Digital Turbine (APPS) Accumulated Expenses (2014 - 2026)
Digital Turbine (APPS) recorded Accumulated Expenses of $85.76 million in fiscal Q1 2027 (quarter ended Jun 30, 2026), up 7.3% from $79.89 million a year earlier but down 1.7% from the prior quarter.
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Analysis
Digital Turbine (APPS) Accumulated Expenses (2014 - 2026) Analysis & Trends
At the end of FY2026 (ended Mar 31, 2026), Digital Turbine reported Accumulated Expenses of $87.22 million, up 147.3% from FY2025.
- Annual Accumulated Expenses has a five-year compound annual growth rate of 13.6% (FY2021 to FY2026).
- Across earlier fiscal years, Accumulated Expenses came in at $35.26 million in FY2025 (+3.9%), $33.93 million in FY2024 (-51.0%), $69.22 million in FY2023 (-27.3%) and $95.17 million in FY2022 (+106.0%).
- Quarterly Accumulated Expenses has ranged from $26.32 million in fiscal Q1 2025 to $111.17 million in fiscal Q3 2022 over the past five years.
- On a year-over-year basis, Accumulated Expenses has increased for six consecutive quarters, with growth averaging 76.8% over the last eight quarters.
- Peak year-over-year performance for Accumulated Expenses in the last five years was growth of 268.8% in fiscal Q2 2022, against a decline of 51.0% in fiscal Q4 2024 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $87.22 million (Q4 2026), $94.12 million (Q3 2026) and $80.45 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Alphabet | 3,505.75 Bn | 3,240.65 Bn | 76.16 Bn |
| 2 | Meta Platforms | 1,636.37 Bn | 1,300.89 Bn | 51.23 Bn |
| 3 | Netflix | 264.79 Bn | 226.09 Bn | 6.80 Bn |
| 4 | Alibaba Group Holding | 244.49 Bn | 58.13 Bn | 15.16 Bn |
| 5 | Shopify | 196.00 Bn | 174.81 Bn | 1.78 Bn |
| 6 | Uber Technologies | 145.16 Bn | 115.98 Bn | 6.42 Bn |
| 7 | AppLovin | 136.87 Bn | 125.40 Bn | 1.94 Bn |
| 8 | Spotify Technology | 125.04 Bn | 81.96 Bn | 1.89 Bn |
| 9 | Booking Holdings | 122.68 Bn | 56.42 Bn | - |
| 10 | Digital Turbine | 1.37 Bn | 1.21 Bn | 94.94 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 85.76 Mn |
| Mar 31, 2026 | 87.22 Mn |
| Dec 31, 2025 | 94.12 Mn |
| Sep 30, 2025 | 80.45 Mn |
| Jun 30, 2025 | 79.89 Mn |
| Mar 31, 2025 | 35.26 Mn |
| Dec 31, 2024 | 34.30 Mn |
| Sep 30, 2024 | 29.52 Mn |
| Jun 30, 2024 | 26.32 Mn |
| Mar 31, 2024 | 33.93 Mn |
| Dec 31, 2023 | 66.16 Mn |
| Sep 30, 2023 | 55.15 Mn |
| Jun 30, 2023 | 49.76 Mn |
| Mar 31, 2023 | 69.22 Mn |
| Dec 31, 2022 | 75.38 Mn |
| Sep 30, 2022 | 79.17 Mn |
| Jun 30, 2022 | 86.16 Mn |
| Mar 31, 2022 | 95.17 Mn |
| Dec 31, 2021 | 111.17 Mn |
| Sep 30, 2021 | 81.88 Mn |
API Access
Digital Turbine Accumulated 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=accumulated-expenses&ticker=APPS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=APPS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();