Warby Parker (WRBY) Accumulated Expenses (2020 - 2026)
Warby Parker's (WRBY) quarterly Accumulated Expenses came in at $61.3 million in Q2 2026, up 1.2% on a YoY basis from $60.6 million in Q2 2025, and up 1.58% quarter-over-quarter from $60.3 million in Q1 2026.
Warby Parker (WRBY) Accumulated Expenses (2020 - 2026) Analysis & Trends
Warby Parker (WRBY) has reported Accumulated Expenses for 7 consecutive years, with $61.3 million the latest figure, recorded in Q2 2026.
- For the quarter ending Q2 2026, Accumulated Expenses rose 1.2% year-over-year to $61.3 million; the trailing twelve-month figure through Jun 2026 stood at $61.3 million (up 1.2% YoY), and the FY2025 full-year result was $49.2 million, down 4.62% from the prior year.
- Accumulated Expenses rose to $61.3 million in Q2 2026 per WRBY's latest filing, from $60.3 million in the prior quarter.
- Across five years, Accumulated Expenses topped out at $67.6 million in Q3 2025 and bottomed at $42.8 million in Q2 2023.
- Historically, Accumulated Expenses has averaged $52.7 million across 5 years, with a median of $51.7 million in 2024.
- The sharpest annual moves came in 2023 and 2025: Accumulated Expenses decreased 20.44% in 2023, then surged 47.0% in 2025.
- Over 5 years, Accumulated Expenses stood at $58.2 million in 2022, then declined by 20.44% to $46.3 million in 2023, then rose by 11.42% to $51.6 million in 2024, then dropped by 4.62% to $49.2 million in 2025, then rose by 24.52% to $61.3 million in 2026.
- According to Business Quant data, Accumulated Expenses over the past three periods registered $61.3 million, $60.3 million, and $49.2 million for Q2 2026, Q1 2026, and Q4 2025 respectively.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Lululemon Athletica | 10.45 Bn | 9.06 Bn | 1.46 Bn |
| 2 | Levi Strauss | 7.65 Bn | 6.67 Bn | 979.10 Mn |
| 3 | Gildan Activewear | 7.18 Bn | 6.91 Bn | 459.76 Mn |
| 4 | V F | 5.02 Bn | 4.35 Bn | 917.04 Mn |
| 5 | Kontoor Brands | 3.63 Bn | 3.57 Bn | 328.26 Mn |
| 6 | Pvh | 3.38 Bn | 2.42 Bn | 1.32 Bn |
| 7 | Columbia Sportswear | 2.91 Bn | 2.29 Bn | 358.43 Mn |
| 8 | Warby Parker | 2.78 Bn | 2.48 Bn | 136.46 Mn |
| 9 | Figs | 2.06 Bn | 1.76 Bn | 147.86 Mn |
| 10 | Under Armour | 2.04 Bn | 1.65 Bn | 593.83 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 61.30 Mn |
| Mar 31, 2026 | 60.34 Mn |
| Dec 31, 2025 | 49.23 Mn |
| Sep 30, 2025 | 67.64 Mn |
| Jun 30, 2025 | 60.57 Mn |
| Mar 31, 2025 | 51.80 Mn |
| Dec 31, 2024 | 51.61 Mn |
| Sep 30, 2024 | 46.02 Mn |
| Jun 30, 2024 | 47.74 Mn |
| Mar 31, 2024 | 43.20 Mn |
| Dec 31, 2023 | 46.32 Mn |
| Sep 30, 2023 | 54.64 Mn |
| Jun 30, 2023 | 42.76 Mn |
| Mar 31, 2023 | 48.00 Mn |
| Dec 31, 2022 | 58.22 Mn |
| Sep 30, 2022 | 52.84 Mn |
| Jun 30, 2022 | 49.84 Mn |
| Mar 31, 2022 | 56.32 Mn |
| Dec 31, 2021 | 60.84 Mn |
| Sep 30, 2021 | 63.66 Mn |
Warby Parker Accumulated Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=WRBY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "WRBY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=WRBY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();