Huckleberry.ai (DOMO) Operating Expenses (2017 - 2026)
Huckleberry.ai (DOMO) recorded Operating Expenses of $61.61 million in fiscal Q2 2027 (quarter ended Jul 31, 2026), down 7.9% from $66.89 million a year earlier and down 11.4% from the prior quarter.
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Analysis
Huckleberry.ai (DOMO) Operating Expenses (2017 - 2026) Analysis & Trends
On a TTM basis, Huckleberry.ai's Operating Expenses came in at $268.66 million as of Jul 31, 2026, down 4.9% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $278.22 million, down 5.8% from FY2025.
- Annual Operating Expenses has declined for three straight fiscal years, though with a five-year compound annual growth rate of 4.2% (FY2021 to FY2026).
- Across earlier fiscal years, Operating Expenses came in at $295.33 million in FY2025 (-1.0%), $298.4 million in FY2024 (-8.0%), $324.44 million in FY2023 (+16.2%) and $279.29 million in FY2022 (+23.3%).
- The fiscal Q2 2027 figure is the lowest quarterly Operating Expenses since fiscal Q1 2022.
- On a year-over-year basis, Operating Expenses rose in 1 of the last eight quarters, with an average decline of 5.4%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 42.7% in fiscal Q1 2023, against a decline of 14.1% in fiscal Q2 2024 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $69.51 million (Q1 2027), $71.71 million (Q4 2026) and $65.83 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 450.50 Bn | 419.56 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 401.01 Bn | 273.57 Bn | - | 12.62 Bn |
| 3 | Sap Se | 257.03 Bn | 178.11 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 187.04 Bn | 142.92 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 135.91 Bn | 114.37 Bn | 2.82 Bn | 2.66 Bn |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn | 4.34 Bn |
| 7 | Intuit | 72.30 Bn | 51.65 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 60.17 Bn | 57.14 Bn | - | - |
| 9 | Strategy | 55.31 Bn | 48.30 Bn | 81.55 Mn | 8.41 Bn |
| 10 | Huckleberry.ai | 147.52 Mn | -7.51 Mn | 59.22 Mn | 61.61 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 61.61 Mn |
| Apr 30, 2026 | 69.51 Mn |
| Jan 31, 2026 | 71.71 Mn |
| Oct 31, 2025 | 65.83 Mn |
| Jul 31, 2025 | 66.89 Mn |
| Apr 30, 2025 | 73.79 Mn |
| Jan 31, 2025 | 70.84 Mn |
| Oct 31, 2024 | 70.89 Mn |
| Jul 31, 2024 | 72.77 Mn |
| Apr 30, 2024 | 80.84 Mn |
| Jan 31, 2024 | 74.50 Mn |
| Oct 31, 2023 | 72.12 Mn |
| Jul 31, 2023 | 71.19 Mn |
| Apr 30, 2023 | 80.60 Mn |
| Jan 31, 2023 | 77.52 Mn |
| Oct 31, 2022 | 78.62 Mn |
| Jul 31, 2022 | 82.86 Mn |
| Apr 30, 2022 | 85.44 Mn |
| Jan 31, 2022 | 81.41 Mn |
| Oct 31, 2021 | 72.92 Mn |
API Access
Huckleberry.ai 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=DOMO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DOMO", "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=DOMO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();