Global Industrial (GIC) EBITDA (2010 - 2026)
Global Industrial (GIC) posted EBITDA of $51.3 million for Q2 2026, up 44.9% from $35.4 million a year earlier and up 128.0% from the prior quarter.
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Analysis
Global Industrial (GIC) EBITDA (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, EBITDA at Global Industrial was $123.6 million, up 28.8% year-over-year; for FY2025, it was $105.3 million, up 19.5% from FY2024.
- Annual EBITDA shows a five-year compound annual growth rate of 3.6% (FY2020 to FY2025).
- In prior years, Global Industrial's EBITDA was $88.1 million in FY2024 (-14.4%), $102.9 million in FY2023 (-5.7%), $109.1 million in FY2022 (+19.0%) and $91.7 million in FY2021 (+4.0%).
- The Q2 2026 figure stands as the highest quarterly EBITDA in data going back to Q3 2010.
- On a year-over-year basis, EBITDA has increased in each of the last six quarters, with growth averaging 10.7% over the last eight quarters.
- The strongest year-over-year quarter for EBITDA in the past five years was Q1 2022, with growth of 300.0%; the weakest was Q1 2023, with a decline of 37.8%.
- According to Business Quant data, EBITDA for the three prior quarters was $22.5 million (Q1 2026), $21.5 million (Q4 2025) and $28.3 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | W.W. Grainger | 59.11 Bn | 57.09 Bn | 1.98 Bn | 873.00 Mn |
| 2 | Fastenal | 57.94 Bn | 56.86 Bn | 1.06 Bn | 547.30 Mn |
| 3 | Ferguson Enterprises | 44.13 Bn | 41.35 Bn | 2.32 Bn | 709.00 Mn |
| 4 | Sunbelt Rentals Holdings | 30.69 Bn | 30.57 Bn | 1.25 Bn | 1.28 Bn |
| 5 | Reliance | 20.00 Bn | 19.04 Bn | 1.30 Bn | 511.10 Mn |
| 6 | Wesco International | 17.78 Bn | 15.09 Bn | 1.46 Bn | 444.90 Mn |
| 7 | Applied Industrial Technologies | 12.42 Bn | 12.29 Bn | 411.22 Mn | 175.57 Mn |
| 8 | Watsco | 11.14 Bn | 9.30 Bn | 578.93 Mn | 249.30 Mn |
| 9 | Avantor | 10.34 Bn | 9.14 Bn | 537.00 Mn | 227.40 Mn |
| 10 | Global Industrial | 1.61 Bn | 1.33 Bn | 155.40 Mn | 51.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 51.30 Mn |
| Mar 31, 2026 | 22.50 Mn |
| Dec 31, 2025 | 21.50 Mn |
| Sep 30, 2025 | 28.30 Mn |
| Jun 30, 2025 | 35.40 Mn |
| Mar 31, 2025 | 20.10 Mn |
| Dec 31, 2024 | 16.30 Mn |
| Sep 30, 2024 | 24.20 Mn |
| Jun 30, 2024 | 28.30 Mn |
| Mar 31, 2024 | 19.30 Mn |
| Dec 31, 2023 | 23.30 Mn |
| Sep 30, 2023 | 30.10 Mn |
| Jun 30, 2023 | 30.60 Mn |
| Mar 31, 2023 | 18.90 Mn |
| Dec 31, 2022 | 18.80 Mn |
| Sep 30, 2022 | 28.50 Mn |
| Jun 30, 2022 | 31.40 Mn |
| Mar 31, 2022 | 30.40 Mn |
| Dec 31, 2021 | 27.00 Mn |
| Sep 30, 2021 | 31.50 Mn |
API Access
Global Industrial EBITDA 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=ebitda&ticker=GIC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "GIC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=GIC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();