Nextdoor Holdings (NXDR) Operating Expenses (2021 - 2026)
Nextdoor Holdings' Operating Expenses came in at $80.22 million for Q2 2026, down 6.0% from $85.37 million a year earlier but up 4.2% from the prior quarter.
Nextdoor Holdings (NXDR) Operating Expenses (2021 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Nextdoor Holdings reported Operating Expenses of $320.25 million, down 4.5% year-over-year; for FY2025, it came in at $329.59 million, down 10.7% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 10.5% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $368.92 million in FY2024 (-5.6%), $390.59 million in FY2023 (+9.4%), $356.97 million in FY2022 (+24.4%) and $287 million in FY2021 (+43.5%).
- The five-year range for quarterly Operating Expenses is $71.79 million (Q3 2021) to $112.31 million (Q2 2024).
- Year-over-year, Operating Expenses has declined for eight consecutive quarters, with an average decline of 10.5% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q1 2022 (growth of 41.8%), and the weakest in Q2 2025 (a decline of 24.0%).
- Business Quant data shows NXDR's Operating Expenses at $77 million (Q1 2026), $76.9 million (Q4 2025) and $86.13 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,142.52 Bn | 3,900.05 Bn | 73.85 Bn | 79.03 Bn |
| 2 | Meta Platforms | 1,882.44 Bn | 1,584.96 Bn | 49.47 Bn | 42.03 Bn |
| 3 | Netflix | 292.72 Bn | 252.92 Bn | 6.52 Bn | 1.51 Bn |
| 4 | Alibaba Group Holding | 250.25 Bn | 68.12 Bn | 15.11 Bn | -5.17 Bn |
| 5 | Shopify | 192.03 Bn | 169.21 Bn | 1.71 Bn | 1.22 Bn |
| 6 | Uber Technologies | 141.56 Bn | 113.53 Bn | 6.38 Bn | 12.30 Bn |
| 7 | Booking Holdings | 121.98 Bn | 55.03 Bn | - | 4.85 Bn |
| 8 | PDD Holdings | 110.31 Bn | -141.62 Bn | 9.45 Bn | -5.39 Bn |
| 9 | AppLovin | 102.49 Bn | 92.52 Bn | 1.70 Bn | 429.41 Mn |
| 10 | Nextdoor Holdings | 937.40 Mn | -621.81 Mn | 63.08 Mn | 80.22 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 80.22 Mn |
| Mar 31, 2026 | 77.00 Mn |
| Dec 31, 2025 | 76.90 Mn |
| Sep 30, 2025 | 86.13 Mn |
| Jun 30, 2025 | 85.37 Mn |
| Mar 31, 2025 | 81.19 Mn |
| Dec 31, 2024 | 82.33 Mn |
| Sep 30, 2024 | 86.39 Mn |
| Jun 30, 2024 | 112.31 Mn |
| Mar 31, 2024 | 87.90 Mn |
| Dec 31, 2023 | 103.21 Mn |
| Sep 30, 2023 | 100.47 Mn |
| Jun 30, 2023 | 98.33 Mn |
| Mar 31, 2023 | 88.58 Mn |
| Dec 31, 2022 | 89.60 Mn |
| Sep 30, 2022 | 90.35 Mn |
| Jun 30, 2022 | 92.80 Mn |
| Mar 31, 2022 | 84.23 Mn |
| Dec 31, 2021 | 88.59 Mn |
| Sep 30, 2021 | 71.79 Mn |
Nextdoor Holdings 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=NXDR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "NXDR", "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=NXDR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();