By Lisa Schreiber, Ph.D. and Morgan Hartranft
Millersville University, Millersville, PA
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
- List techniques for analyzing a specific target audience.
- Explain audience analysis by direct observation.
- Describe audience analysis by inference.
- Identify the purpose of a basic questionnaire.
- Recognize and apply data sampling.
- Determine when to use a Likert-type test.
- Define the five categories of audience analysis.
- Summarize the purpose of the situational analysis.
- Explain audience analysis by demography.
- Recognize the difference between beliefs, attitudes and values.
- Identify reasons for sampling a multicultural audience.
- Apply the chapter concepts in final questions and activities.
Chapter Outline
- Introduction
- Approaches to Audience Analysis
- Direct Observation
- Inference
- Sampling
- Models of Communication
- Linear
- Transactional
- Categories of Audience Analysis
- Situational Analysis
- Demographic Analysis
- Psychological Analysis
- Multicultural Analysis
- Interest and Knowledge Analysis
- Conclusion
- Review Questions and Activities
- Glossary
- References
Introduction
Robert E. Mullins, a well-known local bank officer, was preparing a speech for the Rotary Club in Dallas, Texas on the topic of “finding the right loan” for a rather diverse audience. He knew his topic extremely well, had put a lot of hard work into his research, and had his visual aids completely in order. One of the things he had not fully considered, however, was the audience to which he would be speaking. On the day of the presentation, Mr. Mullins delivered a flawless speech on “secured” car and home loans, but the speech was not received particularly well. You see, on this particular week, a major segment of the audience consisted of the “Junior Rotarians” who wanted to hear about “personal savings accounts” and “college savings plans.” It was a critical error. Had Mr. Mullins considered the full nature and demographic makeup of his audience prior to the event, he might not have been received so poorly.
In contemporary public speaking, the audience that you are addressing is the entire reason you are giving the speech; accordingly, the audience is therefore the most important component of all speechmaking. It cannot be said often or more forcefully enough: know your audience! Knowing your audience—their beliefs, attitudes, age, education level, job functions, language, and culture—is the single most important aspect of developing your speech strategy and execution plan. Your audience isn’t just a passive group of people who come together by happenstance to listen to you. Your audience is assembled for a very real and significant reason: they want to hear what you have to say. So, be prepared.
Spectacular achievement is always preceded by unspectacular preparation. – Robert H. Schuller
We analyze our audience because we want to discover information that will help create a bond between the speaker and the audience. We call this bond “identification.” Aristotle loosely called it “finding a common ground.” This isn’t a one-way process between the speaker and the audience; rather, it is a two-way transactional process. When you ask an audience to listen to your ideas, you are inviting them to come partway into your personal and professional experience as an expert speaker. And, in return, it is your responsibility and obligation to go partway into their experience as an audience. The more you know and understand about your audience and their psychological needs, the better you can prepare your speech and your enhanced confidence will reduce your own speaker anxiety.[1]
This chapter is dedicated to understanding how a speaker connects with an audience through audience analysis by direct observation, analysis by inference, and data collection.[2] In addition, this chapter explores the five categories of audience analysis: (1) the situational analysis, (2) the demographic analysis, (3) the psychological analysis, (4) the multicultural analysis, and (5) the topic interest and prior knowledge analysis.