Ishaan and Elizabeth, both graduate students in business, are attending a marketing strategy lecture at a business school in the Northeast. While learning about the principles of market segmentation, Ishaan texts "outdated" followed by three thinking—face emojis to Elizabeth. He wonders how demographic-, geographic-, or psychographic-based segmentation—the topic of the lecture—can help his family's franchise restaurant deal with the hundreds of sometimes-not-so-positive online reviews and social media posts. Meanwhile, Elizabeth hopes that the fast-food restaurant where she ordered her lunch understands that she now belongs to the segment of 'extremely displeased' customers. Earlier, she used the restaurant's new app to order a burrito without cheese and sour cream, only to discover that the meal included both offending ingredients. Her lunch went straight into the trash can and she angrily tweeted her disappointment to the restaurant. Elizabeth replies to Ishaan's text, "that is so passé," followed by a face_with_ rolling_eyes.
This simple vignette illustrates an important point. Organizations of every size are challenged with capitalizing on enormous amounts of unstructured organizational data—for instance, from social media posts—particularly for applications such as market segmentation. The purpose of this article is to give the reader an idea of the challenges and opportunities faced by businesses using market segmentation, including the impacts of big data. Our research will demonstrate what market segmentation might look like in the near future, as we also offer a promising approach to implementing market segmentation using unstructured data. With this demonstration, the article also illustrates how firms can develop specific actions or adjust their marketing mix based on unstructured data segmentation.
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