Neighborhood Intelligence (NXH) Accumulated Expenses (2010 - 2026)
Neighborhood Intelligence (NXH) recorded Accumulated Expenses of $68.25 million in Q2 2026, up 44.9% from $47.09 million a year earlier and up 43.7% from the prior quarter.
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Analysis
Neighborhood Intelligence (NXH) Accumulated Expenses (2010 - 2026) Analysis & Trends
At the end of FY2025, Neighborhood Intelligence reported Accumulated Expenses of $51.3 million, down 30.3% from FY2024.
- Annual Accumulated Expenses has a five-year compound annual growth rate of -16.1% (FY2020 to FY2025).
- Across earlier years, Accumulated Expenses came in at $73.61 million in FY2024 (-0.1%), $73.68 million in FY2023 (+15.8%), $63.61 million in FY2022 (-37.6%) and $101.9 million in FY2021 (-17.6%).
- The Q2 2026 figure is the highest quarterly Accumulated Expenses since Q4 2024.
- On a year-over-year basis, Accumulated Expenses rose in 1 of the last eight quarters, with an average decline of 10.2%.
- Peak year-over-year performance for Accumulated Expenses in the last five years was growth of 44.9% in Q2 2026, against a decline of 37.6% in Q4 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $47.48 million (Q1 2026), $51.3 million (Q4 2025) and $48.84 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Amazon Com | 2,712.14 Bn | 2,228.84 Bn | 104.83 Bn |
| 2 | Home Depot | 282.27 Bn | 275.52 Bn | 16.12 Bn |
| 3 | Tjx Companies | 146.16 Bn | 123.70 Bn | 5.07 Bn |
| 4 | Lowes Companies | 101.42 Bn | 94.39 Bn | 8.58 Bn |
| 5 | Ross Stores | 73.06 Bn | 55.98 Bn | 2.12 Bn |
| 6 | Target | 70.86 Bn | 65.45 Bn | 8.94 Bn |
| 7 | Carvana | 70.11 Bn | 61.71 Bn | 1.38 Bn |
| 8 | O Reilly Automotive | 69.29 Bn | 68.38 Bn | 2.52 Bn |
| 9 | Autozone | 45.61 Bn | 44.51 Bn | 2.52 Bn |
| 10 | Neighborhood Intelligence | 225.66 Mn | -351.99 Mn | 96.68 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 68.25 Mn |
| Mar 31, 2026 | 47.48 Mn |
| Dec 31, 2025 | 51.30 Mn |
| Sep 30, 2025 | 48.84 Mn |
| Jun 30, 2025 | 47.09 Mn |
| Mar 31, 2025 | 61.57 Mn |
| Dec 31, 2024 | 73.61 Mn |
| Sep 30, 2024 | 54.32 Mn |
| Jun 30, 2024 | 61.31 Mn |
| Mar 31, 2024 | 72.53 Mn |
| Dec 31, 2023 | 73.68 Mn |
| Sep 30, 2023 | 72.48 Mn |
| Jun 30, 2023 | 62.60 Mn |
| Mar 31, 2023 | 68.59 Mn |
| Dec 31, 2022 | 63.61 Mn |
| Sep 30, 2022 | 88.83 Mn |
| Jun 30, 2022 | 91.79 Mn |
| Mar 31, 2022 | 107.91 Mn |
| Dec 31, 2021 | 101.90 Mn |
| Sep 30, 2021 | 103.90 Mn |
API Access
Neighborhood Intelligence Accumulated 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=accumulated-expenses&ticker=NXH&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "NXH", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=NXH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();