Goosehead Insurance (GSHD) Operating Expenses (2017 - 2026)
Goosehead Insurance (GSHD) reported Operating Expenses of $86.8 million for Q2 2026, up 10.8% from $78.37 million a year earlier and up 11.2% from the prior quarter.
Goosehead Insurance (GSHD) Operating Expenses (2017 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Goosehead Insurance's Operating Expenses came in at $308.4 million, up 12.1% year-over-year; for FY2025, it was $290.86 million, up 14.8% from FY2024.
- Operating Expenses has increased for six consecutive years, with a five-year compound annual growth rate of 24.5% (FY2020 to FY2025).
- By year, Operating Expenses came in at $253.37 million in FY2024 (+11.0%), $228.32 million in FY2023 (+14.6%), $199.26 million in FY2022 (+39.7%) and $142.64 million in FY2021 (+46.9%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q1 2017.
- Year over year, Operating Expenses has now increased in each of the last 28 quarters, with growth averaging 13.5% over the last eight quarters.
- Across the past five years, year-over-year growth in Operating Expenses ran from 6.5% in Q3 2023 to 52.3% in Q3 2021.
- Per Business Quant data, the three quarters before Q2 2026 came in at $78.08 million (Q1 2026), $74.36 million (Q4 2025) and $69.16 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Berkshire Hathaway | 1,082.55 Bn | -334.93 Bn | 55.86 Bn | 86.07 Bn |
| 2 | Chubb | 128.03 Bn | 80.09 Bn | 9.13 Bn | 12.19 Bn |
| 3 | Progressive | 122.38 Bn | 98.22 Bn | 9.04 Bn | 19.40 Bn |
| 4 | Marsh & Mclennan Companies | 81.46 Bn | 73.20 Bn | - | 5.51 Bn |
| 5 | Travelers Companies | 75.77 Bn | 52.02 Bn | 6.23 Bn | 9.39 Bn |
| 6 | Manulife Financial | 73.91 Bn | 75.11 Bn | - | -902.21 Mn |
| 7 | Metlife | 60.71 Bn | -45.77 Bn | 7.82 Bn | 18.12 Bn |
| 8 | Aon | 58.53 Bn | 51.77 Bn | - | 3.33 Bn |
| 9 | Arthur J. Gallagher | 58.38 Bn | 52.82 Bn | - | 3.59 Bn |
| 10 | Goosehead Insurance | 1.56 Bn | 1.35 Bn | - | 86.80 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 86.80 Mn |
| Mar 31, 2026 | 78.08 Mn |
| Dec 31, 2025 | 74.36 Mn |
| Sep 30, 2025 | 69.16 Mn |
| Jun 30, 2025 | 78.37 Mn |
| Mar 31, 2025 | 68.97 Mn |
| Dec 31, 2024 | 66.07 Mn |
| Sep 30, 2024 | 61.60 Mn |
| Jun 30, 2024 | 62.69 Mn |
| Mar 31, 2024 | 63.01 Mn |
| Dec 31, 2023 | 56.33 Mn |
| Sep 30, 2023 | 57.42 Mn |
| Jun 30, 2023 | 58.09 Mn |
| Mar 31, 2023 | 56.49 Mn |
| Dec 31, 2022 | 50.63 Mn |
| Sep 30, 2022 | 53.90 Mn |
| Jun 30, 2022 | 47.36 Mn |
| Mar 31, 2022 | 47.38 Mn |
| Dec 31, 2021 | 38.08 Mn |
| Sep 30, 2021 | 38.14 Mn |
Goosehead Insurance Operating Expenses 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=operating-expenses&ticker=GSHD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GSHD", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=GSHD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();