Pitney Bowes (PBI) Cost of Revenue (2009 - 2026)
Pitney Bowes' Cost of Revenue came in at $197.13 million for Q3 2026, down 1.8% from $200.69 million a year earlier but up 0.2% from the prior quarter.
Pitney Bowes (PBI) Cost of Revenue (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Sep 30, 2026, Pitney Bowes reported Cost of Revenue of $799.82 million, down 5.3% year-over-year; for FY2025, it came in at $807.26 million, down 16.3% from FY2024.
- Cost of Revenue has declined in each of the last four years, with a five-year compound annual growth rate of -19.6% (FY2020 to FY2025).
- Going back by year, Cost of Revenue was $964.3 million in FY2024 (-8.0%), $1.05 billion in FY2023 (-21.2%), $1.33 billion in FY2022 (-47.9%) and $2.55 billion in FY2021 (+6.1%).
- The five-year range for quarterly Cost of Revenue is -$455.56 million (Q4 2022) to $712.04 million (Q4 2021).
- Year-over-year, Cost of Revenue has declined for 11 consecutive quarters, with an average decline of 9.6% over the last eight quarters.
- Over the past five years, the year-over-year decline in Cost of Revenue ranged from 0.9% (Q1 2026) to 56.2% (Q3 2023).
- Business Quant data shows PBI's Cost of Revenue at $196.8 million (Q2 2026), $204.84 million (Q1 2026) and $201.06 million (Q4 2025) in the three quarters before Q3 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 172.92 Bn | 132.01 Bn | 5.98 Bn | 12.69 Bn |
| 2 | Cintas | 90.00 Bn | 89.09 Bn | 1.55 Bn | 1.46 Bn |
| 3 | Iron Mountain | 32.99 Bn | 32.50 Bn | 1.06 Bn | 926.65 Mn |
| 4 | Rollins | 18.37 Bn | 17.91 Bn | 582.90 Mn | 506.77 Mn |
| 5 | APi | 18.18 Bn | 15.39 Bn | 770.00 Mn | 1.78 Bn |
| 6 | UL Solutions | 16.47 Bn | 14.51 Bn | 423.00 Mn | 400.00 Mn |
| 7 | Aramark | 14.29 Bn | 12.30 Bn | 430.34 Mn | 4.63 Bn |
| 8 | Rentokil Initial | 11.99 Bn | 5.51 Bn | - | - |
| 9 | Gartner | 11.92 Bn | 5.41 Bn | 1.07 Bn | 433.14 Mn |
| 10 | Pitney Bowes | 2.13 Bn | 955.79 Mn | 259.05 Mn | 197.13 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 197.13 Mn |
| Jun 30, 2026 | 196.80 Mn |
| Mar 31, 2026 | 204.84 Mn |
| Dec 31, 2025 | 201.06 Mn |
| Sep 30, 2025 | 200.69 Mn |
| Jun 30, 2025 | 198.73 Mn |
| Mar 31, 2025 | 206.79 Mn |
| Dec 31, 2024 | 238.52 Mn |
| Sep 30, 2024 | 237.99 Mn |
| Jun 30, 2024 | 239.27 Mn |
| Mar 31, 2024 | 248.52 Mn |
| Dec 31, 2023 | 258.58 Mn |
| Sep 30, 2023 | 248.03 Mn |
| Jun 30, 2023 | 255.37 Mn |
| Mar 31, 2023 | 286.34 Mn |
| Dec 31, 2022 | -455.56 Mn |
| Sep 30, 2022 | 566.73 Mn |
| Jun 30, 2022 | 546.29 Mn |
| Mar 31, 2022 | 568.78 Mn |
| Dec 31, 2021 | 712.04 Mn |
Pitney Bowes Cost of Revenue 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=cost-of-revenue&ticker=PBI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cost-of-revenue", "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=cost-of-revenue&ticker=PBI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();