Scienjoy Holding (SJ) Operating Expenses (2019 - 2026)
Scienjoy Holding's Operating Expenses was $6.21 million in Q2 2026, up 10.1% from $5.64 million a year earlier and up 12.8% from the prior quarter.
Scienjoy Holding (SJ) Operating Expenses (2019 - 2026) Analysis & Trends
On a trailing twelve-month basis, Scienjoy Holding's Operating Expenses was $24.57 million through Jun 30, 2026, down 14.0% year-over-year; for FY2025, it came in at $24.65 million, up 7.7% from FY2024.
- Operating Expenses has now increased for three consecutive years, with a five-year compound annual growth rate of 20.3% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $22.89 million in FY2024 (+7.8%), $21.23 million in FY2023 (+10.9%), $19.14 million in FY2022 (-11.9%) and $21.73 million in FY2021 (+121.9%).
- Quarterly Operating Expenses has moved between $4.02 million (Q4 2022) and $9.12 million (Q3 2024) over five years.
- Compared with a year earlier, Operating Expenses was higher in four of the last eight quarters, with growth averaging 4.4%.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2021 (growth of 107.5%); the worst was Q4 2022 (a decline of 51.5%).
- Per Business Quant data, SJ's Operating Expenses in the three quarters before Q2 2026 was $5.5 million (Q1 2026), $6.49 million (Q4 2025) and $6.36 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 3,505.75 Bn | 3,240.65 Bn | 76.16 Bn | 87.00 Bn |
| 2 | Meta Platforms | 1,636.37 Bn | 1,300.89 Bn | 51.23 Bn | 51.61 Bn |
| 3 | Netflix | 264.79 Bn | 226.09 Bn | 6.80 Bn | 1.50 Bn |
| 4 | Alibaba Group Holding | 244.49 Bn | 58.13 Bn | 15.16 Bn | 5.19 Bn |
| 5 | Shopify | 196.00 Bn | 174.81 Bn | 1.78 Bn | 1.21 Bn |
| 6 | Uber Technologies | 145.16 Bn | 115.98 Bn | 6.42 Bn | 13.32 Bn |
| 7 | AppLovin | 136.87 Bn | 125.40 Bn | 1.94 Bn | 475.85 Mn |
| 8 | Spotify Technology | 125.04 Bn | 81.96 Bn | 1.89 Bn | 645.39 Mn |
| 9 | Booking Holdings | 122.68 Bn | 56.42 Bn | - | 5.48 Bn |
| 10 | Scienjoy Holding | 38.67 Mn | -140.55 Mn | 8.13 Mn | 6.21 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 6.21 Mn |
| Mar 31, 2026 | 5.50 Mn |
| Dec 31, 2025 | 6.49 Mn |
| Sep 30, 2025 | 6.36 Mn |
| Jun 30, 2025 | 5.64 Mn |
| Mar 31, 2025 | 5.91 Mn |
| Dec 31, 2024 | 7.91 Mn |
| Sep 30, 2024 | 9.12 Mn |
| Jun 30, 2024 | 4.97 Mn |
| Mar 31, 2024 | 5.93 Mn |
| Dec 31, 2023 | 5.31 Mn |
| Sep 30, 2023 | 7.73 Mn |
| Jun 30, 2023 | 5.37 Mn |
| Mar 31, 2023 | 5.12 Mn |
| Dec 31, 2022 | 4.02 Mn |
| Sep 30, 2022 | 5.14 Mn |
| Jun 30, 2022 | 5.60 Mn |
| Mar 31, 2022 | 5.72 Mn |
| Dec 31, 2021 | 8.28 Mn |
| Sep 30, 2021 | 4.86 Mn |
Scienjoy Holding 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=SJ&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SJ", "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=SJ&period=max&api_key=YOUR_API_KEY");
const data = await res.json();