Tags: DIY market research, consumer insight, online survey
In the Pinterest era, DIY solutions are available for virtually everything. DIY storage solutions, DIY website development, DIY home improvements, DIY wedding…and finally, DIY research.
“Re: We want your opinion!”
Everyone’s received an email with a similar subject line at some point or another. For all companies, research is the foundation of a strong business plan, but for many, the costs of professional research can be prohibitive. With today’s evolving technology, self-served market research and market intelligence-gathering have become all the craze, especially with the ever-increasing number of tool options available for consumers and businesses to conduct market research on their own.
The wide availability of information and tools on the Internet can offer quick solutions, gathering market feedback with minimal cost and minimal turnaround time. On the flip side, most sources available on the Internet are designed to be simple and easy to use in order to ensure the products are scalable, and choosing simplicity over comprehensiveness may limit your market reach and the depth of your results. In other words, DIY is great for shedding light on the unknown to guide directional planning. But DIY research methods may not be comprehensive enough when it comes to strategizing about big investments.
If DIY research is inevitable, here is a checklist, brought to you by MineMR:
1. Am I talking to the right people?
Your sample composition impacts the type of feedback you’ll get. Your results are a representation of who you’ve included in your research, so watch out for any overrepresentation of a particular type of respondent, which can skew your results’ point of view.
The level of targeting in your research can also impact your results, so be careful about who you include in your research, depending on your specific goals. With a really broad sample, your results may be too diluted for impactful planning; on the other hand, a sample set that is too narrow may thwart an opportunity to discover new or overlooked customer prospects.
2. Do I have the right number of respondents for what I need?
Your sample size impacts the margin of error of your results. Market research uses a subset of the population to understand real-world market potential, and when you do not have a big enough sample, your results could yield a higher margin of error. For instance, a sample size of 100 has a margin of error of 9.8%, at a statistical confidence level of 95%.
If you use a sample size that is too small, your results may prove unreliable as you delve deeper into your results among key subgroups of interest (e.g., examining your customer results by age group or location).
3. Am I asking the right questions?
Asking the wrong questions will give you the wrong answers. In addition, keep in mind that there isn’t one way to address your business objectives. Sometimes what best serves your goals are not questions at all, but rather, for instance, behavioral or in-the-moment data.
It’s helpful to start with the end goal in mind. You need to think about what you want to measure, how it’s going to be used, and by whom. After that, you can methodically design the questions or seek the metrics that will be most valuable to your end goal.
4. Am I asking questions in the right way?
The quality of a questionnaire dictates the outcome. How you ask the question, how you allow your respondents to answer, and the order in which they are asked questions could be potentially leading. Thus, inflate the results. The challenge with DIY design is ensuring neutrality and asking questions in a way that makes sense for the respondent.
Questions should help respondents to know what you need and to provide more accurate feedback. “How many times have you checked your email on your phone in the past week?” How would you answer that question? Keep in mind that some of us can barely recall what we did a couple of days ago. Alternative methods such as allocation exercises, usage diary, or a narrowed timeframe can more effectively draw the insights you need.
When respondents are given a list of answers to choose from, this can create a minefield of data skews. An incomplete list or a list without opt-out options (such as “other” or “none”) can force your respondent to choose an option that may not be most reflective of what he or she really means to say. What about language confusion? Industry jargon may go unnoticed for most of us, but to the people we serve, it could mean something else entirely or nothing at all. When in doubt, keep the language simple.
5. Is my research designed to answer the tasks at hand?
Envision a successful research project from all possible angles. Once you have a clear idea of what it would look like, think about how you can get there. For an A/B testing, you might want to create a survey with a sufficient sample to minimize the margin of error. But if you are interested in understanding emotions, you might want to conduct in-depth interviews to delve into the emotional drivers.
Also, make sure that you are using the right tool platform to reach the people you care about. While most online platforms capture a wide swath of the general population, it may nevertheless be limited in its reach to niche markets – for example, less-acculturated, elderly, or less tech-savvy consumers. Using the wrong method can bias results towards a point of view that is not representative of your target market.
6. Is my research telling me the full story?
Context gives meaning to your results. A critical aspect of market research is in data interpretation beyond the absolute value you see or feedback you hear. It is easy to spot the notable statistics at a total level. But the most actionable insights are usually derived from a driving force below surface level. Be obsessed with the whys. Persist in explaining them, and you will discover things that you may not have anticipated.
Also, be mindful of category seasonality. There are outside factors that may skew your results, such as the time in which research is conducted. For instance, if you are in retail, results you get before and after the holiday shopping season might vary drastically.
