How Surveys Help Reduce the 4 Types of Sampling Errors in Market Research

sampling errors

Market researchers must learn how to grapple with the different types of sampling errors. As one of the major manifestations of the flaws in market research, researchers should be well-aware of what they are and the consequences they carry for market research campaigns.

Although damaging to the effectiveness of your research, the four types of sampling errors aren’t ineradicable. When you are well-versed in their meanings and ramifications, you can better track them. Surveys can help you reduce them, so that your output consists of effective survey studies.

This article explains the four types of sampling errors and how surveys can put them at bay so that you yield the most accurate and quality data.

Understanding Sampling Errors

Sampling errors denote the deviations in the sampling pool data from the data that would actually result from the true population. They occur from the phenomenon in which the sample used is not a genuine representation of a certain population.

Essentially, these errors are the difference between the real values of a population and the values taken from a sampling of the population. 

The origin of the errors lies in the collection of data, which then renders the results as invalid. 

These are categorized into four types of sampling errors. You can minimize these four types of errors through a number of ways. Using surveys can alleviate these types of sampling errors when used correctly. This is to say that each type of error has its own reduction requirements to be used with surveys.

The Four Types of Sampling Errors

There are four types of sampling errors. The problem with these errors is that they invalidate the results of a survey. In such instances market researchers should calculate the margin of error, as sampling errors are not specific calculations

Instead, they rely on the margin of error as a measurement of the maximum likely size of your sampling errors. You can use this metric if you use random survey sampling methods.

The following explains each of the four types of sampling errors present in market research.

Selection Error

This error comes about when the survey participation is selected by the respondents themselves, meaning that only those who are interested take part in the survey. A common example of this kind of error is a survey that uses a small portion of respondents who partake immediately. 

If a business or the market researchers thereof follow up with the respondents who didn’t initially respond to the survey, the results are bound to see some change. Also, if the researchers overlook the respondents who don’t respond immediately, this too will not reflect the views of the entire target market. 

Population Specification Error 

This error transpires when market researchers do not know who exactly to include in their sampling. This error emerges when certain niches and more specifically — products, do not have specific members of a target market.  For example, sandwich consumers can span across generations and ethnicities.

When the population specification error occurs, it is also due to sampling the wrong population. For example, a company may be launching a new line of handbags, aimed at the younger generation. However, this population may not have the required purchasing power to be consumers. Thus, the company targets slightly older targets. Although they have a higher purchasing power, they have no interest in the handbags.

In this error, the wrong respondents are targeted from a lack of knowing which group(s) would most precisely be of use to survey.

Sample Frame Error 

The sample frame error relates to surveying the wrong population in the way that a sample has been selected. Survey biases occur from this error, in that market researchers in this case do not foresee that only certain kinds of respondents would be in their sampling pool, thereby excluding critical members of a target population. 

This error includes targeting the wrong segments, or missing out on certain demographics within the correct segments. A few examples of this error include when researchers do not target respondents who:

  • use a particular device (iPhone vs Android)
  • live in a certain region
  • are of a certain income group

By missing the key people in a survey study, it results in sampling a group who does not fully fit or complete a target market or population of a study. 

Non-Response Error

This error refers to the issue that results from failing to obtain a useful response in the surveys, in regards to the groups of respondents who take them. This occurs when a common group of people disproportionately partake in a company’s survey studies, instead of all relevant groups, therefore skewing its results.

In the case of this error, other groups who pertain to a survey’s study, such as other target market segments miss the opportunity to offer their data and insights. It can spring from a refusal to complete a survey or take it in the first place.

How the Four Types of Sampling Errors Differ from Non-Sampling Errors

Aside from the four types of sampling errors, other types of errors exist in market research. These are commonly associated with errors that don’t occur due to sampling itself, thereby landing them the name of non-sampling errors.

Non-sampling errors are deviations of estimates from their true values, ones that are not a part of the function of a chosen sample, which includes both random and systematic errors.

Non-sampling errors can spring up in the case of samples and censuses, i.e., when an entire targeted population is surveyed. 

Non-sampling errors can also arise within a representative sample, e.g., a national survey, or during total enumeration, e.g., via an employee feedback survey.

survey sampling errors

The below explains the ways in which various types of sampling errors differ from non-sampling errors. 

  1. Sampling errors can emerge even when there is no apparent mistake, while non-sampling errors come up due to a mistake.
  2. Sampling errors dictate a sample that is not representative of a universal truth of a target population, whereas non-sampling errors are particular to a study design.
  3. You can reduce sampling errors by increasing the sampling size, but non-sampling errors require methodical practices for reduction.
  4. Internal factors usually cause sampling errors; on the other hand, non-sampling errors occur from external factors not entirely related to a survey, study, or census.

How Surveys Reduce the 4 Types of Sampling Errors

Surveys as a market research mechanism may often be embroiled in the different types of sampling errors. However, when used correctly, they can greatly reduce them. It predominantly depends on the online survey platform you use. The following explains how surveys help reduce the four types of sampling errors.

  1. Selection Error: You can reduce it by encouraging participation.
    1. The call-out of a survey can help grab res[ondents’ attention and interest.
    2. A survey’s setup can also help. For example, if site and app users find a survey, they are obviously more likely to take it than those who don’t see it.
      1. This will depend on the online survey platform you use, along with where you set it up.
    3. Survey incentives are known to drive up respondent interest in taking a survey. 
  2. Population Specification Error: You can avoid it by having a deep knowledge of your target market and its makeup of sectors.
    1. Surveys help you to both identify and study your target market, via market segmentation.
    2. You can learn more about the proper segments for your various market research and marketing campaigns via the target market survey
    3. Survey research also completes secondary market research on your target market.
  3. Sample Frame Error: The proper online survey platform will allow you to not merely identify all the correct members of your target market, but reach them as well.
    1. It should be set up in a way that makes it nearly impossible to miss the crucial members of your target population.
    2. Various demographic, psychographic and geographic filters should allow you to include (or include) your intended respondents.
    3. A survey platform must allow you to target any group, while seeing how various groups are divide, e.g., by device type, operating system, location, etc.
  4. Non-Response Error: The makeup of the survey and the way it is deployed can cut back on this error.
    1. A strong online survey tool can ensure potential respondents that the survey is short.
    2. Such a platform can make surveys more engaging by including various question types so that respondents do not get bored and complete their surveys.
    3. You can also add multimedia files to weed out boredom. 
    4. Incentives also help net those who are not inclined to take surveys.

Warding off the Four Types of Sampling Errors in all Your Endeavors

Market researchers should always expect the presence of different types of sampling errors; no study can fully encapsulate the opinions and other data of all the members of a target market.

These errors even arise when no mistake is present, making them inevitable. 

However, market researchers and general research ought not to fret, because there are ways in which you can significantly minimize these errors. Surveys themselves can help you keep these errors to a minimum. 

The effectiveness of using surveys as a method of lessening the four main types of sampling errors depends on both the online survey platform you use and the different best practices you take to ensure their reduction. As such, you should choose platforms that offer relentless quality.