How to Find and Obtain a Survey Sample for Accurate Market Research

How to Find and Obtain a Survey Sample for Accurate Market Research

A survey sample is a critical batch of respondents studied in market research campaigns. Given that this group forms the core of any campaign, it needs to be dealt with correctly. 

This involves extracting the sample, reaching out to it across various digital properties, analyzing it and moving forward with all the necessary steps to generate effective survey studies

As such, market researchers and marketers should be acquainted with the various survey sampling methods used to obtain a survey sample and all of its other particulars.

This article provides insights into the survey sample, including how to collect one and proceed with analysis and other crucial next steps. 

Defining the Survey Sample

Also called the survey pool, a survey sample is a group of participants who take part in a market research study, specifically, a survey study.

As its name suggests, this sample is derived from the method known as survey sampling, in which researchers extract respondents to represent a population of study. There are various methods and sub-methods involved in survey sampling.  

In market research, the survey sample comprises a business’s target market, that is, a portion of a market population that is most willing and likely to purchase from the business. As such, all marketing efforts are directed at this group of the population.

A survey sample does not have to be broad, meaning that it does not necessarily need to study all the members that make up a target market. Instead, it can be composed of a specific segment of a target market.

In order to procure this segment, researchers must perform market segmentation.

Understanding the Various Ways to Obtain a Survey Sample 

As aforementioned, there are various ways to acquire a survey sample, one of the most critical preliminary steps in conducting market research techniques

Acquiring a survey sample includes two major undertakings

  1. Deciding on the makeup of the survey sample itself
  2. Choosing a method to obtain the survey sample

The former involves determining who will take part in the sample and how many respondents to include in the sample. The latter is known as survey sampling and it entails garnering the members of a target population to take part in a survey study. 

In regards to the latter, there are two main methods of survey sampling: probability and random sampling. First, you will need to identify the makeup and scope of your survey pool. Then, you can move forward with it by deciding on a survey sampling method to obtain the pool.

The following explains how to carry out the formation of the survey sample. 

How to Choose the Makeup of the Survey Sample Itself

In reference to the above section on understanding the ways to obtain a survey sample, the second aspect of acquiring a sample — after choosing between the probability and non-probability sampling methods — is to decide who should be in the survey sample itself and how big it should be.

In order to decide on the makeup of the sampling pool, follow these steps.

  1. Refer to the purpose of your market research campaign.
    1. Ask yourself, what are its main themes and variables, along with its appropriate macro markets.
    2. For example: To learn how to market a new product to middle-aged adults in the US, your target market, or target population is middle-aged adults in the US.
  2. Decide whether you are looking to study the wider target population, or if it is more convenient for your business to study a particular segment of the population of interest.
    1. In this case, you would need to conduct market segmentation.
    2. You can also perform market research to reach the correct target market sample.
  3. Determine your accuracy requirements. This involves understanding the degree of the risk your survey study will take in terms of receiving answers that do not accurately describe the entire population.
    1. This is because you won’t be surveying the entire population.
    2. To determine how closely your answers reflect the views of your studied population, you’ll need to calculate the margin of error
      1. Ex: If your margin of error is 4%, that means 4% is added on both sides of the results of your survey sample. So if 70% of your sample likes shopping online, then the results show that 66-74% of your sample actually likes online shopping. 
      2. Your margin of error should be kept under 10% to maintain quality findings.
  4. Find the proper confidence interval. Also called the confidence level, this metric shows the likelihood of the sample you used matters in your results, as repeated studies would form the same results. 
    1. For example, a 95% confidence level would yield the same results 95% of the time. 
    2. 95% is the most common confidence level used in statistics. The ideal confidence level range is between 90-99%. Anything lower than 90% is not recommended.
  5. Finally, decide on the most fitting survey sampling method to extract your survey pool.

The Two Main Methods for Obtaining a Survey Sample

Once you’ve identified the makeup of your survey sample, you’ll need to deploy your surveys. To do so, you must decide on a method for obtaining your survey sample. The following explains the two main types of survey sampling methods.

Market researchers ought to understand these methods and all that they entail before initiating any market research campaign. Being versed in these methods will help guide your study.

Probability Sampling

Also called random sampling, this method involves giving every member of a studied population an equal chance of being selected in the survey sample. In order to select the respondents, researchers would use a random process, in which selected participants are presented as unbiased representations of the total population.

Probability sampling has several more complex sub-methods, such as stratified sampling, which involves selecting participants from subgroups of a population, such as those based on age, location, ethnicity, interest, etc. There are various other methods that makeup probability sampling.

Random sampling aims to gain a sample that represents an entire population of study. Therefore, the results of the study must be generalizable to the studied population. As such, this method is viable for quantitative market research, since it is focused on understanding a larger population by studying a much smaller subset.

This kind of sampling is therefore not ideal for qualitative market research, which seeks to elucidate a specific group of people, without generalizing the findings to a larger population.

Non-Probability Sampling

Also referred to as non-random sampling, non-probability sampling acts antithetically to probability sampling, as it does not use random means to select respondents. Thus, the members of a studied population do not have an equal chance of being selected; some of them will have no chance of being selected.

This main sampling method also has several of its own methods, such as convenience sampling, in which participants are selected if they are readily available and willing to participate. For example, if your study requires studying librarians and you only select those in your zip code, as opposed to those across geographic locations.

All procedures that avoid random selections and involve the judgment of the researchers fall under the non-probability sampling method. As such, even an online survey platform — which has a far wider reach than focus groups or one-on-one interviews — is considered a non-probability sampling tool. This is because in such a platform, the survey sample is not derived from every member of the target population. These kinds of platforms may also not rely on random processes.

One of the most powerful forms of non-probability sampling is organic sampling or Random Device Engagement. This method procures respondents organically, that is, it reaches them in their natural digital settings, as opposed to using survey panels, a sampling method that involves pre-recruiting a set of respondents. 

RDE polling engages digital users where they are voluntarily; as such, participants join on their own will and can be found on a vast network of publishing websites and apps. Thus, although the respondents aren’t extracted through organic means, RDE still offers a survey sample that joined through organic settings. 

How to Proceed with a Survey Sample

After determining the correct people to use for your survey sample, choosing which sampling method is best, along with the correct sub-method to use, launch your survey. Then analyze your initial results by performing a survey data analysis

This will be the preliminary analysis, as based on your findings, you may need to conduct another survey, either on the same group or on a specific segment of your target market, if your study was aimed at your general target market.

If you surveyed a segment of your target market, you may need to study another to compare the two. Perhaps some segments are more inclined to generate customer loyalty than others. 

If you discovered a particular behavior from your survey studies that require further studying, consider embarking on experimental research. This will help you prove whether there are correlational factors at play between your variables.

Once you’ve received a valuable share of insights, take action. A valuable amount will differ from company to company and research campaign to research campaign. Consider the findings of your survey studies. If they point to the utility in certain actions, especially if those actions seem prospective for your study or business at large, then take them. The goal of a survey sample is to forge ahead in your market research, which should always be actionable.

Leading the Charge on Your Survey Pool

The survey sample, also referred to as the survey pool, is indispensable for all market research campaigns, as those of the present-day usually rely on survey research. As the core of the survey campaign, the survey sample will determine the accuracy of the entire market research operation.

As such, it must be identified carefully and obtained properly. Aside from the actions to take in regards to these practices, another crucial factor in developing surveys for the correct survey sample is an online survey platform. Such a platform should not simply allow you to create surveys and deploy them, but to reach the correct people, i.e., your survey sample.

A potent online survey platform will allow you to choose the respondents making up your survey pool in the screening or audience section of the survey tool. In this section, you should be able to add and filter the respondents you seek on a variety of categories, including demographics, psychographics and geolocation

The key is to choose the correct online survey provider.

Mastering Survey Sampling Methods for Consumer Intelligence

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. 

  1. 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. 
  2. 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. 
  3. 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. 
  4. 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. 
  5. 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.

Survey Panels Vs Organic Sampling: Which is Better for Market Research?

Survey Panels Vs Organic Sampling: Which is Better for Market Research?

Survey panels and organic sampling are two of the major methods used to collect survey data. Since getting survey responses without the assistance of software is an almost impossible feat, these two methods have reigned supreme.

Both of these survey response mechanisms are unlikely to wane anytime soon, due to the prevalence of online surveys. As a matter of fact, the online survey software space has risen by 8% between 2015 and 2020.

With online surveys granting market researchers and marketers a large sweep of survey types to conduct, the point of contention becomes: which type of survey response collection data is better, survey panels or organic sampling?

This article will explore both forms of data collection so that you can objectively decide which to opt for in your survey research campaigns. 

Defining Online Survey Panels

Survey panels, also called online panels or research panels, all denote a data collection method in which responses are collected by way of pre-recruited and pre-screened respondents who agreed to take part in a survey.

This method helps businesses in that it assures them that a group of people will take their survey; usually, members of their target market are called upon to take the survey. 

There are a number of ways survey panels can be assembled. One such method involves mail-in recruitment, which has significantly declined in the digital age. Another relies on phone calls via Random-Digit Dial (RDD), a method in which respondents are chosen to take a survey from random telephone numbers. 

When it comes to recruiting survey panels digitally, they are garnered through an opt-in format such as a signup page or through an email invite that routes users to the survey page.  All of these recruitment manners have low participation, as few people opt into panels.

That is why some brands and market researchers resort to compensating their pre-screened panelists.

The Pros and Cons of Survey Panels

Now that you understand the basic methodology behind survey panels, you ought to consider their pros and cons before fully forming your opinion on whether to use them or not. 

The pros of online panels:

  1. They provide a network of respondents for continuous survey participation. This is especially useful if you need to conduct longitudinal studies. 
  2. They are inexpensive and create fast studies. 
  3. Returning to the same respondents, allows you to detect changing opinions over time, allowing you to see how your target market changes its opinions.
  4. They allow you to create informed custom polling questions based on previous research.

The cons:

  1. Repeated survey participation causes panel fatigue, a term denoting the decline in the quality of survey data, due to the boredom or exhaustion of a panelist. This creates them to inaccurately provide responses, either due to skipping questions, ticking off the “don’t know” option or rushing through a survey. 
  2. They occur in non-organic (unnatural) environments — inauthentic environments create inauthentic responses. This is because a survey’s environment can affect its’ respondents’ mindsets.
  3. Web panels gather respondents either on desktop or mobile, creating scenarios in which participants are dependent on device types. As such, the survey experience is not very adaptive. 
  4. Panel conditioning: Repeated survey participation can change respondents’ true attitudes, behaviors and knowledge. This makes it difficult to differentiate between actual changes and changes in reporting behaviors.

Random Device Engagement (RDE): A Precursor to Organic Sampling 

Before you analyze the organic sampling method, you should understand what makes it tick. That is because organic sampling is reliant on the delivery structure known as Random Device Sampling (RDE).

This framework implements intent-based behavioral targeting, typically used by advertisers, to narrow down random respondents in a digital setting, such as on websites, mobile sites and mobile apps. 

Thus, it provides a solution for randomization and capturing the correct audience. 

Random Device Sampling works by tracing the unique IDs of respondents, which are used to track them across devices. RDE, therefore, institutes a mechanism that is both random and organic. 

Organic Sampling Defined

Also called random organic sampling, this method refers to an RDE-based response collection method in which a survey is deployed randomly to users who are already in apps and other digital spaces.

Since surveys are randomly transferred, this method allows respondents to take the surveys while they are in their organic environments. These are the spaces that users spend time in organically, meaning they chose to take part in those environments, rather than being taken there via a promotion, incentive or signing up at a web panel.

Organic sampling works by giving optional invitations (or call-outs) to users in organic settings, so that they would partake in quick surveys. These invitations (along with the surveys themselves) are natively integrated within the digital environments (ex: apps) that the users are in.

This makes several benefits possible. 

The Pros and Cons of Organic Sampling

Powered by Random Device Engagement, organic sampling has many upper hands. However, like the panel survey method, organic sampling also presents certain disadvantages that you should carefully consider. You ought to weigh them against one another before deciding whether or not to use them. 

The Pros of Organic Sampling

  1. An organic environment allows you to avoid panel conditioning, allowing you to extract genuine responses from participants.
  2. It targets respondents’ unique IDs so that they can be traced even while shuffling between devices, preventing the same participants from taking the same survey twice. 
  3. Using respondents’ IDs allows you to create respondent profiles, which build an overview of the respondents’ behaviors demographics, which are critical data to possess.
  4. In turn, the respondent profile helps prevent fraud, as multiple accounts or bots won’t able to submit their surveys. 
  5. It yields high response rates (higher than RDD and survey panels).
  6. It creates a seamless UX across all device types, rather than being tied to just one with little wiggle room. 
  7. It provides vast coverage, as RDE integrates natively with a bevy of digital and mobile platforms. That entails greater accuracy. 

The Cons:

  1. It relies on non-probability sampling, wherein some of the members of a population have been excluded and this amount cannot be calculated, which limits how much you can determine about the population from the sample.
  2. It will include biases based on the populations you have preset to include in your sample, even if you assign quotas.
  3. Organic sampling and RDE are at the mercy of the websites and apps that they can be integrated with. It is possible that your targeted sample pool visits apps and other digital places that your RDE survey isn't integrated with.

Which Sample Pool Method Reigns Supreme?

While random organic sampling has made a mark in the survey realm, due to Random Device Engagement, it still faces its rivalrous counterpart: survey panels. 

Other forms of survey sampling methods have been on the decline, yet survey panels are still in use. While they may appear to have fewer advantages and more disadvantages, survey panels still provide value to researchers. 

As such, it is entirely up to you to decide which survey sampling method is best for your market research needs. Random organic sampling is our survey sampling method of choice, as it continues to rise above survey challenges, provides solid results and does so in a short span of time.

Frequently asked questions

What is an online survey panel?

Also called online panels or research panels, an online survey panel is a way of repeatedly collecting data from pre-recruited respondents via digital surveys.

What are some of the benefits of an online survey panel?

Online survey panels allow companies to quickly and inexpensively collect data from a group of people since the recruitment and screening process only needs to be performed once. Since responses are collected from the same group over time, they are able to show if and how opinions or behaviors change over.

What is panel fatigue?

Panel fatigue is a concern associated with survey panels. It occurs when panel participants become bored or tired of replying to surveys. This can result in the overall inaccuracy of the data collected from that participant.

What is organic sampling?

Organic sampling, or random organic sampling, refers to the process of distributing surveys to a random group of respondents. The respondents are typically sourced from websites or apps where they are given the option to participate in a survey.

What are the benefits of organic sampling?

Organic sampling can help prevent some of the pitfalls of survey panels including panel fatigue and panel conditioning. Organic sampling also tends to yield higher response rates and can help prevent fraud or data errors.