Conjoint Survey Sample Size1

Sample Surveys: The Pillar of Effective Data Collection

Transform your insight generation process

Use our in-depth online survey guide to create an actionable feedback collection survey process.


Table of Contents

Data collection activities are meant to gather useful and relevant insights about a targeted population which is then used as input in making important organizational decisions.

In order to understand the interests and perceptions of your target market, it is isn’t practically feasible to use every individual in the population as a participant in the research process. In order for the study to be completed within a timely manner, selecting certain number of suitable individuals is the way to go. This is where sample survey steps in.

What are sample surveys?

Sample surveys are a methodology that focuses on selecting a set of individuals capable of representing the target population.

The basic idea behind the concept of sample surveys is to gather the information that will boost data collection while doing so within a specific time frame. This maximises the effectiveness of research processes by making the end result and analysis actionable.

For example: A footwear brand decides to conduct a pricing model study for a line of shoe designs launched as teenage sportswear, using conjoint analysis. This is an attempt to revive the brand from declining customer demand due to overcharging.

The study is targeted at teenage customers of the brand. However, surveying all the customers within that age group would not be practically possible. The brand requires a sample of individuals that are willing and capable of delivering significant value additions to the research by providing an accurate overview of the price points or range that is deemed fit and will provide an impetus to brand sales.

So, the brand uses a random number generator to select people to be included in the sample. This ensures that every member who is a part of the target population has an equal chance of being included in the sample of survey participants and eliminates any bias that may lead to window dressing in the survey results.

The sample, upon selection, provides their authentic responses to multiple price models using criteria such as comfort, quality, size, colour coding and other such relevant characteristics that impact customer choices. The input so provided gets summarized by using appropriate data analysis and statistical tools, to be used by multiple stakeholders and users for directing follow up actions. The quality of research is projected by how well the responses provided by the sample assist in boosting brand footwear sales.

The above example portrays the use of a subset of people to derive insights in a timely manner.

What is the need for sample surveys?

Implementing a surveys that collects data from the entire target population is neither efficient nor feasible. This becomes even more difficult when the population is large in number. Each aspect of data collection from distribution to analysis and compilation becomes more cumbersome.

Organizations belonging to any industry are part of a dynamic environment that pushes them to make quick decisions according to the changing circumstances. Such decisions have to be fuelled by substantive market knowledge that provides direction and guides the investment of resources in the right areas.

Sample surveys drive organizational actions by concentrating on a particular set of highly representative individuals. The process of selecting and screening such individuals has to be planned and implemented carefully for such surveys to generate qualitative results. The researcher needs to ensure the eligibility of a selected respondent by aligning sample information with the characteristics of target population.

Sample selection

Sample selection is the most integral part of your entire sample survey. The method that you choose for selecting your sample will impact the validity and quality of your responses.

The sample selection can be done manually or using multiple techniques that are adopted by data scientists. Researchers choose sample selection methods that help them filter out the useful candidates from the ones which lack the relevant knowledge base to supply key insights.

The idea behind choosing a suitable selection mechanism is eliminating any sort of distortion, misrepresentation or bias in survey results. Selecting a non- representative samples brings in high sampling error that are in no way useful for organizations to maintain a competitive market footing. The downsides of improper sample selection are:

  •       Wastage of resources invested in ideating and conducting the research
  •       Loss of personnel time
  •       Inaccurate analysis
  •       Lack of directional decision making
  •       Dissatisfied stakeholders among others.

To optimize you selection procedure, keep certain basic pointers in mind:

  1.     Equal representation: Ensure that each sub-group has an equal share in your sample volume. This way, no single group has a majority sway over the final results.
  2.     Know your respondents: Organizations must possess updated information about their respondents to be confident about their eligibility as a qualified respondent. The sample frames used to build research samples must supply current demographics of the respondent.

    Substantial sample size: Process the right balance between including excessively large samples and samples that are too small to be significant. More the number of suitable individuals in your sample, more cohesive will be your survey.

Advantages of sample surveys

Quick data collection: Sample surveys do not require the researcher to collect data from a large set of respondents. The relatively small group of people make it easier to distribute, collect and analyse survey responses for meeting organizational needs in a timely manner.

Lower cost: Sample surveys are an efficient data collection mechanism. It does not ask for extensive resource investment research affiliated activities. Lower the number of research participants , lower is the cost of surveying.

Increase in surveying capacity: Researchers exercise greater degrees of freedom while surveying samples. The lack of time bound questioning and restricted knowledge of the respondents can be eliminated as researcher can engage in narrowing their focus to conduct nuanced research.

Large scale impact: Sample responses are a representation of the entire target populations perceptions. Provided that the sample gets carefully screened and selected, these time based surveys can generate huge results for end-users.

Explore all the survey question types possible on Voxco

Explore all the survey question types possible on Voxco

Disadvantages of of sample surveys

Sampling errors: This error occurs when the sample so selected does not accurately represent the target population. This error can lead to distorted or skewed results, neither of which can be used a reliable source for channelling intelligent follow up actions. The researcher can adopt multiple practices to minimise such an error: Increase sample size, incentivise surveys, segmentation of samples and random selection process.

Complexity involved: Picking a representative is not something that can be done with a 100% certainty. The researcher needs to study the target population deeply before figuring out which group of people will be able to provide high quality inputs.

Survey pattern: The terminology and progressions of questioning must be suitable for all individuals within the sample. Even if the sample is highly representative, incorrect patterns of surveying can deform the survey results.

Need for statistical expertise: Personnel assigned with the task of monitoring and summarizing survey results must be equipped with a certain degree of pre-requisite knowledge about sampling and the right tools and methodology to be used to suit the research needs. They  must be familiar with the research purpose and the practices that will fit best in formulating a balanced understanding for each end-user.

Read more