Exploratory research is an important part of any marketing or business strategy. Its focus is on the discovery of ideas and insights as opposed to collecting statistically accurate data.
That is why exploratory research is best suited as the beginning of your total research plan. It is most commonly used for further defining company issues, areas for potential growth, alternative courses of action, and prioritizing areas that require statistical research.
When it comes to online surveys, the most common example of exploratory research takes place in the form of open-ended questions. Think of the exploratory questions in your survey as expanding your understanding of the people you are surveying.
Text responses may not be statistically measureable, but they will give you richer quality information that can lead to the discovery of new initiatives or problems that should be addressed.
Descriptive research takes up the bulk of online surveying and is considered conclusive in nature due to its quantitative nature. Unlike exploratory research, descriptive research is preplanned and structured in design so the information collected can be statistically inferred on a population.
The main idea behind using this type of research is to better define an opinion, attitude, or behaviour held by a group of people on a given subject. Consider your everyday multiple choice question. Since there are predefined categories a respondent must choose from, it is considered descriptive research.
These questions will not give the unique insights on the issues like exploratory research would. Instead, grouping the responses into predetermined choices will provide statistically inferable data. Like descriptive research, causal research is quantitative in nature as well as preplanned and structured in design. For this reason, it is also considered conclusive research. Causal research differs in its attempt to explain the cause and effect relationship between variables.
This is opposed to the observational style of descriptive research, because it attempts to decipher whether a relationship is causal through experimentation. In the end, causal research will have two objectives: For example, a cereal brand owner wants to learn if they will receive more sales with their new cereal box design. Experiments are typically conducted in laboratories where many or all aspects of the experiment can be tightly controlled to avoid spurious results due to factors other than the hypothesized causative factor s.
Many studies in physics , for example, use this approach. Alternatively, field experiments can be performed, as with medical studies in which subjects may have a great many attributes that cannot be controlled for but in which at least the key hypothesized causative variables can be varied and some of the extraneous attributes can at least be measured. Field experiments also are sometimes used in economics , such as when two different groups of welfare recipients are given two alternative sets of incentives or opportunities to earn income and the resulting effect on their labor supply is investigated.
In areas such as economics , most empirical research is done on pre-existing data, often collected on a regular basis by a government. Multiple regression is a group of related statistical techniques that control for attempt to avoid spurious influence from various causative influences other than the ones being studied. If the data show sufficient variation in the hypothesized explanatory variable of interest, its effect if any upon the potentially influenced variable can be measured.
From Wikipedia, the free encyclopedia. There are two research methods for exploring the cause-and-effect relationship between variables: Experimentation [ edit ] Main article: Statistics and Regression analysis.
Market researchers utilize casual research designs to predict hypothetical scenarios and report their findings to companies so that they can alter their business plans accordingly, says Market Research World. One example of a casual research design is a marketer wanting to pinpoint why sales are low.
Causal research, also known as explanatory research is conducted in order to identify the extent and nature of cause-and-effect relationships. Causal research can be conducted in order to assess impacts of specific changes on existing norms, various processes etc.
The goal of causal research is to give proof that a particular relationship exists. From a company standpoint, if you want to verify that a strategy will work or be confident when identifying sources of an issue, causal research is the way to go. Definition of causal research: The investigation into an issue or topic that looks at the effect of one thing or variable on another. For example, causal research might be used in a business environment to quantify the effect that.
Causal Theory and Research Design Chapter 6 of The Craft of Political Research Chris Lawrence [email protected] Causal Theory and Research Design – p.1/ Causal research, also called explanatory research, is the investigation of (research into) cause-and-effect relationships. To determine causality, it is important to observe variation in the variable assumed to cause the change in the other variable(s), and then measure the changes in the other variable(s).