrive at the types of surveys, the most granular aspect of survey market research methods, that is, unless you delve further by looking into survey questions.

These surveys are classified as belonging to either quantitative or qualitative methods, along with their best application type. As for the latter classification, you ought to know that these surveys are not necessarily limited to these applications.

Rather, they are most apt for the named applications and campaigns, but due to the versatile nature of surveys, the following can be used in other applications, including those not mentioned in this article.

Cross-sectional surveys: Gather data to make inferences about a population at some point in time.

1. Used to provide snapshots of the populations they survey.
2. Drawn from a few specific variables to narrow down a unique and smaller population.
3. Method: Quantitative surveys
4. Best used for: advertising, market segmentation, employee satisfaction, customer satisfaction, branding
Longitudinal Surveys: Study variables over longer periods of time. (Weeks to decades)
1. Require more dedication from respondents and researchers, including time and money. In this regard, a larger pool of participants is used and studied for much longer.
2. Like cross-sectional surveys, these are also observational and study the exact sample pool for the length of the study.
3. Method: Primarily qualitative, but can be quantitative
4. Best used for: marketing, competitor analysis, market segmentation
Retrospective Surveys: Merge aspects of both cross-sectional and longitudinal survey methods.
1. Observe changes that occur over a longer period of time, but are facilitated just once.
2. Thus, responders discuss occurrences, attitudes and feelings from the past.
3. Method: Qualitative and quantitative surveys
4. Best used for: Marketing, branding, competitor analysis

Going Beyond Survey Research Methods

Understanding the various survey research methods are crucial to forming the most fitting market research campaign for your brand. However, it doesn’t end here. With innovations in the market research field, other survey methods and sub-methods are going to emerge.

Moreover, after you’ve found the best survey research method(s) for your company, you’ll need to conduct the proper survey data analysis.

As such, you’ll need to analyze your surveys, and this can be done in a number of formats. Some are going to be more visual than others.

After all, conducting surveys is one thing, but understanding the surveys is the centerpiece of any research campaign.