Quantitative research is considered the "gold standard" because it uses strict methodologies like experiments, surveys, and statistics to objectively measure phenomena with large random samples and eliminate bias. This allows quantitative research to draw conclusions about entire populations and test hypotheses in a controlled, repeatable manner. In contrast, qualitative research uses smaller samples and open-ended tools that can introduce more subjective researcher and participant bias and do not aim to generalize findings.

1. A basic decision to take before starting any research exercise is to decide whether to go for a
quantitative research or qualitative research. In a lay man terms, quantitative research is the
method employed for measuring anything whereas qualitative research deals with the
description and in depth analysis of a particular subject. Therefore, it can be easily inferred
that quantitative research methods include numbers, proportions and statistics and qualitative
methods include quotes, description and explanations pertaining to different phenomena’s. It
has been observed that both of these methodologies have been used simultaneously in the
research process.
An important question that arises while a research is being carried out is the scope and
dimensions of required research. Quantitative methods usually have an edge over qualitative
methods as they involve a huge, random sample (which erases biases) and also take into
consideration various dimensions (variables affecting the test environment). Another
characteristic of quantitative research is its focus on objectivity and identification of
important agents, their associations and co-relations e.g. a research survey of sales of a
particular product in some region will not only discover the role of certain factors (such as
pricing, trends, purchasing power) but will also establish the relational analysis between two
factors (like if price increases and purchasing power is kept constant, how will sales be
affected).
The central idea behind quantitative research is the division of different factors so that they
can be measured and modeled according to the rules of statistics and mathematics. These
models are generally free from factors (distortion) that might perturb the flow and direction
of research. A researcher has a very clear picture of the thing that is to be accounted for;
therefore, testing and experiments follow strict controls and regulations. The process is
clearly monitored and as the process can be repeated several times, the chances of getting
concordant results are very high. On the other hand, qualitative research don’t provide such

2. strict controls and since the researcher is unaware of his goal (which is not pre-determined),
there is a very high probability of him going off-track. The nature of qualitative research is
such that it will always lead to non-conclusive results and not to precise results which will
surely affect the decision making practice.
Quantitative tools are meant to remove any bias and their results are always some sort of
numbers which can be subjugated to any sort of analysis and findings. There is only one truth
which is vigorously proven through different techniques and derivations. On the contrary,
qualitative tools are mostly open-ended and their results are specific texts describing one
problem area. Qualitative tools fail to recognise general tools and pattern and therefore, they
cannot be assigned to whole population for analysis.
Being indifferent to emotions, cultures, values and traits is a key aspect of quantitative
research coupled with the removal of researched bias. A researcher cannot bring any bias as
tested models won’t accommodate any changes. Perversely, researcher bias and information
collection bias is very evident in qualitative research.
Quantitative research has a special application in product development and marketing
research as it’s used for confirming findings and concluding results. For example, customer
visits can be conducted which may result in revealing some unmet needs of customers. Then,
a larger group of customers can be surveyed with specific inputs on particular aspects of the
product. This will help you catch the factor that is the cause of concern.
In its true sense, quantitative research looks to focus on how people think, act or feel about a
particular thing as opposed to why they think, act or feel about the same thing. This sort of
research encompasses huge sample sizes often peaking to 100k respondents (example is AC
Nielsen’s Survey). This sample can constitute of respondents belonging to different cultures
and customs but they are asked same series of questions to maintain consistency and

3. coherency. These research studies often take the form of tightly couple closed-end
questionnaires for better statistical analysis (such as tally marking).
Some people fence that quantitative methods are victor than qualitative methods because of
the very reason that they are free from any sort of preconception. What it really means is the
fact that the results are very close to reality. Qualitative methods are full of biases and hence,
the obtained results may not depict the original picture. This leverage to include irrelevant
observations is highly undesirable in social and mathematical sciences. Another argument
that can arise is about the ‘flexibility’ of research. Qualitative researchers, without doubts
tend to be more innovative and flexible but this idea is actually not supported as flexibility
often leads to risk and on average, every researcher is risk averse.
“Qualitative researchers still largely feel themselves to be second-class citizens whose work
typically evokes suspicion, where the ‘gold standard’ is quantitative research.”
An explanation to why quantitative research is termed as gold standard can be the fact that it
comprises of five tried and tested methods that include social surveys, controlled
experiments, official statistics, structured ethnographies and content analysis. A very good
example would be a survey of a product sales and competitors product. The independent
variable would be the competitor’s product and the product sales would be a dependent
variable relying on the performance of competitor’s product in the same area. The findings of
such a study can be put into a table and a graph can also be plotted for dependent variable
against the independent one. The researcher can achieve confidence by surveying at least 100
customers of the Wal-Mart store in the proximity and also analyze the correlation if it exists
between the factors taken under consideration. Quantitative researchers don’t make causal
statements until and unless they have tested all possible hypotheses on every factor. In our

4. example, product sales may not have dependent only on competitor’s performance but also
on pricing and advertising of product.
One can easily deduce from the above discussion that quantitative research is an appropriate
method of finalising results and approving or disapproving an already formulated hypothesis.
For this very reason, quantitative methods have been standardised and are widely used in
industries and organisations. Analysis and studies of results leads to comprehensive findings
which may be published and legally discussed. External and internal diagonals are normally
filtered out from the system which establishes the authenticity of results.