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Words are part of almost every marketplace interaction. Online reviews, customer service calls, press releases, marketing communications, and other interactions create a wealth of textual data. But how can marketers best use such data?
Automated text analysis provides a computer-assisted methodology to describe “what” is being said and “how” it is said.
Text reflects information about the text producer, or one can study how text impacts the text receiver.
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Related Marketing Courses:
Brand Management; Consumer Behavior; Digital Marketing; Marketing Analytics; Marketing Communications; Social Media Marketing
Full Citation:
Berger, Jonah, Ashlee Humphreys, Stephan Ludwig, Wendy W. Moe, Oded Netzer, and David A. Schweidel (2020), “Uniting the Tribes: Using Text for Marketing Insight,” Journal of Marketing, 84(1), 1-25.
Article Abstract:
Words are part of almost every marketplace interaction. Online reviews, customer service calls, press releases, marketing communications, and other interactions create a wealth of textual data. But how can marketers best use such data? This article provides an overview of automated textual analysis and details how it can be used to generate marketing insights. We discuss how text reflects qualities of the text producer (and context in which the text was produced) and impacts the audience or text recipient. Next, we discuss how text can be a powerful tool both for prediction and for understanding (i.e., insights). Then, we overview methodologies and metrics used in text analysis, providing a set of guidelines and procedures. Further, we highlight some common metrics and challenges and discuss how researchers can address issues of internal and external validity. Finally, we conclude with a discussion of potential areas for future work. Along the way, we note how textual analysis can unite the tribes of marketing. While most marketing problems are interdisciplinary, the field is often fragmented. By involving skills and ideas from each of the subareas of marketing, text analysis has the potential to help unite the field with a common set of tools and approaches.
Special thanks to Kelley Gullo and Holly Howe, Ph.D. candidates at Duke University, for their support in working with authors on submissions to this program.
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