Convenience sampling, also known as grab, accidental, or opportunity sampling, is a type of non-probability sampling in which researchers choose participants solely on convenience. The user gathers samples from people in their proximity—at work, school, neighborhood, or gym, for example—and whether the sample is representative of a specific population is not a consideration. Let’s take a deeper look at this sampling method.
The main reason you might use convenience sampling is that it’s convenient! The only selection criteria for participants is that they are present and willing to participate. You could collect responses from friends, coworkers, social media users, people in the shopping mall, or anyone who meets your very narrow criteria.
The main advantages of using a convenience sample relate to its ease of use. That’s why it’s so attractive to those needing fast data.
Although there are drawbacks to convenience sampling, there are some clear instances where it is the best option for your research.
As we’ve discussed, convenience sampling is random, based only on proximity to the person conducting the research and willingness to participate in the survey. In simple random sampling, a probability sampling technique, individuals in a larger population each have a fair and equal chance of being selected for a smaller sample.
Convenience sampling relies on location and accessibility to determine the research variables. This makes it very difficult to replicate results. In simple random sampling, you select your ideal sample size and use a random or lottery-based method to choose variables. Because of how participants are chosen, the data collected by a simple random sample will represent the entire, more extensive population. The data is replicable, and validity is not an issue.
Simple random sampling eliminates bias with its specific method of selecting variables. Convenience sampling is open to bias, as the variables are up to the researcher’s discretion.
Convenience sampling is best used for pilot testing, hypothesis generation, or gathering information for more in-depth research. Simple random sampling is best used when you need data that provides context and generalizations about the larger population.
Keep these steps in mind as you conduct convenience sampling.
In probability-based sampling, you would set very specific parameters for your survey respondents, but with convenience sampling, you simply choose participants based on location. If you have an idea of your target audience, you can plan to go to locations where you are more likely to encounter those people. For example, if you are looking for opinions from college students, you’d go to a nearby campus.
Convenience sampling may be done in person, by telephone, or online. You can post your survey on a website, social media, or email it to your contacts. Depending on what your goal is, you can employ multiple methods.
Use both quantitative and qualitative questions in your survey. You’ll collect more useful data with a variety of question types. Ensure that your questions are clear, concise, and balanced.
Conduct your survey research using your chosen methods. Sort, filter, and analyze results and how they relate to your goals. You can choose to present your findings in a summary of all results, graphs of language or sentiment trends, or another way that meets your needs. Ensure that your analysis is presented in a way that connects back to your initial goals.
Repeat your research with new sampling to ensure the accuracy of your results. Add other research methods to clarify and supplement your convenience sampling-based research.
You may be wondering what occasions call for convenience sampling. Let’s take a look at several use cases.
A family restaurant is seeking people's opinions near its location on its updated menu. To gather data, the owner surveys a convenience sample in the local mall that’s known to attract families. The survey collectors stand near the food court and ask patrons to rank the new menu choices for the restaurant. The restaurant then uses the data to inform its menu changes.
A student in a doctoral program in engineering wants to identify a particular need for adaptive equipment for the elderly. He goes to an assisted living facility with his survey and asks residents for their thoughts and opinions on his ideas for equipment. From this, he can form a hypothesis and proceed with further research.
You’re seeking information to support the development of a new mobile phone app. You decide to use convenience sampling because you are looking for data to support your hypothesis that this will be a widely used application. You post a link to your survey on social media channels and email a link to coworkers asking them to participate. Before you invest, you can use this data as a stepping stone for more research.
Your company has just launched a new product. There is a launch event scheduled at a local media store. You station survey-takers outside the store to collect information about how people heard about the event, what they thought of specific parts of the event, and their thoughts on the new product. You use the gathered data to assess your marketing strategies and plan for future events and product development.
Convenience sampling is even used in medical studies, especially when speed is of the essence. For example, a study in early 2020 used convenience sampling to create symptom profiles for COVID-19.
Since one of the main limitations of convenience sampling is bias, let’s look at some ways to reduce the impact of bias in your convenience sample-based research.
As long as you aren’t looking to use a sample that is representative of an entire population, convenience sampling may be a valuable tool for easy research with fast results.
There are times when you need probability-based sampling, and while it takes longer, we can help make it quicker and easier with SurveyMonkey Audience.
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