Trade Desk (TTD) Other Operating Expenses (2015 - 2026)
Trade Desk's Other Operating Expenses came in at $358.74 million for Q2 2026, up 14.9% from $312.11 million a year earlier and up 1.3% from the prior quarter.
Trade Desk (TTD) Other Operating Expenses (2015 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Trade Desk reported Other Operating Expenses of $1.37 billion, up 18.3% year-over-year; for FY2025, it came in at $1.26 billion, up 24.0% from FY2024.
- Other Operating Expenses has increased in each of the last 11 years, with a five-year compound annual growth rate of 29.0% (FY2020 to FY2025).
- Going back by year, Other Operating Expenses was $1.02 billion in FY2024 (+25.2%), $813.57 million in FY2023 (+31.4%), $619.1 million in FY2022 (+31.5%) and $470.85 million in FY2021 (+33.2%).
- The Q2 2026 figure represents the highest quarterly Other Operating Expenses in data going back to Q3 2015.
- Year-over-year, Other Operating Expenses has increased for 40 consecutive quarters, with growth averaging 23.3% over the last eight quarters.
- Across the past five years, year-over-year growth in Other Operating Expenses ran from 14.9% in Q2 2026 to 39.4% in Q2 2022.
- Business Quant data shows TTD's Other Operating Expenses at $354.15 million (Q1 2026), $336.69 million (Q4 2025) and $318.98 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Alphabet | 4,071.44 Bn | 3,828.96 Bn | 73.85 Bn |
| 2 | Meta Platforms | 1,777.07 Bn | 1,479.59 Bn | 49.47 Bn |
| 3 | Netflix | 272.74 Bn | 232.94 Bn | 6.52 Bn |
| 4 | Alibaba Group Holding | 242.17 Bn | 55.95 Bn | 15.11 Bn |
| 5 | Shopify | 225.98 Bn | 203.16 Bn | 1.71 Bn |
| 6 | Uber Technologies | 137.80 Bn | 109.60 Bn | 6.38 Bn |
| 7 | Booking Holdings | 121.57 Bn | 54.62 Bn | - |
| 8 | PDD Holdings | 110.14 Bn | -133.64 Bn | 9.45 Bn |
| 9 | Spotify Technology | 107.49 Bn | 64.99 Bn | 1.86 Bn |
| 10 | Trade Desk | 5.90 Bn | 261.57 Mn | 530.72 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 358.74 Mn |
| Mar 31, 2026 | 354.15 Mn |
| Dec 31, 2025 | 336.69 Mn |
| Sep 30, 2025 | 318.98 Mn |
| Jun 30, 2025 | 312.11 Mn |
| Mar 31, 2025 | 295.58 Mn |
| Dec 31, 2024 | 285.90 Mn |
| Sep 30, 2024 | 262.95 Mn |
| Jun 30, 2024 | 244.33 Mn |
| Mar 31, 2024 | 225.36 Mn |
| Dec 31, 2023 | 227.49 Mn |
| Sep 30, 2023 | 205.85 Mn |
| Jun 30, 2023 | 198.14 Mn |
| Mar 31, 2023 | 182.09 Mn |
| Dec 31, 2022 | 172.45 Mn |
| Sep 30, 2022 | 155.16 Mn |
| Jun 30, 2022 | 156.91 Mn |
| Mar 31, 2022 | 134.58 Mn |
| Dec 31, 2021 | 139.35 Mn |
| Sep 30, 2021 | 112.68 Mn |
Trade Desk Other 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=other-operating-expenses&ticker=TTD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "ticker": "TTD", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=other-operating-expenses&ticker=TTD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();