Digital Brands (DBGI) Inventory Average (2021 - 2026)
Digital Brands' (DBGI) quarterly Inventory Average came in at $4.5 million in Q2 2026, up 7.79% on a YoY basis from $4.2 million in Q2 2025, and up 34.33% quarter-over-quarter from $3.3 million in Q1 2026.
Digital Brands (DBGI) Inventory Average (2021 - 2026) Analysis & Trends
Digital Brands (DBGI) has reported Inventory Average for 6 consecutive years, with $4.5 million the latest figure, recorded in Q2 2026.
- For the quarter ending Q2 2026, Inventory Average rose 7.79% year-over-year to $4.5 million; the trailing twelve-month figure through Jun 2026 stood at $4.5 million (up 7.79% YoY), and the FY2025 full-year result was $3.5 million, down 19.75% from the prior year.
- Inventory Average improved to $4.5 million in Q2 2026 per DBGI's latest filing, from $3.3 million in the prior quarter.
- Across five years, Inventory Average topped out at $5.1 million in Q3 2024 and bottomed at $2.6 million in Q1 2022.
- Historically, Inventory Average has averaged $4.1 million across 5 years, with a median of $4.3 million in 2024.
- The sharpest annual moves came in 2022 and 2026: Inventory Average jumped 206.35% in 2022, then fell 17.26% in 2026.
- Over 5 years, Inventory Average stood at $3.9 million in 2022, then advanced by 22.91% to $4.8 million in 2023, then fell by 7.27% to $4.4 million in 2024, then slipped by 15.89% to $3.7 million in 2025, then rose by 20.41% to $4.5 million in 2026.
- According to Business Quant data, Inventory Average over the past three periods registered $4.5 million, $3.3 million, and $3.7 million for Q2 2026, Q1 2026, and Q4 2025 respectively.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Inventory Avg. (Qtr) |
|---|---|---|---|---|---|
| 1 | Lululemon Athletica | 10.45 Bn | 9.06 Bn | 1.46 Bn | 1.70 Bn |
| 2 | Levi Strauss | 7.65 Bn | 6.67 Bn | 979.10 Mn | 1.14 Bn |
| 3 | Gildan Activewear | 7.18 Bn | 6.91 Bn | 459.76 Mn | 2.29 Bn |
| 4 | V F | 5.02 Bn | 4.35 Bn | 917.04 Mn | 1.64 Bn |
| 5 | Kontoor Brands | 3.63 Bn | 3.57 Bn | 328.26 Mn | 481.03 Mn |
| 6 | Pvh | 3.38 Bn | 2.42 Bn | 1.32 Bn | 1.62 Bn |
| 7 | Columbia Sportswear | 2.91 Bn | 2.29 Bn | 358.43 Mn | 749.37 Mn |
| 8 | Warby Parker | 2.78 Bn | 2.48 Bn | 136.46 Mn | 44.28 Mn |
| 9 | Figs | 2.06 Bn | 1.76 Bn | 147.86 Mn | 129.47 Mn |
| 10 | Digital Brands | 2.45 Mn | 1.06 Mn | 324,265.00 | 4.49 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 4.49 Mn |
| Mar 31, 2026 | 3.34 Mn |
| Dec 31, 2025 | 3.73 Mn |
| Sep 30, 2025 | 4.20 Mn |
| Jun 30, 2025 | 4.16 Mn |
| Mar 31, 2025 | 4.04 Mn |
| Dec 31, 2024 | 4.43 Mn |
| Sep 30, 2024 | 5.05 Mn |
| Jun 30, 2024 | 4.85 Mn |
| Mar 31, 2024 | 4.75 Mn |
| Dec 31, 2023 | 4.78 Mn |
| Sep 30, 2023 | 4.74 Mn |
| Jun 30, 2023 | 4.85 Mn |
| Mar 31, 2023 | 5.02 Mn |
| Dec 31, 2022 | 3.89 Mn |
| Sep 30, 2022 | 2.77 Mn |
| Jun 30, 2022 | 2.69 Mn |
| Mar 31, 2022 | 2.62 Mn |
| Dec 31, 2021 | 2.54 Mn |
| Sep 30, 2021 | 1.75 Mn |
Digital Brands Inventory Average 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=inventory-average&ticker=DBGI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "inventory-average", "ticker": "DBGI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=inventory-average&ticker=DBGI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();