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Wells Fargo: GLP-1 Adoption Is a Multi-Year Apparel Tailwind — Footwear Left Behind

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Wells Fargo: GLP-1 Adoption Is a Multi-Year Apparel Tailwind — Footwear Left Behind

Wells Fargo Securities published a sector-wide analysis (May 2026) finding that GLP-1 adoption is driving a measurable lift to US apparel spending through wardrobe replacement as users lose weight — but the benefit is uneven across categories.

Key Findings

  • GLP-1 has driven a +100bps lift to apparel category growth in 2024, +120bps in 2025, with potential for +160bps in 2026 and +170bps in 2027
  • GLP-1 users spent over 40% more on clothing annually than non-users based on Wells Fargo's proprietary survey of ~1,000 consumers
  • Bottoms and bras cited as highest-priority purchases
  • Circana (retail data firm) reports 55% of active GLP-1 users have purchased new clothing or footwear due to changing sizes; 25% updated wardrobes to refresh appearance

Winners and Losers

Overweight / Bullish (sizing-sensitive categories):

  • Kontoor Brands, Levi Strauss, Gap, Burlington Stores, Ross Stores, ThredUp
  • Victoria's Secret upgraded to Overweight (bras = highest priority item for female GLP-1 consumers)
  • "Intimates, dresses, denim, and fashion apparel" favored

Downgraded / Cautious (footwear and athletic):

  • Nike: downgraded to Equal Weight from Overweight; target cut $55 → $45 (heavy footwear exposure, international challenges)
  • Deckers Brands (Hoka/Ugg): downgraded to Underweight from Equal Weight; target cut $115 → $90
  • Academy Sports, Dick's Sporting Goods, Lululemon also flagged as relative underperformers

Rationale: shoe size changes only marginally from weight loss. Users replenish casual/leisure wardrobes faster than athletic apparel. Athleisure faces additional headwinds from post-COVID category rotation and increased competition.

Circana Context

As of fall 2025, 23% of US households had at least one GLP-1 user annually (up 4pp YoY). Circana projects these households will represent 35% of all food and beverage units sold by 2030.

Part of

This finding is an example of a pattern recurring across your work:

  • AI is turning software companies into heavy utility businesses

    When people experience a fundamental shift in their core constraints, like a change in physical body size or cognitive output density, they stop patching up their old setups with piecemeal upgrades and instead replace everything at once, driving rapid growth for integrated, full-stack providers at the expense of single-feature tools.

Revision history

  • Updated without a stated reason.
    · by migration
  • Updated without a stated reason.
    · by migration