Final answer:
A/B testing is a true and effective method a company uses before running a campaign to compare different characteristics of ads. It involves collecting data, forming hypotheses, and testing them through experiments. Larger sample sizes improve the reliability of such experiments.
Step-by-step explanation:
The statement is true: prior to running a campaign, a company should indeed test different characteristics in the ad and copy to determine the most effective one. This process is known as A/B testing. A/B testing involves the following steps:
- Collecting and organizing data: This is crucial as you need baseline data to compare the results of your A/B tests.
- Making a hypothesis: Based on the initial data, the company would make an educated guess on which version of the ad might perform better.
- Testing a hypothesis by experiment: The company would run the two ad versions (A and B) to see which performs better in terms of consumer response.
- If the initial hypothesis is rejected, the company may need to reject the old hypothesis and make a new one, leading to further tests.
When testing products like a new laundry detergent, the experiment involves a scientific process where the hypothesis is involving the preference over a competitor brand. Moreover, experiments can indeed be conducted on humans, provided ethical guidelines and regulations are followed. Also, larger sample sizes in scientific experiments tend to give more reliable results than smaller ones.