Introduction: Why the Base Rate Fallacy Still Skews Market Research Results

It is widely believed that every human is entitled to their own opinion and they see things and life in general from different perspectives. Everyone uses their own suitable yardstick to measure things or situations around them. You wouldn’t want to tell people that their point of view isn’t right because they have a full right to their own opinion either through their thinking and comprehension level.

Base rate fallacy bias has a very huge tendency to skew research because research demands for an honest opinion or response in a bid to expand or improve an existing knowledge or offer better products and services but in the light of people placing what they think is more important or specific over the generalised notion or result. This subtle act through their responses to survey questions, interviews or any other research method adopted could sabotage the end result of a research. This bias is a social occurrence that deals in social cognitive and social psychological perception. It tends to place personal belief or perspective of how things are rather than the obvious or general result which is backed up by long term fact or information.

This bias which is also known as base rate neglect is a type of thinking error when respondents ignore statistical information called base rate and focus only on specific details they choose.

What Is the Base Rate Fallacy in Simple Terms

Oxford dictionary termed the word fallacy to mean a mistaken belief , especially one based on unsound argument. In layman terms, base rate fallacy means the act of choosing more specific information rather than what is true about the subject. Additionally, base rate fallacy is also known as base rate bias or base rate neglect. This bias tends to ignore general statistics even when they matter more.

For example: imagine you hear that a person is quiet, works alone and reads books so you assume they are a librarian but if you forget there are way more teachers than librarians, you might make a wrong guess. Another example is a medical test that gives a positive result for a rare disease, if the disease is uncommon, the result might be wrong even if the test is actually correct.

How the Base Rate Fallacy Shows Up in Surveys and Customer Data

Surveys are conducted to get an overview of a subject, product or services and this can’t be carried out without human resources. In gathering customers data, research methods would be adopted and this could be in the form of surveys, interviews, questionnaires and other used methods.

Base rate fallacy reflects in surveys and customers data in the following ways:

• Respondent response: It is important to know that base rate bias focuses more on the specific information about a subject than the generalized result. If a survey is carried out on a health related products, if 1 in 100 persons used a particular product and it works, a few others might tend to focus on the review of that one person while negating the aspect of the same drug won’t birth the same result for all users because the usage dose is different for each ages.
• Overreport personal experience: Placing the specific view of a product rather than the generalized result can result in survey data distortion because a researcher would be more focused on the result of its survey data without knowing that base rate fallacy has been indoctrinated by the respondent while filling the survey questions.
• Inaccurate response: In a bid of giving a response in a survey, respondent who places emphasis on stereotype information rather than the base rate information would give a response in line with their perception through the stereotype information they held unto and this would reflect through inaccurate response to the expected response by the researcher.
• Stereotype sketches: Respondents in survey tend to ignore base rate probabilities rather while placing their focus on individualized information.
• Placing value on recent data: If respondents are given survey questions on recent news or events, they wouldn’t give a response from the base rate pov but rather from the recent data they heard.

How to Avoid the Base Rate Fallacy When Designing Surveys

To avoid base rate fallacy, it begins with the researchers’ preparedness using the best methods required towards achieving the desired result expected and also learn to identify things that point out base rate fallacy.

Researchers should put these listed measures in place in a bid to avoid base rate fallacy while designing their surveys:

• Prioritize general statistics over specific stats: Researchers should pay attention to the base rate information about the survey they want to carry out.
• Don’t jump to conclusions: In a bid to have detailed survey questions, avoid jumping to conclusions based on recent data or reports. Focus more on detailed long term data to derive your desired result.
• Detailed study of the survey plan: In carrying out a detailed survey and getting the desired result, it is important to take time to study the line of the survey you’re carrying out so as to get your desired result.
• Use natural frequencies: Don’t adopt the usage of percentage but rather use numerical data e.g ( 2 out of 200 instead of 2%).
• Probability usage: Don’t use recent data/fact in updating your probability but rather focus on using the base rate data/fact.
• Analyze and consider the whole context: Evaluate specific details that are within the context of the required population.
• Consult experts: Learning from people who have carried out such a research and have an in-depth understanding can help know things to lookout for in interpreting specific cases.
• Adopt the usage of Bayes’ rule: Bayes’ theorem predicts the probability of an occurrence based on the prior knowledge of situations related to the event. In using Bayes’ theorem, researchers should update current probabilities with new data instead of replacing the base rate with new data.

How to Analyze Survey Data Without Ignoring Base Rates

Analyzing Survey data isn’t a rush through process but one that requires carefulness and intentionality in getting the desired result. Researchers should note the following when creating their survey questions:

• Define your base rate: In analyzing your survey data, it is important to lay bare the base rate(past probability, existing data) of your research without overlooking its impact on your research outcome. This will help establish the intended result desired.
• Adopt the usage of natural occurrences instead of percentages: Don’t go about using 1% out of 100 rather use 1 out 100. Convert the percentage into real numerical data so it can be relatable for respondents while answering the survey questions.
• Reference historical data: Achieving 90 percent result in your survey without considering measuring the past historical stats can render your results invalid .
• Know your population: Researchers should ensure the demographic (age,sex, education) of the respondents fits into the scope of research being carried out.
• Specific groups: Researchers should identify the specific groups ignoring the base rate and opting for the recent trend.

Key Takeaways for Survey Creators and Market Researchers

No fisherman goes to the river without his equipment nor does a farmer go to the farm without its hole and cutlass. A farmer knows the right tool to use to plant, he also knows the right tools to use to harvest. Note, if he does not apply the required tactics and methods required, he will end up catching nothing.

Survey creators should note that in creating survey questions, there are a lot of factors that need to be considered while drafting or putting survey questions together. All of the required steps in curating detailed survey questions should not be negated by survey creators. This includes the right demographic,clear goals, simple and clear language, no use of ambiguous words and employ the required measure to draft your questions. Market researchers should understand the base rates of their target audience, don’t carry out your survey based on assumptions but rather use the base rate applicable to the designated population.

Conclusion

Remember if you do not know how to swim, you should not dive into the swimming pool so also if you’ve not mastered the swimming strokes, never risk it or else you will drown.

So also, researchers should not dive into a research project without checking into the pros and cons of the survey questions to be used. Maximal efforts should be inputted to get the desired result. Study fallacies that can hinder the effectiveness of your survey, pay attention to how to identify it and also eliminate any traces of it from your survey results. Do your due diligence and leave no stone unturned, invest your time and resources in prepping your materials and data in getting your desired result. Remember if you fail to plan, then you will plan to fail, do not overlook any tiny error, pay keen attention and do every adjustment necessary to derive your desired result.