Comscore (SCOR) Operating Expenses (2010 - 2026)
Comscore's Operating Expenses was $91.23 million in Q2 2026, up 0.2% from $91.07 million a year earlier and up 1.5% from the prior quarter.
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Analysis
Comscore (SCOR) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Comscore's Operating Expenses was $355.18 million through Jun 30, 2026, down 15.0% year-over-year; for FY2025, it was $352.96 million, down 15.1% from FY2024.
- Operating Expenses has now declined for three consecutive years, with a five-year compound annual growth rate of -1.3% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $415.56 million in FY2024 (-6.6%), $444.94 million in FY2023 (-1.4%), $451.3 million in FY2022 (+14.0%) and $395.88 million in FY2021 (+4.9%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses since Q3 2024.
- Compared with a year earlier, Operating Expenses was higher in four of the last eight quarters, with growth averaging 0.3%.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2024 (growth of 66.5%); the worst was Q3 2025 (a decline of 41.1%).
- Per Business Quant data, SCOR's Operating Expenses in the three quarters before Q2 2026 was $89.84 million (Q1 2026), $86.91 million (Q4 2025) and $87.2 million (Q3 2025).
Peer Set
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 | Comscore | 73.80 Mn | -24.28 Mn | 28.26 Mn | 91.23 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 91.23 Mn |
| Mar 31, 2026 | 89.84 Mn |
| Dec 31, 2025 | 86.91 Mn |
| Sep 30, 2025 | 87.20 Mn |
| Jun 30, 2025 | 91.07 Mn |
| Mar 31, 2025 | 87.78 Mn |
| Dec 31, 2024 | 91.04 Mn |
| Sep 30, 2024 | 148.08 Mn |
| Jun 30, 2024 | 87.77 Mn |
| Mar 31, 2024 | 88.67 Mn |
| Dec 31, 2023 | 119.56 Mn |
| Sep 30, 2023 | 88.93 Mn |
| Jun 30, 2023 | 141.06 Mn |
| Mar 31, 2023 | 95.39 Mn |
| Dec 31, 2022 | 94.82 Mn |
| Sep 30, 2022 | 149.23 Mn |
| Jun 30, 2022 | 102.74 Mn |
| Mar 31, 2022 | 104.51 Mn |
| Dec 31, 2021 | 99.03 Mn |
| Sep 30, 2021 | 96.51 Mn |
API Access
Comscore 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=SCOR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SCOR", "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=SCOR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();