Image courtesy of Under Armour

The case study, Under Armour’s Willful Digital Moves, delves into Under Armour’s successful segmentation strategies in the female athletic apparel market segment. These strategies, primarily demographic, were instrumental in capturing the attention of female customers through the viral “I Will What I Want” campaign. The study also identifies other potential segments, such as the women’s nutrition market, health, fitness, weight loss, sports apparel, “athleisure,” etc. (Murray & Saghian, 2016). The market segmentation in the case study could be described as “niche segmentation” because Under Armour is attempting to gain market share with the female athlete audience.

Market segmentation involves breaking a large and varied mass market into smaller groups “of consumers who share common needs, characteristics, or behaviors and then targeting one or more segments with a distinct marketing mix” (Murray & Saghian, 2016). Some key points to remember when implementing segmentation strategies are recognizing that consumers’ preferences vary, understanding the competition, and having solid market research and data as a foundation (Kardes, 2014). Market segmentation can be accomplished by looking at criteria such as demographic, psychographic, behavioral, or geographic factors (Adobe Experience Cloud Blog, 2023). Marketing segmentation aims to present customers with marketing information relevant to their specific interests and needs.

A new segment and technology that would be interesting to explore is AI (artificial intelligence) and how predictive modeling is and will be used to segment and target customers. AI audience segmentation is changing how we market and provides several benefits over traditional marketing segmentation. One of the biggest benefits of AI will be predictive analytics—or the ability for AI to use a combination of historical data, AI, and machine learning to create a more accurate picture of who the customer is and what their future spending will be (Sivek, 2024).

The case study on Under Armour is from 2016. Interestingly, in 2017, Thomas Hobbs of Marketing Week posted an article stating that Under Armour was “losing its cool” in response to slowing sales and low share prices. However, Thomas’s prediction that Under Armour was losing its cool was off the mark: https://www.marketingweek.com/has-the-under-armour-brand-lost-its-cool/. In 2023, Under Armour generated almost six billion U.S. dollars in global net revenue and is the sixth-highest revenue producer for athletic apparel, accessories and footwear globally (Tighe, 2024). Maybe AI can do a better job of predicting when companies are losing their coolness factor.

References

Adobe Experience Cloud Team. (2023, May 26). Market segments — what they are, how they work, and how to use them. Market Segments – what they are, how they work, and how to use them. https://business.adobe.com/blog/basics/market-segment

Kardes, F. (2014). Consumer Behavior (2nd ed.). Cengage Learning US. https://mbsdirect.vitalsource.com/books/9798214340623

Murray, M., & Saghian, M. (2016, May 18). Under Armour’s Willful Digital Moves. Harvard Business Publishing Education. https://hbsp.harvard.edu/product/UV7147-PDF-ENG

Sivek, S. C. (2024, March 7). Revamp your marketing campaigns with AI Customer Segmentation. Pecan AI. https://www.pecan.ai/blog/ai-customer-segmentation-marketing/

Tighe, D. (2024, March 19). Topic: Under armour. Statista. https://www.statista.com/topics/2470/under-armour/#topicOverview