Athleisure Consumer
Landscape
A comprehensive survey of 2,000 U.S. athleisure consumers conducted by Alvarez & Marsal – Consumer & Retail Group. Respondents purchased athleisure within the last 12 months. The survey explores brand perceptions, shopping behavior, discovery channels, and purchase barriers across 12 major brands. For additional information, contact dlimberopoulos@alvarezandmarsal.com.
Executive Summary
Methodology
This survey was fielded in February 2026 to a U.S. census-balanced online panel of 2,000 adults aged 18–70. The sample is naturally representative by age, gender, income, and ethnicity — no oversampling or weighting was required. Respondents qualified by having purchased athleisure clothing in the last 12 months. The qualification rate was approximately ~30%.
Key Findings
Brand loyalty is the exception, not the norm. The average consumer purchased from 4.8 different athleisure brands in the last 12 months. Very few shoppers are exclusive to a single brand — they're cross-shopping freely across price tiers and positioning. This means brands compete not for loyalty but for inclusion in a rotating consideration set, making product freshness, availability, and moment-of-purchase experience critical.
The athleisure wallet is substantial and broad-based. Of consumers who purchased athleisure in the last 12 months, they report spending an average of $593 on athleisure in the last 12 months (median: $300), with spend distributed across nearly 5 brands. The gap between mean and median reflects a segment of high-value power buyers spending $1,000+ annually, while the majority of consumers maintain a steady $200–500 annual commitment to the category.
Nike and Adidas dominate awareness and purchase, but premium challengers are gaining ground. Nike (97.8%) and Adidas (94.7%) lead aided awareness, with Lululemon (95.7%) matching them. Vuori and Alo, despite ~30% awareness, command the highest NPS scores alongside Nike and Lululemon — signaling intense loyalty among their smaller customer bases.
Lululemon faces a notable awareness-to-consideration gap. Despite near-universal awareness (95.7%), a significant share of aware consumers have never considered purchasing. Price is the #1 cited barrier at 44% — more than double the next reason. This suggests a marketing and positioning challenge: the brand is well-known but many consumers self-select out before even evaluating the product. Bridging this gap — through trial programs, entry-price products, or reframing the value proposition — could unlock substantial conversion upside.
Comfort and quality trump everything. Consumers overwhelmingly prioritize comfort, quality, and fit — far ahead of brand reputation or endorsements. The brand attributes data confirms this: top-performing brands are consistently associated with "comfortable to wear" and "high quality materials."
Athleisure has fully crossed over into everyday life. Consumers wear athleisure an average of 4.8 days per week. While working out remains a core occasion, casual wear at home, running errands, and socializing now rank equally high — confirming the category has moved well beyond its performance origins into a true lifestyle play.
Word of mouth and social media rule discovery, but the final purchase decision tilts toward in-store browsing and personal recommendations. AI tools (ChatGPT, Gemini) are emerging as a discovery channel — 11% already use them — with notable skew toward younger demographics.
Who Are Athleisure Consumers?
Brand Landscape
Category Engagement
Discovery & Channels
Brand Health — Net Promoter Score
Methodology
Net Promoter Score (NPS) is calculated by subtracting the percentage of Detractors (respondents who rated 0–6) from the percentage of Promoters (respondents who rated 9–10). Passives (7–8) are excluded from the calculation. Scores range from −100 to +100; a positive score indicates more promoters than detractors. Only brands with n ≥ 10 respondents are shown.
Brand Attributes & Perceptions
Brand Deep Dive
Barriers & Conversion
Shopper Overlap — Venn Diagram
How to Read
Select a primary universe of shoppers (all consumers, or shoppers of a specific brand) and frequency filter. Then select one or more overlap brands to see how many shoppers from your primary universe also buy those brands. Overlap is estimated using survey purchase rates.