Pitney Bowes (PBI) EBITDA (2009 - 2026)
Pitney Bowes' EBITDA was $106.2 million in Q3 2026, down 5.2% from $111.99 million a year earlier but up 2.5% from the prior quarter.
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Analysis
Pitney Bowes (PBI) EBITDA (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Pitney Bowes' EBITDA was $411.68 million through Sep 30, 2026, up 44.5% year-over-year; for FY2025, it was $372.83 million, up 101.4% from FY2024.
- EBITDA shows a five-year compound annual growth rate of 2.5% (FY2020 to FY2025).
- In earlier years, EBITDA was $185.16 million in FY2024 (+3.9%), $178.27 million in FY2023 (-55.0%), $395.8 million in FY2022 (-22.6%) and $511.41 million in FY2021 (+55.4%).
- Quarterly EBITDA has moved between -$639.8 million (Q2 2023) and $600.1 million (Q4 2022) over five years.
- Compared with a year earlier, EBITDA was higher in five of the last seven quarters, with growth averaging 200.6%.
- The best year-over-year quarter for EBITDA over five years was Q4 2025 (growth of 663.5%); the worst was Q3 2024 (a decline of 74.3%).
- Per Business Quant data, PBI's EBITDA in the three quarters before Q3 2026 was $103.62 million (Q2 2026), $120.87 million (Q1 2026) and $80.99 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 172.92 Bn | 132.01 Bn | 5.98 Bn | 3.47 Bn |
| 2 | Cintas | 90.00 Bn | 89.09 Bn | 1.55 Bn | 839.21 Mn |
| 3 | Iron Mountain | 32.99 Bn | 32.50 Bn | 1.06 Bn | 711.62 Mn |
| 4 | Rollins | 18.37 Bn | 17.91 Bn | 582.90 Mn | 256.13 Mn |
| 5 | APi | 18.18 Bn | 15.39 Bn | 770.00 Mn | 306.00 Mn |
| 6 | UL Solutions | 16.47 Bn | 14.51 Bn | 423.00 Mn | 211.00 Mn |
| 7 | Aramark | 14.29 Bn | 12.30 Bn | 430.34 Mn | 351.69 Mn |
| 8 | Rentokil Initial | 11.99 Bn | 5.51 Bn | - | - |
| 9 | Gartner | 11.92 Bn | 5.41 Bn | 1.07 Bn | 327.51 Mn |
| 10 | Pitney Bowes | 2.13 Bn | 955.79 Mn | 259.05 Mn | 132.18 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 132.18 Mn |
| Jun 30, 2026 | 132.20 Mn |
| Mar 31, 2026 | 146.86 Mn |
| Dec 31, 2025 | 107.17 Mn |
| Sep 30, 2025 | 138.06 Mn |
| Jun 30, 2025 | 110.07 Mn |
| Mar 31, 2025 | 77.21 Mn |
| Dec 31, 2024 | 10.61 Mn |
| Sep 30, 2024 | 15.74 Mn |
| Jun 30, 2024 | 52.49 Mn |
| Mar 31, 2024 | 82.11 Mn |
| Dec 31, 2023 | -3.29 Mn |
| Sep 30, 2023 | 61.21 Mn |
| Jun 30, 2023 | -639.80 Mn |
| Mar 31, 2023 | -541.20 Mn |
| Dec 31, 2022 | 600.10 Mn |
| Sep 30, 2022 | 90.54 Mn |
| Jun 30, 2022 | 127.11 Mn |
| Mar 31, 2022 | 154.40 Mn |
| Dec 31, 2021 | 133.94 Mn |
API Access
Pitney Bowes 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=PBI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "PBI", "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=PBI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();