3 common market research mistakes and their significance to you

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Posted Apr 05, 2023
Cory Long

We’ve said it before: Any successful business strategy is going to rely on market research to achieve it’s goals. But, even the most well-intentioned insights seekers can fall victim to all-too-common errors that can compromise the effectiveness and accuracy of their research. Indeed, we all make mistakes. But in this post, we thought it would be helpful to discuss three of the most prevalent market research mistakes we see when working with insights seekers. Our hope is to not only help you avoid this missteps, but also to console you if you’ve already made them. Again… we all make mistakes. It’s ok. But by being aware of these pitfalls, we can all become better insights seekers, build more illuminating research initiatives, and produce better business outcomes. But enough of the preamble—your time’s valuable—let’s just dive right in.

Mistake #1: Conducting research without clear objectives

We’re starting off with a bang here. We see this one quite a bit. But that’s because the prospect of data is just so dang exciting. Sometimes we’re blinded by it. So let’s just say this from the outset: Data and insights aren’t always the same thing. There’s this wild expectation placed on researchers today to leverage technology to collect all the data they can. But collecting data and turning it into actionable, digestible intelligence are two completely different things. Here are some things to consider:

You got a problem?

Starting a research project without clearly defining the research problem is like making a sandwich without bread. I mean, it can be done. It can even be tasty… but is it really a sandwich? When you don't clearly define the problem you're trying to solve, you may end up conducting research that doesn't really provide meaningful insights.

Questions, anyone?

Research questions are key to narrowing the scope of your study, allowing you to focus on the specific information you need to gain. Without clear research questions, your research runs the risk of becoming too broad or vague, leading to irrelevant or inaccurate findings. Defining clear research questions help ensure that the data collected is relevant to the study—and that can save you valuable time and resources.

Ultimately, this race to conduct research without clear objectives can lead to irrelevant, poorly targeted, and (ultimately) useless studies that are unable to aid stakeholders in making the informed business decisions they need to make. What we’re trying to say is that we realize it’s tough. Sometimes this mistake is hidden by the potential of what you COULD uncover. But by focusing on a problem and the questions you’re trying to answer, you can keep your studies focused, relevant, and geared towards providing valuable insights needed to guide your business decisions. 

Mistake #2: Poor sampling techniques and data quality

Ok, now let’s move into some more nuanced territory and talk about sampling techniques. If done poorly, sampling techniques can be a major stumbling block in market research—mainly because they have the potential to completely skew your results towards one particular segment of the target audience. 

The frequent buyer fallacy

One example of poor sampling techniques comes into play when we conduct a study that only surveys customers who are frequent buyers of a particular product. Seems like you’d get some good insights on these power users, right? Not so much, believe it or not. In reality, this can create a myopic understanding of the entire customer base and may exclude important perspectives that could offer insight. 

Thinking too small, are we?

Another mistake we often see is when researchers build a study where the sample size is simply too small. This can make it difficult to draw robust conclusions from the data collected, leading to a severe lack of confidence in the insights you’re aiming to generate. Not a lot to work with here, right? Probably not a great idea to base decisions on such a small sample. 

Value the opinions you get

This one is near and dear to our hearts. We believe (and it’s been proven time and time again) that inadequate compensation for survey participants can lead to disengaged respondents. You don’t want the folks taking their time to give you their thoughts rushing through the survey or providing you with inaccurate responses. That makes for bad data quality, which makes for misleading insights.

To err is human

To finish off this topic, we also want to mention that poor data quality can also be caused by technical issues such as data entry errors, inaccurate coding, or malfunctioning equipment. These errors can be difficult to detect and can lead to significant inaccuracies in the final result. Automation can be really helpful here. It can save you tons of time and tremendously reduce the risk of human error while speeding up data processing. 

Your sample is a critical component of your research. Poor sampling techniques will lead to poor data quality, and poor data quality will lead your research initiatives down a long trail of desperation and despair. But fear not! There is hope! With proper attention and care, sampling can be one of your most effective tools for generating meaningful insights. By leveraging technology, incentivizing respondents, and partnering with expert researchers, we’re certain you’ll be yielding valuable insights in no time!

Mistake #3: Inadequate research design

When we speak of inadequate research design, we’re mostly talking about the failure to create a research plan that accurately and effectively addresses research questions. We see it a lot, and it can lead to incomplete or irrelevant data collection, which (you guessed it) can lead to misguided decisions. This one sort of ties in with mistake number one a bit. Except, this is the knock-on effect of that mistake. Oops, you made a mistake that caused you to make this mistake… now let’s look at all the mistakes this can cause as a result. It’s sadistic, but it’s also significant. It’s sadistically significant!

Barking up the wrong tree

An inadequate research design can take many forms. A common one might involve asking the wrong questions, using the wrong research method. If you’re looking to understand why product sales are declining but you choose to ask consumers what color they prefer your new packaging, you’re not really going to get the answers you need. It’s a silly example, we know, but this also translates into your approach. Maybe you need to ask open ended questions instead of a narrowed set of options?

Your bias is showing

Another example of this is failing to account for any potential biases or confounding factors you as a researcher might be bringing into the study. Does your survey include leading questions? Have you failed to take into account some of your respondents’ broader context or culture? That could sway your respondents towards certain answers.

Don’t go at it alone

We don’t wish this mistake on anyone, but don’t be the only person to review your study before you launch. Expert researchers aren’t off the hook here! It’s totally possible that you, in your infinite wisdom, have begun to rely too heavily on your past experiences and assumptions without fully considering the unique needs and goals of the current project. It’s very possible you could have also overlooked the important details or failed to ask critical questions during the planning phase. I mean, you’re only human! 

Our advice with this mistake is to try and involve multiple stakeholders in the research planning process. This can include subject matter experts, data analysts, and other relevant team members. But it can also mean pulling in a third-party partner for a gut-check! By incorporating diverse perspectives and expertise, the research plan is more likely to be comprehensive, effective, and unbiased.

Now go forth!

So there we have it, folks. Listen, the way we see it, if you can avoid these mistakes, you’re already well on your way to research success. Remember to set clear objectives—keeping in mind the problem you’re trying to solve and the questions you’re looking to answer. Remember to consider your audience carefully and intentionally when selecting your sample—you want to make sure this doesn’t skew your results. And finally, remember that  adequate  research design is key to ensuring you generate  accurate, relevant, and valuable insights—getting a second opinion on how you’ve designed your approach can be invaluable.

And partnering with aytm can help you with all that and more. We can consult with you from the outset to help frame your research initiatives to launch successful studies, and then iterate and scale your research to build your insights engine effectively. Our platform can also help you pinpoint the right sample and build a dynamic audience, so you can be sure you’re reaching the consumers you need to target. Finally, we can lend a hand at any phase of your research design—whether it’s advising you on methodology or giving you a gut check before you launch. So if we can be of service, don’t hesitate to reach out.

Interested in learning more on your own? We have all kinds of resources available to help you learn.

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