Neighborhood Intelligence (NXH) Enterprise Value (2010 - 2026)
Neighborhood Intelligence's Enterprise Value came in at $374.23 million for Q2 2026, up 36.2% from $274.73 million a year earlier and up 100.8% from the prior quarter.
Powered by 
Analysis
Neighborhood Intelligence (NXH) Enterprise Value (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Neighborhood Intelligence reported Enterprise Value of -$104.26 million; for FY2025, it was $201.1 million, up 96.3% from FY2024.
- Enterprise Value carries a five-year compound annual growth rate of -34.1% (FY2020 to FY2025).
- Going back by year, Enterprise Value was $102.46 million in FY2024 (-89.3%), $954.91 million in FY2023 (+91.4%), $498.99 million in FY2022 (-75.5%) and $2.04 billion in FY2021 (+25.9%).
- The five-year range for quarterly Enterprise Value is $102.46 million (Q4 2024) to $2.84 billion (Q3 2021).
- Year-over-year, Enterprise Value increased in three of the last eight quarters, with an average decline of 7.5%.
- The fastest year-over-year change in Enterprise Value over five years came in Q1 2024 (growth of 156.0%), and the weakest in Q4 2024 (a decline of 89.3%).
- Business Quant data shows NXH's Enterprise Value at $186.38 million (Q1 2026), $201.1 million (Q4 2025) and $469.17 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Amazon Com | 2,659.84 Bn | 2,176.54 Bn | 104.83 Bn |
| 2 | Home Depot | 287.59 Bn | 280.83 Bn | 16.12 Bn |
| 3 | Tjx Companies | 147.38 Bn | 124.93 Bn | 5.07 Bn |
| 4 | Lowes Companies | 105.03 Bn | 97.99 Bn | 8.58 Bn |
| 5 | Ross Stores | 74.93 Bn | 57.86 Bn | 2.12 Bn |
| 6 | Target | 71.05 Bn | 65.64 Bn | 8.94 Bn |
| 7 | O Reilly Automotive | 70.25 Bn | 69.33 Bn | 2.52 Bn |
| 8 | Carvana | 69.96 Bn | 61.56 Bn | 1.38 Bn |
| 9 | Autozone | 46.92 Bn | 45.82 Bn | 2.52 Bn |
| 10 | Neighborhood Intelligence | 244.46 Mn | -333.19 Mn | 96.68 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 374.23 Mn |
| Mar 31, 2026 | 186.38 Mn |
| Dec 31, 2025 | 201.10 Mn |
| Sep 30, 2025 | 469.17 Mn |
| Jun 30, 2025 | 274.73 Mn |
| Mar 31, 2025 | 215.05 Mn |
| Dec 31, 2024 | 102.46 Mn |
| Sep 30, 2024 | 321.46 Mn |
| Jun 30, 2024 | 412.24 Mn |
| Mar 31, 2024 | 1.39 Bn |
| Dec 31, 2023 | 954.91 Mn |
| Sep 30, 2023 | 391.29 Mn |
| Jun 30, 2023 | 1.13 Bn |
| Mar 31, 2023 | 541.31 Mn |
| Dec 31, 2022 | 498.99 Mn |
| Sep 30, 2022 | 686.24 Mn |
| Jun 30, 2022 | 700.23 Mn |
| Mar 31, 2022 | 1.39 Bn |
| Dec 31, 2021 | 2.04 Bn |
| Sep 30, 2021 | 2.84 Bn |
API Access
Neighborhood Intelligence Enterprise Value 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=enterprise-value&ticker=NXH&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "enterprise-value", "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=enterprise-value&ticker=NXH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();