electroCore (ECOR) Cost of Revenue (2017 - 2026)
electroCore's Cost of Revenue came in at $1.27 million for Q2 2026, up 35.6% from $939,000 a year earlier and up 4.3% from the prior quarter.
electroCore (ECOR) Cost of Revenue (2017 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, electroCore reported Cost of Revenue of $4.79 million, up 19.3% year-over-year; for FY2025, it was $4.24 million, up 12.1% from FY2024.
- Cost of Revenue has increased 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 $3.79 million in FY2024 (+35.0%), $2.8 million in FY2023 (+73.5%), $1.62 million in FY2022 (+16.7%) and $1.39 million in FY2021 (-20.3%).
- The Q2 2026 figure represents the highest quarterly Cost of Revenue in data going back to Q2 2017.
- Year-over-year, Cost of Revenue has increased for six consecutive quarters, with growth averaging 19.5% over the last eight quarters.
- The fastest year-over-year change in Cost of Revenue over five years came in Q3 2023 (growth of 156.2%), and the weakest in Q4 2021 (a decline of 64.3%).
- Business Quant data shows ECOR's Cost of Revenue at $1.22 million (Q1 2026), $1.07 million (Q4 2025) and $1.22 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 242.18 Bn | 221.33 Bn | 4.88 Bn | 7.11 Bn |
| 2 | Abbott Laboratories | 168.71 Bn | 139.79 Bn | 7.27 Bn | 5.33 Bn |
| 3 | Danaher | 150.46 Bn | 134.27 Bn | 3.61 Bn | 2.65 Bn |
| 4 | Intuitive Surgical | 138.71 Bn | 118.26 Bn | 1.96 Bn | 931.90 Mn |
| 5 | Medtronic | 110.54 Bn | 76.41 Bn | 6.34 Bn | 3.42 Bn |
| 6 | Stryker | 105.66 Bn | 91.78 Bn | 4.50 Bn | 2.09 Bn |
| 7 | Boston Scientific | 61.74 Bn | 56.75 Bn | 3.85 Bn | 1.59 Bn |
| 8 | Edwards Lifesciences | 49.09 Bn | 33.21 Bn | 1.35 Bn | 392.40 Mn |
| 9 | Becton Dickinson | 48.16 Bn | 45.31 Bn | 2.32 Bn | 2.67 Bn |
| 10 | electroCore | 91.28 Mn | 47.76 Mn | 8.18 Mn | 1.27 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.27 Mn |
| Mar 31, 2026 | 1.22 Mn |
| Dec 31, 2025 | 1.07 Mn |
| Sep 30, 2025 | 1.22 Mn |
| Jun 30, 2025 | 939,000.00 |
| Mar 31, 2025 | 1.01 Mn |
| Dec 31, 2024 | 994,000.00 |
| Sep 30, 2024 | 1.07 Mn |
| Jun 30, 2024 | 838,000.00 |
| Mar 31, 2024 | 888,000.00 |
| Dec 31, 2023 | 1.10 Mn |
| Sep 30, 2023 | 661,000.00 |
| Jun 30, 2023 | 585,000.00 |
| Mar 31, 2023 | 458,000.00 |
| Dec 31, 2022 | 640,000.00 |
| Sep 30, 2022 | 258,000.00 |
| Jun 30, 2022 | 358,000.00 |
| Mar 31, 2022 | 360,000.00 |
| Dec 31, 2021 | 292,000.00 |
| Sep 30, 2021 | 355,000.00 |
electroCore 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=ECOR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cost-of-revenue", "ticker": "ECOR", "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=ECOR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();