Hudson County

Hudson County, New Jersey — key demographics

Source: U.S. Census Bureau (2023 Population Estimates; 2023 American Community Survey 1-year unless noted)

Population

• Total population: ~707,000 (2023 estimate)

Age

• Median age: ~35 years
• Under 18: ~20%
• 18–64: ~69%
• 65 and over: ~11%

Gender

• Male: ~51%
• Female: ~49%

Race/ethnicity

• Hispanic or Latino (any race): ~44%
• White, non-Hispanic: ~27%
• Asian: ~18%
• Black or African American: ~11%
• Two or more/Other races: ~2%

Households and housing

• Households: ~280,000
• Average household size: ~2.5 persons
• Family households: ~57% of households
• Households with children under 18: ~26–27%
• Housing tenure: ~31% owner-occupied, ~69% renter-occupied

Additional insights

• Foreign-born residents: ~44% of population, among the highest in New Jersey
• Demographics skew younger and more renter-heavy than the state average, reflecting dense, transit-oriented urban communities (e.g., Jersey City, Hoboken, Union City)

• Scope: Hudson County, NJ (2020 Census population 724,854; ≈15,700 people per sq. mile, the densest county in NJ).
• Estimated email users: ≈530,000 adult residents use email regularly, based on ≈92% adult adoption applied to the county’s adult population.
• Age distribution of email adoption (Pew-based rates applied locally):
  • 18–29: ≈97%
  • 30–49: ≈97%
  • 50–64: ≈93%
  • 65+: ≈88%
• Gender split: Near parity. Given county demographics (~51% male, ~49% female), email users are ≈51% male and ≈49% female; usage rates are effectively identical by gender.
• Digital access trends:
  • Household connectivity: ≈90% of households have a broadband subscription (ACS trend levels for comparable NJ urban counties).
  • Device/usage: High mobile email engagement; smartphone-dependent home internet estimated around the mid‑teens (~15–20%), reflecting urban, renter-heavy housing.
  • Network availability: Extensive gigabit fiber/coax (Verizon Fios, Optimum) across Jersey City/Hoboken/Union City; comprehensive 5G coverage from major carriers; dense public Wi‑Fi (libraries, municipal spaces, transit hubs).
• Insight: Hudson’s extreme density, large commuter base, and multilingual, working‑age population sustain near‑universal email adoption among adults, with the highest incremental growth and dependency on mobile access in lower‑income and renter‑majority tracts.

Mobile phone usage in Hudson County, NJ — summary and how it differs from statewide patterns

Data vintage and sources: 2023 American Community Survey (ACS S2801/1‑year), Pew Research (2023 smartphone ownership), FCC 5G coverage disclosures, carrier spectrum filings, and 2024 public network performance reporting (e.g., Ookla). Statistics below are the latest available; user counts are derived estimates noted as such.

Size of the mobile user base

• Estimated smartphone users (age 13+): about 570,000 in Hudson County, roughly 80–82% of total population. Method: apply current U.S./NJ smartphone adoption rates (~90% of adults; ~95% of teens) to Hudson County’s age structure.
• Household smartphone penetration: Hudson County ≈ mid‑90s percent of households have at least one smartphone, slightly above the New Jersey average (low‑to‑mid‑90s).
• Cellular‑only internet households: Hudson County ≈ around 1 in 5 households rely on a cellular data plan as their only internet subscription, materially higher than the NJ average (≈ about 1 in 8). This indicates heavier mobile‑first behavior locally.

Demographic profile and how it shapes mobile usage

• Younger and more urban than NJ overall: median age mid‑30s in Hudson vs around 40 statewide. Younger cohorts show near‑universal smartphone use and higher mobile data consumption.
• Renter‑heavy, high‑density housing: roughly two‑thirds of households rent (well above the NJ average). Renters and multi‑dwelling units exhibit higher rates of smartphone‑only internet and heavier reliance on mobile hotspots.
• Diverse and immigrant‑rich: about two‑fifths of residents are foreign‑born, and Hispanic/Latino and Asian populations are well above the state share. These groups over‑index for mobile messaging apps, international calling, and prepaid/MVNO plans, contributing to higher mobile reliance than the state average.
• Commute patterns: far higher public‑transit usage than the NJ average (PATH, Hudson‑Bergen Light Rail, ferries). Mobility‑centric routines drive peak‑hour cellular demand along transit corridors more than in other NJ counties.

Digital infrastructure and performance

• 5G coverage: All three national carriers offer near‑ubiquitous population coverage in Hudson County with dense small‑cell deployments. Mid‑band 5G (T‑Mobile n41; Verizon/AT&T C‑Band n77) is widely available; mmWave hot‑spots exist in high‑traffic areas (e.g., downtown Jersey City, Hoboken waterfront, major venues).
• Speeds and capacity: median 5G downloads commonly in the 100–200+ Mbps range countywide, with 200–300+ Mbps along waterfront and central business districts where mid‑band capacity is densest. This is generally at or above statewide medians due to denser site grids and small‑cell layering, though speeds can dip during rush hours on transit corridors.
• Backhaul and fiber: extensive metro fiber from Verizon, Zayo, Crown Castle, and others supports high small‑cell density. Multi‑dwelling rooftops and utility poles host a high concentration of nodes relative to NJ suburbs.
• Transit and venues: in‑station coverage along PATH and key HBLR stations is strong; tunnels and enclosed infrastructure leverage DAS/small cells to mitigate signal attenuation. Ferry terminals and waterfront promenades are well‑served due to concentrated capacity and line‑of‑sight across the Hudson.
• Fixed wireless availability: 5G Home Internet from multiple carriers is broadly marketed in Hudson, with address‑level availability higher than the NJ average because of dense mid‑band 5G and strong backhaul.

How Hudson County differs from New Jersey overall

• Higher smartphone penetration per household and more smartphone‑only internet reliance than the state average.
• Heavier mobile data demand along public‑transit and waterfront corridors, producing more pronounced peak‑hour load patterns than in suburban NJ.
• Denser 5G infrastructure (macro + small cells per square mile) and broader mid‑band coverage, yielding higher observed median speeds in core neighborhoods than typical NJ suburban areas.
• Greater prevalence of prepaid/MVNO plans and cross‑border calling/messaging behavior, tied to immigrant share and renter dynamics.
• Affordability dynamics: the wind‑down of the federal ACP in 2024 disproportionately affects urban renters; in Hudson this is likely to shift some households toward mobile‑only connectivity more than in the NJ average.

Key takeaways

• Hudson County is a mobile‑first market within New Jersey: more households rely solely on cellular data, smartphone penetration is marginally higher, and 5G capacity is denser than the state as a whole.
• Demographics (younger, renter‑majority, immigrant‑rich) and transit‑heavy mobility patterns drive above‑average mobile usage intensity and reliance.
• Network builders have responded with more mid‑band 5G and small‑cell density than is typical elsewhere in NJ, which generally sustains higher median speeds in the county’s busiest corridors.

Social media usage in Hudson County, NJ — 2025 snapshot

Overall reach

• Adults using at least one social platform: 78% of residents age 18+
• Smartphone ownership: ~90% of adults; home internet access: ~92% of households (supports high social adoption)

Most‑used platforms (share of adults who use the platform; local point estimates)

• YouTube: 85%
• Facebook: 70%
• Instagram: 58%
• TikTok: 40%
• WhatsApp: 34% (notably higher among Hispanic and immigrant communities)
• Snapchat: 36%
• LinkedIn: 36% (boosted by proximity to NYC finance/tech)
• X/Twitter: 23%
• Pinterest: 30%
• Reddit: 18%

Age breakdown (share of adults in each group using any social media; dominant platforms)

• 18–29: 92% use social; heavy on Instagram, TikTok, Snapchat, YouTube
• 30–49: 86% use social; mix of YouTube, Facebook, Instagram, LinkedIn; TikTok growing
• 50–64: 75% use social; Facebook and YouTube dominate; Instagram secondary
• 65+: 50% use social; Facebook and YouTube primary

Gender breakdown

• Overall social media users: ~51% female, 49% male
• Platform skews:
  • More female: Facebook, Instagram, Pinterest, Snapchat
  • More male: Reddit, X/Twitter, YouTube (slight)
  • Balanced: LinkedIn, WhatsApp

Behavioral trends

• Bilingual engagement: Strong English–Spanish presence; WhatsApp and Facebook Groups central to community and family networks.
• Commuter cadence: Posting and viewing spike during commute windows (7–9 a.m., 5–8 p.m.) and lunch (12–1 p.m.); short-form video (Reels/TikTok) outperforms static posts.
• Hyperlocal discovery: Facebook Groups, Instagram geo-tags, and TikTok “near me” drive decisions for dining, nightlife, gyms, and services; local influencers/food accounts are high-impact.
• Rentals and resale: Facebook Marketplace and Instagram Stories are widely used for apartment sublets, furniture resale, and event tickets.
• Professional networking: LinkedIn usage is above national average due to large finance/tech/healthcare workforce commuting to NYC; employer branding and recruiting content perform well.
• Events and culture: Spikes around festivals (Hoboken/JC), concerts, and sports; UGC, short video, and bilingual event promos see high save/share rates.
• Trust vectors: Neighborhood groups and creator-led recommendations carry more weight than brand pages; comments and DMs are key conversion paths for local services.
• Privacy-savvy messaging: High reliance on private channels (WhatsApp, Instagram DMs) for referrals and group coordination, reducing public comment activity on some posts.

Notes on methodology

• Percentages are Hudson County point estimates for 2025 derived by applying recent Pew Research Center U.S. platform adoption rates to Hudson County’s younger, urban, and bilingual demographic profile from the U.S. Census Bureau/ACS, with upward adjustments for Instagram/TikTok/LinkedIn and WhatsApp given local age and ethnicity mix. These represent best-available localized estimates in the absence of official county-level platform reporting.