Causal Research: Definition | Advantages | Examples | Components
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  • Writer's pictureAnpar Research
    • Jan 21, 2022
    • 4 min read

Causal Research: Definition | Advantages | Examples | Components

Updated: Apr 2


Causal research shown on a light bulb, which serves as a symbol of great ideas

You may hear about the importance of causal research mentioned by others but what is it? What are the benefits? And what are the examples of causal research? These are all explained and more in this easy-to-follow article.


Table of contents:


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What is Causal Research?


Causal research is used in the latter stages of the decision-making process to establish whether there is a relationship between cause and effect of multiple variables on various marketing efforts such as a drop in price effecting demand of a product as there may be other factors at play that drive demand. Note causality is something that is probable rather than proved, so we can only infer a cause-and-effect relationship.


Causal research is usually employed to either test a hypothesis, determine the level of the relationship between causal variables and effect to be predicted or to understand which variables are the cause (independent variable) and which variables are the effect (dependent variables) of unique events in marketing.



Components of Causal Research


There are three key components that make up the evidence of a cause-and-effect relationship in causal research, these are:


1. Concomitant variation

Concomitant variation is when causality is implied if the extent of two variables to which cause (X) and effect (Y), occur or vary together, which was predicted by the hypothesis in question. Basically, these two variables need to be systematic for concomitant variation of causality to occur. For example, the hypothesis of low customer satisfaction having a negative effect on retention of customers and vice versa in keeping customers. However, if training is not provided to employees, then you cannot link this as a cause for variations in customer satisfaction.


2. Temporal sequence

Temporal sequence is when the cause occurs before the effect like an increase in sales after an advertising campaign. Although, if the advertising campaign took place after the rise in sales, then you cannot say the advertising is a cause as there may be other factors that are having an impact.


3. Non-Spurious association

Non-Spurious association is only valid when the two variables are correlated and there are no other variables that are linked to either the cause or effect. For example, the quality of the service may be a cause for retention for a company, if they are absolutely sure there are no changes to factors such as pricing, advertising, promotional offers, product features, competition and so on, which remain constant or controlled.


Advantages of Causal Research


1. Repetition

The benefit of repetition with causal research if it is required for a specific situation and will help you to understand what points to change in order to be successful.


2. Higher levels of validity

Higher level of validity can be achieved via causal research as the subjects are chosen systematically.


3. Helps to identify the causes in the process

In identifying what is behind the cause, you can take the necessary steps in resolving an issue or exploit an opportunity to the benefit of your business.


4. Identify the impact of any possible changes

Causal research will help you to recognise and understand the impact of any potential changes that are made to the process or methods of your business, so this will help you to plan accordingly for any future actions.



Disadvantages of Causal Research


1. Difficult to reach the right conclusion

Based on the results of causal research it may be difficult to come down to the right conclusion because there are many other variables and outside influences that may have contributed to the event. This could be technological, political or social factors. So causal research is more inferred rather than proven.


2. Coincidental in occurrence

An occurrence of a cause-and-effect relationship may be coincidental and be wrongly identified as an actual cause and effect relationship when it’s merely a coincidence such as correctly predicting the weather without access to the relevant information.


3. Determining which variable is the cause and which is the effect

Occasionally it may be difficult in research to determine which variable is the cause and which variable is the effect, so this can be challenging rather simply identifying two variables that are linked.


Examples of Causal Research


1. Track the ad effectiveness of a campaign

In tracking how effective your advertising campaign is going and checking whether or not to continue down the same path or change strategy. This can also serve as a learning for future campaigns.


2. Test the sales potential of new prices

Test how well different prices could be received by customers in their intent to purchase the product at a given price. This will allow you to work out the sales potential for each price and help you decide which one to go with. New products can be tested to see if they are a viable business proposition.


3. Measure the effects of a rebrand of a product

Measure the impact on customer loyalty and the effects it has on products when a rebranding program is applied.


4. Monitor the performance of employees

Analyse and monitor the performance of employees following a training program to acquire new skills or change in work processes have on employee’s motivation and productivity.


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