A CASE STUDY: MIA

Let’s check back with Mia and see how she is integrating audience analysis into her speech preparation.

Over the first two days of speeches from other students, Mia noticed something interesting. Several students mentioned they were first-generation Americans, meaning that they were the children of immigrant parents. Mia decided to interview some of these classmates to find out how long ago their families had come to the United States and under what conditions. She was interested to know what challenges they had faced in coming here and what resources they used to overcome them. Although their parents’ journeys to America had preceded smartphones, the challenges they had to overcome were not all that different. Mia decided she would catalogue these challenges and how the families had solved them—and then show how a smartphone could be used to solve these challenges today.

Moreover, aware that every student in her class had a smartphone, Mia decided to interview five more audience members and ask them what apps or functions on their smartphones they used the most. Mia made careful notes of these functions (such as getting the weather, viewing maps, using social media) and began thinking about how this might compare with the ways refugees might use smartphones. In addition to helping her think about how to structure her speech, this also allowed her to create common ground with her audience: audience members would be more likely to understand and appreciate her speech because she was tying it to their own lives.

Look for the and throughout the chapter for adaptive quizzing and online video activities.

A CASE STUDY: JACOB

Let’s see how Jacob is using audience analysis in his speech preparation.

Jacob had a bad habit of arriving to class late. He tried to get there on time, but for some reason (late bus, delicious breakfast sandwich, etc.) he just couldn’t manage it. This meant that he was rarely there when his teacher took attendance. If he had been, he might have noticed that the names the teacher called in his class were mostly those of women. In fact, out of his class of thirty-two students, twenty were women. He might have observed this fact during the rest of class, but between taking notes and surfing the web on his laptop, he didn’t notice. Furthermore, six of the twenty women in his class were in fact college athletes: two were basketball players, one was a volleyball player, one was a hockey player, and two were swimmers.

As he built his speech, Jacob divided the different seasonal sports between “revenue-producing sports” and “the rest,” which were paid for by the dollars generated by the revenue-producing sports. It didn’t cross his mind that many of the women in his audience might interpret the phrase “revenue-producing sports” as code for men’s basketball and football—and that it might imply that women’s sports couldn’t generate revenue or fan interest. Worse, he failed to use examples that included women’s sports as he described how college athletes were exploited. Audience analysis should ideally include all the audience—or at least most. With twenty women out of thirty-two students in the class, Jacob was ignoring more than 60 percent of his audience!

Look for the and throughout the chapter for adaptive quizzing and online video activities.