Smart Ways to Select Superior Samples for Market Research
Get sample size correct and recruit the right respondents means collecting data you can use to elevate products and services
If the entrepreneurial world were a fairytale, market research would be the noble knight who swoops in and saves you from the relentless forces at play that challenge and put your business at risk.
Replete with unpredictable plot twists, the turbulent storybook universe is an apt analogy for the environment in which contemporary commercial organizations operate. New companies take flight and immediately plummet to the ground, making it evident that it isn’t easy for a business to succeed in a landscape that asks you to reinvent yourself consistently to stay relevant.
In this context, if you’re an entrepreneur, standing your ground in a competitive atmosphere is crucial. You can hone your ability to do so by accessing carefully curated insights into the market. However, there is no point in these insights if you acquire them from the wrong people.
Collecting data from audiences who aren’t relevant to your business results wastes time, money, and energy. Therefore, the correct approach to employing sampling methods in research carries a lot of weight. Determining sample size correctly and recruiting the right respondents leads to collecting data that you can use to elevate your products and services.
This sample size calculator is perfect for estimating a random sample size when you are planning for simple random sampling or working in multi-cell samples such as cluster sampling or stratified sampling. It will estimate a probability sample size for most any survey you define.
Science Behind Sample Design in Market Research
In an ideal scenario, you would want to collect data from your entire target population. Logistically speaking, this is not possible, especially if your business operates internationally or across multiple cities. Interviewing every customer will be costly, and the vast amounts of information gathered will require patience and meticulous attention to detail when it comes to drawing statistical inferences.
Surveying the entire audience is inconvenient. Instead, you should select and study a portion of your audience through an appropriate sampling method.
There are various sampling techniques at your disposal in market research. You should opt for those techniques that reward you with a representative participant group. Accounting for every customer type is important because you want your research to be inclusive and not miss a specific audience segment. Otherwise, it can result in the loss of a game-changing insight that could have helped you crush your industry competition.
Smart Sampling Strategies
Figuring out which sampling method suits your research objectives can be the most grueling part of your study, and there are some key considerations to keep in mind when you set out to recruit respondents. To select the perfect sample, choose participants whose input you feel will minimize the margin of error in the results you generate, while simultaneously catering to your inquiry’s aim.
There isn’t any study that boasts complete data accuracy. Human error is part and parcel of every endeavor man undertakes, and market research is no different. However, when it comes to sampling, we can attempt to authenticate our insights by recruiting larger samples. Generally, when more respondents participate in a study, their input can render outliers meaningless and unearth common trends through the shared opinion of a large subject pool.
A well-designed sampling frame can also improve the validity of your study. Consisting of sources of potential participants who can be contacted easily through:
Telephone Survey Sampling
Telephone surveys require sample sources that vary based on the type of study being conducted. Consumer research studies often require Random Digit Dial (RDD) Telephone Sample based on the geography being studied. The same type of sample is used for Political Polling but often it is registered voter contact info that is used as well. You can purchase RDD telephone sample from companies like Scientific Telephone Samples, Inc. or Marketing Systems Group, Inc.
B2B Studies and Customer Satisfaction Studies mainly rely on customer lists but this is not always the case. You can buy business phone contact lists by industry and title from companies like Dun & Bradstreet, ZoomInfo, and many other list companies.
Online Market Survey Sampling
Online research sampling engages participants in various ways from website intercepts where you can place the link to your survey right on your website and invite members or customers to participate or you can intercept people on various websites with behavioral targeting and invite them to participate based on search behavior or shopping behavior assuming they opt-in.
You can leverage customer email lists which often are used when conducting B2B and customer experience online surveys.
What is a Sample Frame?
A sampling frame ensures that you narrow down your target population to folks who can be traced. If you want to revisit a participant’s responses, you can reach out to them to gain more insights and not worry that they’ll be unreachable after the study ends.
Sampling frames ensure further accuracy by providing documented data. For instance, let’s say you are a restaurant owner who wants to explore customers’ spending habits. Pursuing such a study will be chaotic if you interviewed customers who made cash transactions only. Understandably, it’s a long shot to assume that they’ll remember how much they spent on appetizers and entrees through the months leading up to the study! On the other hand, if you recruit customers who use debit/credit cards when dining at your restaurant, the history of their expenditure will be available in your electronic database. In surveying the latter, all you have to do is acquire their consent, and your computer will dig out the information you need.
The sample design you choose for your inquiry also makes the difference between a verifiable study and one tainted by bias and inaccuracy.
Random sampling, also known as probability sampling, is a kind of sampling design where each member of your target population has an equal chance of being recruited for your market research. This design boasts greater accuracy as it eliminates sampling bias and ensures that every person who constitutes your customer base is represented.
Random sampling is accomplished through various techniques. These include but are not limited to:
Simple Random Sampling
As the name suggests, this is the least complex form of random sampling. Many of us have employed this technique in our daily lives when we pick names from a hat or close our eyes and point to an item on a list to make a selection. Similarly, this sampling technique is adopted in market research when we identify a sampling frame and recruit a certain number of respondents from it at random.
Venturing in a slightly different direction compared to simple random sampling, systematic sampling relies on following a sequence. For example, let’s say you own a makeup brand and wish to interview every 50th customer who invests in your recently launched lipstick collection. Systematic sampling can help you accomplish this by allowing you to recruit respondents in a controlled manner.
This sampling method helps you divide your target population into segments and randomly select participants from each segment. Stratified sampling ensures that a representative participant pool is recruited when your audience is massive and defined by various characteristics.
To understand this technique better, imagine you are a business leader who feels that some employees aren’t doing their job. To investigate this drop in productivity, you may want to carry out some research to monitor your labor force. However, you will be left grasping for answers if you have hired workers for two different shifts and end up interviewing just one of the two shifts!
If, for instance, the lackluster employees sign in during the night hours and you haven’t studied that segment of workers, you won’t discover the problem’s origins. In cases like these, you need to use stratified sampling to conduct a thorough analysis of your business’s sectors as it is the only way you will tap into accurate results.
Emerging from the confluence of simple random sampling and stratified sampling, quota sampling is true to its name and requires you to keep recruiting respondents until the target number for each stratum is reached.
As opposed to random sampling, non-probability sampling is the design used when a researcher can’t access sufficient information about the target population.
Suppose you run a clothing business that sells jeans and t-shirts across the globe. Due to a lack of prior research, you may not know of certain towns where your outfits are being sold through second-hand retail. If you opt for stratified sampling, there will be a whole section of people who interact with your products, which will be missing from your research because you were unaware of this sales pattern.
Since it doesn’t allow for every member of the target population to be chosen at random, non-probability sampling poses a greater risk for biases and gaps that can de-legitimize your study’s findings.
Pursuing the right sampling methods in research can grant you powerful insights from a market survey conducted to perfection.
Sampling allows you to engage with members of your target population. A sample is like a symbolic shield that strengthens the arsenal with which you conquer your competitors. Keeping this in mind, you must approach sampling with your undivided attention and use recruitment strategies that guarantee maximum data accuracy along with the collection of information that aligns with your research objectives.
Tyler Maher is a Research Manager at OvationMR and posts regularly on The Standard Ovation.
OvationMR is a global provider of first-party data for those seeking solutions that require information for informed business decisions.
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