Digital Turbine (APPS) Operating Expenses (2010 - 2025)
Digital Turbine (APPS) reported Operating Expenses of $129.75 million for fiscal Q3 2026 (quarter ended Dec 31, 2025), down 12.0% from $147.39 million a year earlier and down 3.1% from the prior quarter.
Digital Turbine (APPS) Operating Expenses (2010 - 2025) Analysis & Trends
Over the twelve months ended Dec 31, 2025, Digital Turbine's Operating Expenses came in at $530.02 million, down 27.8% year-over-year; for FY2025 (ended Mar 31, 2025), it came in at $544.58 million, down 40.7% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 34.1% (FY2020 to FY2025).
- By fiscal year, Operating Expenses came in at $918.92 million in FY2024 (+48.3%), $619.76 million in FY2023 (-5.4%), $655.36 million in FY2022 (+157.6%) and $254.37 million in FY2021 (+102.7%).
- The fiscal Q3 2026 figure ranks as the lowest quarterly Operating Expenses since fiscal Q4 2021.
- Year over year, Operating Expenses gained in three of the last eight quarters, with an average decline of 3.0%.
- The high point for year-over-year Operating Expenses in five years was fiscal Q2 2022 (growth of 192.7%); the low point was fiscal Q4 2025 (a decline of 59.1%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $133.84 million (Q2 2026), $135.59 million (Q1 2026) and $130.84 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,164.76 Bn | 3,922.28 Bn | 73.85 Bn | 79.03 Bn |
| 2 | Meta Platforms | 1,823.40 Bn | 1,525.92 Bn | 49.47 Bn | 42.03 Bn |
| 3 | Netflix | 288.27 Bn | 248.47 Bn | 6.52 Bn | 1.51 Bn |
| 4 | Alibaba Group Holding | 252.72 Bn | 70.58 Bn | 15.11 Bn | -5.17 Bn |
| 5 | Shopify | 186.52 Bn | 163.71 Bn | 1.71 Bn | 1.22 Bn |
| 6 | Uber Technologies | 139.11 Bn | 111.09 Bn | 6.38 Bn | 12.30 Bn |
| 7 | Booking Holdings | 123.13 Bn | 56.18 Bn | - | 4.85 Bn |
| 8 | PDD Holdings | 111.72 Bn | -140.21 Bn | 9.45 Bn | -5.39 Bn |
| 9 | AppLovin | 103.35 Bn | 93.38 Bn | 1.70 Bn | 429.41 Mn |
| 10 | Digital Turbine | 1.34 Bn | 1.19 Bn | - | - |
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 129.75 Mn |
| Sep 30, 2025 | 133.84 Mn |
| Jun 30, 2025 | 135.59 Mn |
| Mar 31, 2025 | 130.84 Mn |
| Dec 31, 2024 | 147.39 Mn |
| Sep 30, 2024 | 132.27 Mn |
| Jun 30, 2024 | 134.08 Mn |
| Mar 31, 2024 | 320.06 Mn |
| Dec 31, 2023 | 151.90 Mn |
| Sep 30, 2023 | 295.88 Mn |
| Jun 30, 2023 | 151.08 Mn |
| Mar 31, 2023 | 149.27 Mn |
| Dec 31, 2022 | 152.51 Mn |
| Sep 30, 2022 | 153.78 Mn |
| Jun 30, 2022 | 164.20 Mn |
| Mar 31, 2022 | 156.71 Mn |
| Dec 31, 2021 | 187.68 Mn |
| Sep 30, 2021 | 172.04 Mn |
| Jun 30, 2021 | 138.93 Mn |
| Mar 31, 2021 | 79.13 Mn |
Digital Turbine 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=APPS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "APPS", "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=APPS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();