EverQuote (EVER) Operating Expenses (2017 - 2026)
EverQuote (EVER) posted Operating Expenses of $171.6 million for Q2 2026, up 20.5% from $142.46 million a year earlier and up 2.5% from the prior quarter.
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Analysis
EverQuote (EVER) Operating Expenses (2017 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at EverQuote was $672.13 million, up 18.0% year-over-year; for FY2025, it was $634.19 million, up 35.4% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 12.1% (FY2020 to FY2025).
- In prior years, EverQuote's Operating Expenses was $468.44 million in FY2024 (+37.8%), $339.9 million in FY2023 (-20.8%), $428.92 million in FY2022 (-2.6%) and $440.44 million in FY2021 (+22.8%).
- Quarterly Operating Expenses has run from a low of $62.47 million in Q4 2023 to a high of $176.69 million in Q4 2025 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last nine quarters, with growth averaging 44.3% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2024, with growth of 116.8%; the weakest was Q4 2023, with a decline of 35.6%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $167.44 million (Q1 2026), $176.69 million (Q4 2025) and $156.4 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 | EverQuote | 588.97 Mn | -98.98 Mn | 190.73 Mn | 171.60 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 171.60 Mn |
| Mar 31, 2026 | 167.44 Mn |
| Dec 31, 2025 | 176.69 Mn |
| Sep 30, 2025 | 156.40 Mn |
| Jun 30, 2025 | 142.46 Mn |
| Mar 31, 2025 | 158.64 Mn |
| Dec 31, 2024 | 135.43 Mn |
| Sep 30, 2024 | 132.86 Mn |
| Jun 30, 2024 | 110.85 Mn |
| Mar 31, 2024 | 89.30 Mn |
| Dec 31, 2023 | 62.47 Mn |
| Sep 30, 2023 | 84.42 Mn |
| Jun 30, 2023 | 81.36 Mn |
| Mar 31, 2023 | 111.65 Mn |
| Dec 31, 2022 | 96.99 Mn |
| Sep 30, 2022 | 109.81 Mn |
| Jun 30, 2022 | 105.74 Mn |
| Mar 31, 2022 | 116.38 Mn |
| Dec 31, 2021 | 110.54 Mn |
| Sep 30, 2021 | 115.35 Mn |
API Access
EverQuote 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=EVER&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "EVER", "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=EVER&period=max&api_key=YOUR_API_KEY");
const data = await res.json();