Assessment scenario: In Strategic Message Design, an upper-level writing course, students identify target audiences and develop strategic messages for a real-life client. Initial brainstorming often leads student to select familiar or oversimplified audiences, but class time for deeper exploration with instructor input is limited. Learn how structured AI prompting exercises helped the instructor scale her ability to guide students to explore more complex audiences while practicing critical AI and information literacy skills.
Instructor: Mary Sterenberg
Department: School of Communication
Course: COMM 3334: Strategic Message Design
Contact: sterenberg.2@osu.edu
Course Details
- Format: Hybrid
- Typical enrollment: 40
- Instructional Staffing: One primary instructor
- Learning Context: Undergraduate Strategic Communication majors completing a core course or Communication majors taking an elective
Expected Learning Outcomes
- Apply class content for a deeper analysis of potential target audiences for a real client
- Gather and evaluate sources to support selection of an audience and effective messaging for the audience
Opportunity
Leveraging AI to explore more complex target audiences
This upper level writing course is designed to help students learn to develop key messages tailored to target audiences and organizational objectives. As part of this course, small groups of students work with real clients and identify new target audiences that could represent potential growth opportunities for the client and then develop strategic messages that appeal to those audiences. Through course content and full class discussion, students are exposed to a complex, multi-dimensional characterization of audiences in terms of demographics, psychographics, geography and consumer behavior.
In one group assignment, students researched their clients, brainstormed potential audience segments, and then used a research process to assess the viability of their top ideas. Student ideas on potential target audiences were often informed primarily by their own experiences or stereotypes and assumptions about a potential audience. For instance, students often picked an audience familiar to themselves, like “OSU students,” or picked the first target audience they brainstormed that seemed to potentially align with their client. Many of these audiences were oversimplified (i.e., women ages 25-40) or were not well aligned to help the client achieve its objectives (i.e., choosing "OSU students" as an audience for a bakery located in Hilliard).
There isn’t enough time for me to meet individually with each group to walk them through developing potential target audiences that are more aligned with their clients’ business objectives and or help them flesh out the more complete characterization of the audiences needed to create strategic and effective messaging. This left many potentially viable target audiences unexplored and limited students’ ability to analyze different ways to characterize audiences. It ultimately limited students’ strategic evaluation of potential messages for different types of audiences or audiences at different stages of their consumer journey.
I explored ways for using generative AI to help students achieve a richer analysis of the viability of more high-potential target audiences so they could ultimately develop messaging to influence those audiences and help clients achieve business objectives.
Change
Using structured AI prompts to promote deeper analysis of potential audiences
I pivoted to an in-class group exercise that used an instructor-designed sequence of prompts to guide students through a more structured, AI-assisted exploration of potential target audiences. Then each group member was assigned a target audience to complete an individual assignment in which they developed a consumer profile and at least two communications recommendations.
In-class group activity
Before prompting AI, students gathered public-facing information from their assigned real client’s website, social media accounts and customer reviews. They included those materials in an initial prompt, so the exploration was grounded in information specific to the client rather than beginning with a generic question about possible audiences. Each group then used the chatbot to explore a range of potential target audiences.
I designed prompts to help students conduct a more complete analysis, one that included attention to not only demographics but also psychographics, geography and consumer behavior.
I also included prompts that helped students consider what stage of life customers might be in when they need this product/service, what events or transitions might cause someone to become a customer, and what potential customers may be underserved by competitors in the client’s market. Students customized my prompts with information about their client and then selected and adapted follow-up questions that were most useful for exploring that client’s potential audiences.
While they conversed with a chatbot, I walked around and talked to groups in class about target audiences they were considering as a result of the AI responses and why they hadn’t thought about those audiences or whether the audiences had strong potential for their clients.
After completing the in-class AI exploration, each group submitted screenshots or notes about the conversation and a list of potential target audiences, with a different audience assigned to each group member for an individual follow-up assignment.
Individual assignment
In the individual assignment, each student conducted a deeper analysis of their assigned audience, beginning again with AI, to better understand demographic, psychographic, behavioral and geographic characteristics of their target audience as well as needs or pain points, customer journey triggers, possible market gaps and patterns in media use or online engagement.
Their goal was to develop a well-rounded understanding of the audience’s wants, interests and needs and identify insights that could inform strategic marketing and communication decisions.
Students were required to cite at least three credible sources, verify any sources generated by AI to ensure they were real, credible and current, and use those sources to support the key insights in their audience profile. They then developed at least two communication recommendations that directly connected to what they had learned about that specific audience segment.
Because each student researched a different audience and posted in a discussion board to their group, the individual assignments also created a body of research the group could use later. Students reviewed one another’s findings to select the strongest target audience, consider whether multiple audiences should be addressed, and make communication recommendations grounded in a broader understanding of potential audiences.
Reflection
Pushing beyond the familiar, expanding possibilities, promoting information literacy
As a result of this change, I found that groups considered specific audiences they would not have come up with on their own. The structured AI exploration pushed students beyond the first or most familiar audience that came to mind and encouraged them to consider audiences through multiple dimensions, including demographics, psychographics, behavior, geography, customer needs and market opportunities.
The transition from the group activity to the individual assignment also created clearer individual responsibility. Instead of one group collectively researching a small number of audience ideas, each student was responsible for developing a research-supported profile of a distinct audience and identifying communication implications from that research. When those individual analyses came back together, groups had a wider range of evidence and audience possibilities to consider.
Grading the individual assignment also revealed an important learning opportunity. Some students did not adequately verify sources suggested by AI, which led to additional class discussion about source credibility and verification. It also gave us an opportunity to discuss the importance of strong prompts, following up on initial AI responses, and distinguishing between using AI to generate possibilities and using credible evidence to support strategic decisions.
Overall, generative AI gave me a way to scale a type of guided exploration that I don’t have enough class time to provide to multiple groups. It helped students move beyond assumptions and familiar audiences to explore target audiences in all of the ways we discussed as a fully class while keeping the exploration tied to their specific real client. It also required students to move beyond AI-generated possibilities: they had to evaluate information, verify sources, identify meaningful audience insights and translate those insights into specific communication recommendations.
In the future, I would like to extend this exercise to allow students to think through the prompt development themselves rather than providing prompts to them (especially as students become more savvy with AI use and prompt engineering).