The Importance of Sampling Your Market

Prior to Campaign Launch

Prior to launching your marketing campaign, it’s important to know who your audience is and what your audience wants and needs. Understanding the various methods of sampling – and which option will work best for your campaign – is key to increasing your ROI. There are two main categories of sampling: Probability and Non-probability. As probability sampling is used to determine the outcome of many different scenarios, it isn’t the most cost-effective method for exploring your consumer base. We recommend focusing on non-probability sampling, instead. We’ll lightly explore both kinds of sampling methods, but we’re honing in on two specific methods today, specifically: Stratified and Quota. From there, we’ll talk more about why it’s so important to test your audience prior to launching your campaign.

A Quick Recap: Understanding Your Audience

As we’ve mentioned before, knowing your audience and why you’re targeting them is a great way to avoid frustration when communicating with and advertising to your market. When you properly use your audience data, you can make better choices for your marketing plan. Here are some key areas you’ll want to assess when determining who and where you’ll sample from.

  • Consumer Behavior: How are people buying and using your goods and services?
  • Demographics: Who exactly is your target customer? Characteristics to narrow down include age, gender, race/ethnicity, household income, education level, marital status, and geographic location.
  • Psychographics: Introduced in 2016, psychographics is the study of consumers based on their activities, interest, and opinions.

With these three areas identified, you can identify your market(s). Then, it’s time to select the best method of sampling for your audience.

Probability Sampling

Probability sampling follows two rules. Everyone within the population you’re pulling from must have an equal chance of being selected, and it’s imperative that you know what the chance of any one person being selected is.

With those basics set, here is a brief overview of 4 types of probability sampling you may encounter.

  • Simple Random Sampling is as it sounds. It’s a sample where anyone in the population has an equal chance of being selected.
  • Systematic Sampling uses a predetermined interval to choose members of a population to represent a sample.
  • Cluster Sampling divides the population into smaller portions – clusters – to make a random selection within each.
  • Stratified Sampling divides the population into mutually exclusive subgroups – referred to as strata – based on previously acquired data.

Non-Probability Sampling

On the other hand, non–probability sampling uses specific criteria – such as availability or geographic information – to identify a population before narrowing down the population size. Unlike probability sampling, each person within the target population doesn’t have to have an equal chance of being selected. With non-probability sampling, you take a small portion of your target audience and see what they like and dislike based on laid-out parameters.

  • Convenience Sampling is done at the convenience of the researcher. Some example factors for identifying your sample group include location, ease of access, and existing contact within the population of interest.
  • Snowball Sampling, also known as chain/network sampling, is defined by the way new units are added to the sample by referrals from a base group of participants.
  • Purposive (Judgmental) Sampling runs a high risk of running into research biases. The population sampled only includes those characteristics that you are inherently looking for.
  • Quota Sampling is, of all the sampling methods we’ve laid out, the one we’d recommend . We’ll explain this in more detail in the paragraph below.

Quota vs. Stratified

It’s important to define the distinction between stratified sampling and quota sampling because – at face value – the two are extremely similar. Both focus on dividing the population into subgroups and then selecting a certain number of units from each. However, the key difference is that stratified sampling relies on an additional random sampling technique like cluster or simple random. While – put simply – quota sampling involves selecting a predetermined number prior to evaluating your sample population. We advise quota sampling because it’ s more time- and cost-effective. When used, it provides a great deal of insight into how an overall market will perform (and at a fraction of the cost of sampling an entire population).

Why Sample?

With 74% of consumers annoyed by irrelevant marketing, it’s important to make sure your campaigns remain fresh and relevant to your target audience. Analyzing the data you received from sampling allows for creative optimization based on your key demographic. Knowing what your audience is looking for, what they like to see, and where they’re coming from “tells stories about customer intentions and motivations. Consumer insights are key to building creative campaigns that speak to and resonate with your audience and potential customers.” There’s also the element of personalization that allows you to address the specific inquiries or needs of your potential and current customers.

How Does it Work?

Let’s say, for example, that you’re a grocery in Southeastern Pennsylvania, and you’re seeking to connect with new movers. In theory, you could get the demographic data for your region and make assumptions based on the information provided. The marketing team could then send out two print mailers – a brochure and a postcard, to everyone in the market, and gauge which piece received better feedback through tracking coupons or QR codes. However, not only would that be a large amount of collateral, but the cost could also be exorbitant to get all those pieces in front of customers without really knowing if they’d respond to either at all.

This is where quota sampling comes in handy. Defining your subgroup (for example, moved into the zip code within the last 6 months, age 21-65, median income), and selecting the number of units to mail out before launching your campaign is key.  As those groups begin to shop at your stores, you can track how they found you, using coupon redemption or QR codes, and once this data is received, you can determine which mailer had the better ROI. With all of this information, you can begin a more informed rollout for the rest of your campaign.

We highly recommend quota sampling to help better inform your marketing tactics. If you’re not sure where to start, no problem. You can contact us today to get started on your next marketing campaign, and we’ll work with you every step of the way.

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