Specificity (SPTY) Operating Expenses (2021 - 2026)
Specificity (SPTY) posted Operating Expenses of $180,775 for Q2 2026, up 1.2% from $178,664 a year earlier but down 14.9% from the prior quarter.
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Analysis
Specificity (SPTY) Operating Expenses (2021 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Specificity was $754,737, down 26.9% year-over-year; for FY2025, it came in at $811,220, down 16.7% from FY2024.
- Annual Operating Expenses has declined for three consecutive years, though with a five-year compound annual growth rate of 39.6% (FY2020 to FY2025).
- In prior years, Specificity's Operating Expenses was $974,128 in FY2024 (-26.3%), $1.32 million in FY2023 (-68.1%), $4.14 million in FY2022 (+53.0%) and $2.71 million in FY2021.
- Quarterly Operating Expenses has run from a low of $142,602 in Q2 2024 to a high of $2.07 million in Q4 2022 over five years.
- On a year-over-year basis, Operating Expenses increased in four of the last eight quarters, with an average decline of 9.6%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2022, with growth of 153.8%; the weakest was Q4 2023, with a decline of 80.6%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $212,396 (Q1 2026), $198,812 (Q4 2025) and $162,754 (Q3 2025).
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 | Specificity | 5.87 Mn | 5.82 Mn | 118,436.00 | 180,775.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 180,775.00 |
| Mar 31, 2026 | 212,396.00 |
| Dec 31, 2025 | 198,812.00 |
| Sep 30, 2025 | 162,754.00 |
| Jun 30, 2025 | 178,664.00 |
| Mar 31, 2025 | 270,990.00 |
| Dec 31, 2024 | 320,768.00 |
| Sep 30, 2024 | 262,137.00 |
| Jun 30, 2024 | 142,602.00 |
| Mar 31, 2024 | 248,621.00 |
| Dec 31, 2023 | 402,271.00 |
| Sep 30, 2023 | 248,684.00 |
| Jun 30, 2023 | 369,328.00 |
| Mar 31, 2023 | 302,324.00 |
| Dec 31, 2022 | 2.07 Mn |
| Sep 30, 2022 | 628,436.00 |
| Jun 30, 2022 | 628,436.00 |
| Mar 31, 2022 | 1.44 Mn |
| Dec 31, 2021 | 816,247.00 |
| Sep 30, 2021 | 284,229.00 |
API Access
Specificity 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=SPTY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SPTY", "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=SPTY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();