Marketing research is a powerful tool for any business that wants to stay competitive. It can help you understand what customers think of your brand, how they feel about your products, which new markets you should expand into, and much more.
But when it comes to market research, many companies make the same mistakes over and over again.
After all, the field of marketing research isn’t exactly easy to navigate. Here are some of the most common complaints from marketing researchers and how you can avoid them in order to produce high-quality insights for your team:
Key Takeaways |
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1. Identify and address biased sampling to ensure representative data. |
2. Implement robust data analysis techniques to avoid misinterpretation. |
3. Choose appropriate research methodologies for accurate insights. |
4. Integrate storytelling to enhance engagement and convey findings effectively. |
5. Explore alternative research methods for comprehensive insights. |
6. Align research insights with marketing strategies for better decision-making. |
7. Mitigate bias by using random sampling and unbiased survey questions. |
8. Employ diverse recruitment strategies to counteract potential bias. |
9. Apply statistical techniques like weighting to correct data imbalances. |
10. Continuously refine the research process based on feedback and results. |
1. Precision
Precision is the ability to measure the same thing consistently. It’s important because marketing research can help you understand your customers better, which leads to better marketing decisions.
But without precision, you may end up making assumptions that are not accurate or helpful.
For example, if a customer says in one survey that they like listening to music while working out at the gym, but then says in another survey that they don’t care about music when working out at the gym which one do you believe?
The answer is neither! Both responses could be true for different people in different situations, so it’s best not to rely on any one response as gospel truth unless there’s strong evidence backing it up (like surveys with open-ended questions).
Here are some ways to improve precision:
Use multiple sources of data both qualitative and quantitative to verify findings from each source independently before looking for patterns between them
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2. Measurement
Measurement is important but only if it’s accurate. For example, if you want to measure the effectiveness of your marketing campaigns, you can’t simply look at how many viewers watched your commercial: you need to know how many picked up the product afterward.
This isn’t always easy to do in practice some metrics are more useful than others.
For example, “awareness of a brand” may seem like a good metric for measuring success, but it can be hard to tie that information back to sales figures or other measures of success (like customer retention).
On top of this problem with measurement comes another big issue: finding out whether or not your findings are statistically significant (meaning they aren’t just random chance).
This requires a form of hypothesis testing called t-tests and ANOVA tests (depending on what type of data you have), which we’ve covered in detail here
3. Hypothesis Testing
Hypothesis testing is a method of statistical inference for testing the validity of a hypothesis. It is used to determine whether or not an observed difference between two sets of data could be due to chance.
Hypothesis testing is similar to other forms of statistical analysis, such as univariate analysis and regression analysis, but it differs in its focus on determining whether or not something can be assumed true with a certain degree of certainty.
A hypothesis test provides evidence against the null hypothesis that there are no differences between groups or variables being compared (for example: “There will be no difference between the average number of hours worked per week by men and women.”)
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4. Control Groups
Control groups are used to compare results against a standard. Control groups can be used to test for bias, accuracy, validity, reliability, and consistency.
Bias: A control group helps determine whether or not one group is showing more positive results than another group because of an outside influence.
For example, if you have a product that’s already popular in the market and you’re trying to test it out with your target audience (e.g., males aged 18-25).
Then there may be bias in your data because they’ve already heard of it and could be biased by their own experience with the product/service.
By using a control group (e .g., males aged 18-25) who have never heard about this product before as well as comparing their responses against those who did know about it beforehand.
It will allow you to understand how much impact exposure had on these individuals’ attitudes towards this particular product/service overall since everyone’s feedback was collected under similar conditions (i.e., knowing nothing about what they were doing).
5. Inappropriate Statistics
Inappropriate statistics are those that do not answer the question you have set out to answer. If a hypothesis is your test of whether or not you can conclude something about the population, then using statistics incorrectly means you’ll get an inaccurate result.
The most common way this happens is by drawing incorrect conclusions from statistical tests used on data samples with large variances (for example, in a survey of 100 people, one person may be very atypical).
Another way inappropriate statistics happen is when they are used inappropriately. For example, many different types of tests can be done on data samples: significance tests that compare two means (one might assume they’re equal).
Regression analyses look at how one variable changes over time as others change (like determining what effect advertising has on sales).
Chi-square tests determine whether there’s any relationship between two variables at all (which may seem like it depends on previous relationships but just tells us about independence).
Each test uses its assumptions about how populations behave and we need to remember these assumptions when interpreting results!
The final third reason inappropriate statistics happen is that we use them without considering other factors in our environments that could affect our results or even worse than this mistake: using them to prove something instead of disproving something!
Statistics don’t prove anything; they simply show us relationships between variables so we can conclude them based upon what else we know about those variables’ interactions with each other and/or ourselves.”
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6. Ignoring The Market, The Competition, And Brand Relationships
In today’s competitive markets and competitive industries, it’s vital that you understand your market and how it works. You need to know what makes them tick, and what they think of the competition and brands in their industry.
When conducting market research, most companies will take a very broad look at their target audience by asking questions like “Who are our customers?” or “What do they want?”
These types of questions tend to be too general as they don’t ask anything specific about each customer’s needs or preferences. Instead, you should ask more detailed questions such as “What type of car do you drive?” or “How often do you have dinner at restaurants?”
These more specific questions allow for a better understanding of your target audience because they reveal details about the lifestyle and needs under consideration (i.e., whether someone drives a sports car versus an SUV).
When doing competitor analysis or brand tracking studies with customers, some businesses still fail to explore these relationships in any significant way beyond basic demographics (age/gender) which can be misleading when trying to understand how consumers think about competitors/brands within an industry context.
It is also important for marketers not only to look at how customers perceive competitors but also themselves relative to other products in their categories; this reveals whether there is room for improvement on certain aspects like price value proposition etc…
7. Generalizations From A Single Case
The first and most important thing you can do to avoid making generalizations from a single case is to collect more than one example.
If you’re collecting data from customers, find three or four of them. If you’re trying to understand your target audience, including at least two different types of people in their 20s, 30s, and 40+ age groups.
Similarly, if you have some quantitative measures of customers’ attitudes toward your brand or products (e.g., Net Promoter Score).
Run multiple surveys using different questions and scales; don’t just use the same survey every time because it makes things easier on yourself! This will help prevent spurious correlations that are due entirely to chance.
For example, You might find that customer satisfaction scores correlate positively with loyalty rates but only if your sample size is big enough!
8. Relying On One Method Of Market Research
Relying on one method of market research is a dangerous game. The more you’re able to use, the better you will understand your customers and their needs.
Consider these examples:
Focus Groups
This is an effective way of getting feedback from consumers in person, but it can be difficult for larger companies that don’t have the resources to host or monitor focus groups regularly.
Online Surveys
These are easy and cost-effective tools that allow you to collect data from thousands of people at once, but they often don’t provide as much insight into your customers as watching them interact with your product in real life.
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Customer Satisfaction Surveys
These are great for identifying problems with your product or service before they become too big to handle, but they are not very useful at determining what exactly needs fixing if there isn’t already something wrong with it!
9. Self-Reporting
Self-reporting is one of the most popular ways to collect data. It can be a great way to gather qualitative information, but it’s not as reliable or objective as you might think.
People may not always be honest with themselves or others, and they may not know the answer, even if they’re trying their best.
They may also have trouble remembering what happened in the past, or understanding exactly what you mean when asking them questions about something that happened in their lives.
In addition to these potential problems with self-reporting:
If you ask someone if they’ve done something before and then ask them how often they do it again for example “Have you ever eaten at McDonald’s?” followed by “How often do you eat at McDonald’s?”
They might say “yes” both times because there are different definitions for “eaten” (eating some fries once doesn’t count). To avoid this confusion in surveys, use closed-ended questions whenever possible and avoid using open-ended questions where possible
10. Bias In Sampling
Bias in sampling can occur when the sample is not representative of the population. In this case, your results may be inaccurate and useless. There are several ways to reduce bias in sampling:
Use probability sampling where possible (e.g., random selection). This will ensure that each element has an equal chance of being selected for your research study.
Where it’s not possible or practical to use probability sampling, then use stratified random selection (e.g., census data).
Stratified random samples are more likely than simple random samples to produce results that are representative of the wider population.
Because they take into account variations within different subgroups or segments within your target audience group e.g., gender, age group, geographic location etcetera).
11. Inaccurate Scales Or Tracks
Inaccurate scales or tracks are often a result of not taking into account the full range of your data when designing your scale.
For example, if you’re measuring respondents’ satisfaction with a product and have only three categories to choose from: “dislike very much”, “like very much” and “neither like nor dislike.”
Then you may end up with a lot more people selecting one of the former two options than the latter.
The way around this is to make sure that all responses are included in your scale design by adding an extra category at both ends (e.g., ‘hate very much’ and ‘love very much) so that no one feels they have missed out on giving their true opinion.
To test how well measured something is by asking people how likely they would be to buy something on a scale from 0-10 (where 0 means never and 10 means definitely).
If most people give answers between 4-7 then there is probably something wrong with either how sensitively designed question was or just how accurate these kinds of measurements can be!
12. Outdated Data Collection Methods And Technology
If you’re relying on old data collection methods and technology, it’s time to upgrade. Your research may be accurate enough for basic analysis.
But if you want to create meaningful reports that can help your business make smart decisions going forward, then it needs to be more accurate than “good enough.”
Some of the most important reasons why outdated methods should be updated include:
- Increased accuracy more modern methods are simply better at getting accurate results from customers than older ones
- Reduced cost modern tools are cheaper than traditional ones (and can even save money)
- Improved speed the faster that you can get data back from your customers, the faster you can act on it
13. Confusing Advertising Research With Sales Forecasting
If you’re not a big fan of mathematics, you’re in luck. You don’t have to do it yourself you can hire someone else to do it for you.
That’s right, hiring a sales expert or business analyst is the easiest way to get your sales forecasts done quickly and accurately.
The most important thing when looking for someone is finding someone who understands how your industry works and has experience with estimating sales figures based on trends and market data.
They should also be able to work closely with marketing experts so that they understand what kind of information will help create accurate forecasts.
Embracing the true challenges of marketing research can yield insights beyond the surface. Navigate the complexities by reading about the inconvenient truth of marketing research – a deeper exploration that complements your exploration of research flaws and their remedies.
14. Ignoring The Importance Of Cultural Differences In Consumer Behavior And Attitudes Across Countries And Regions
Cultural differences are a major barrier to understanding consumers. They can make it difficult to predict their behaviors, attitudes, and preferences.
You need to take into account cultural differences when conducting your market research, so you can get a clearer idea of how your product or service will be received by different markets around the world.
Research is not sales forecasting! A good survey won’t tell you how well your product will sell in another country.
Only whether people would buy it if they were given the chance (which isn’t exactly what matters most). It also won’t tell you when they might buy it: having a follow-through plan after your research is crucial for marketing success abroad.
15. Lack Of Follow-Through On Insights Gained From Marketing Research Findings
The most important part of a marketing research project is the follow-through on insights gained from findings. Without action, all the work you put into your research will be for nothing.
But how can you keep yourself accountable? How do you get started with implementation? How can you sustain the effort over time and measure progress toward achieving your goals? The answer lies in making sure there’s a habit built around marketing research.
So it becomes a regular part of your routine, whether that’s every day or once per quarter.
Conclusion
Marketing research is a vital tool for the modern marketer. It helps us understand our audience, tailor our message to their needs, and build long-lasting relationships with them. But it’s not always easy to get it right.
A lot of marketers rely on their gut instinct when making decisions about marketing research or don’t know how to interpret the results they get back from studies. This can lead to bad decisions that don’t reflect reality and that’s why we need better ways of doing things
Further Reading
Here are some additional resources that delve deeper into the challenges and solutions in the field of market research:
The Problem with the Market Research Industry and How to Fix It Short Description: Explore the prevailing issues within the market research industry and discover actionable strategies to address and resolve these challenges.
Top 5 Market Research Problems and Solutions Short Description: Learn about the top market research challenges faced by professionals and explore innovative solutions to overcome them effectively.
11 Expert Tips for Conducting Better Market Research Short Description: Gain insights from industry experts on how to enhance your market research endeavors and elevate the quality of your findings.
FAQs
What are the key flaws in marketing research and how can they be addressed?
The key flaws in marketing research often revolve around biased sampling, inadequate data interpretation, and insufficient research methodologies. To address these, ensure diverse and representative samples, apply rigorous data analysis techniques, and choose suitable research methodologies for each study.
How can storytelling be integrated into marketing research to improve insights?
Storytelling in marketing research can be a powerful tool to engage respondents and convey complex data effectively. By crafting compelling narratives around research findings, you can enhance the impact of your insights and make them more relatable to stakeholders.
What are some alternative methods for conducting market research?
Alternative methods in market research include ethnographic studies, social media sentiment analysis, and user experience testing. These approaches provide unique perspectives and deeper insights that can counteract some of the limitations of traditional research methods.
How can I make better marketing decisions based on research findings?
Making better marketing decisions involves not only analyzing research findings but also considering their implications in the context of your business goals. Align the insights with your marketing strategies and test different approaches to refine your decision-making process over time.
What strategies can be employed to address the challenges of bias in market research?
To mitigate bias in market research, employ random sampling techniques, use unbiased survey questions, and implement diverse recruitment strategies. Additionally, applying statistical techniques like weighting can help correct for potential bias in the collected data.
Costantine Edward is a digital marketing expert, freelance writer, and entrepreneur who helps people attain financial freedom. I’ve been working in marketing since I was 18 years old and have managed to build a successful career doing what I love.