Blog Post

Using Marketing Data to Assess Public Health Programming

Knowing how to interpret and apply research data is an important skill in public health marketing. Data can help to inform marketers of the success of their programming by using simple statistical tools, such as a paired t-test looking at pre- and post-intervention data. The ability to show the success of programming will help to inform stakeholders and justify campaign expansion.

For example, you work for a chain of retirement communities and there is an STI outbreak at one of the campuses. It would be wise to survey the population before and after a ‘safer sex’ campaign to determine its effectiveness and if it should be implemented on all of the campuses.

Communicating the effectiveness of a public health campaign to stakeholders is critical in maintaining and expanding programming. The ability to understand and apply marketing data can improve your odds of winning stakeholders over.

Blog Post

Surveys and Experiments in Public Health Marketing

As a public health marketer, it is important to know when to run a market research survey or to run an experiment.

A market research survey  is often done as a first step in a marketing plan to gain baseline data from the target population. For example, if a health department was looking to find out the eating habits of middle schoolers in the county a survey would be appropriate.

A marketing experiment is generally done to fine tune messaging and to see what is most effective at persuading your target population. For example, if a health department wanted to find out which of two nutritional messages middle schoolers preferred, a marketing experiment would be appropriate.

Both marketing surveys and experiments are important in the formation of public health marketing, and can improve the effectiveness of campaigns.

Blog Post

Sample Populations for Survey Data

When marketing in the healthcare sector it is important that messaging be both medically accurate and culturally appropriate. In order to ensure your messaging is received well it is helpful to survey your client base regarding their knowledge and comfort level surrounding the topic.

A good sample will ensure that the data collected from your survey will give accurate results. It should be large enough to give statistically significant results but not so large as to create an oversample. Oversampling not only wastes resources but can also skew data by making it less reliable.

There are some instances where you may want to restrict who is able to take the survey in the first place. If a healthcare network is looking to expand its cervical cancer screening efforts, it would not make much sense to include cis-men in the sample. Instead you would want to have a screener question in the beginning to ensure that only eligible patients participate. 

Survey data can be very helpful for understanding your clients’ perspectives and experiences. And building an intentional and useful sample of your clients is an essential first step in getting accurate survey results.