Goochland County

Goochland County, Virginia — key demographics (U.S. Census Bureau, ACS 2019–2023 5‑year estimates; rounded)

• Population: ~26,600
• Median age: ~47–48 years
• Age distribution:
  • Under 18: ~20%
  • 18 to 64: ~58–59%
  • 65 and over: ~21–22%
• Sex:
  • Female: ~51%
  • Male: ~49%
• Race/ethnicity:
  • White (non-Hispanic): ~78–79%
  • Black or African American (non-Hispanic): ~13–14%
  • Hispanic/Latino (any race): ~4–5%
  • Asian: ~1–2%
  • Two or more races: ~2–3%
  • Other (incl. AIAN, NHPI, some other race): ~1% combined
• Households:
  • Total households: ~10,200
  • Average household size: ~2.45–2.50
  • Family households: ~70–72% (married-couple ~58–60%)
  • Households with children under 18: ~26–27%
  • Nonfamily households: ~28–30%; living alone ~23–24% (65+ living alone ~8–9%)
  • Owner-occupied housing rate: ~84–86%

Source: U.S. Census Bureau, American Community Survey 2019–2023 5-year; profile: https://data.census.gov/profile/Goochland_County,_Virginia?g=0500000US51075 (Note: Percentages may not sum to 100 due to rounding.)

Goochland County, VA snapshot

• Scale and density: Population ≈27,000; low-density/exurban (~90–100 people per sq. mi.) west of Richmond.
• Estimated email users: 22,000–24,000 residents (driven by very high adult adoption; lower among seniors and teens).
• Age distribution of email users (approx.):
  • 18–49: 45–50% of users (adoption ~95–99%)
  • 50–64: 25–30% (adoption ~90–95%)
  • 65+: 15–20% (adoption ~75–85%)
  • 13–17: 5–10% (adoption ~60–75%)
• Gender split: Roughly even, mirroring the population (≈49% male, 51% female).
• Digital access and trends:
  • Most households have a computer and home internet; broadband subscription likely in the mid‑80s to low‑90s percent range, with a small smartphone‑only segment.
  • Best connectivity clusters along I‑64/Route 288 corridors and village centers; more gaps or reliance on fixed‑wireless/legacy DSL in lower‑density western/river‑adjacent areas.
  • Ongoing state‑supported fiber buildouts are reducing remaining unserved pockets.
  • Email use is effectively universal for working‑age residents; incremental growth comes from older adults coming online and improved rural broadband. Smartphone-centric access is rising, but multi‑device households remain common.

Figures are estimates based on county size and U.S. email/digital access patterns applied to Goochland’s rural‑exurban profile.

Below is a concise, county-focused snapshot that pulls together best-available public indicators (ACS/Pew/FCC/state broadband program data) and local context. Figures are estimates; small-county samples and rapidly changing network builds introduce uncertainty.

At-a-glance user estimates (2025)

• Population: about 26,000; adults roughly 21,000–22,000.
• Smartphone users: 19,000–21,000 adults (about 88–92% of adults). Virginia overall sits roughly in the low 90s, so Goochland is very similar overall but with more variation by place and age.
• Smartphone-dependent for internet (no wired home broadband, rely on cellular): about 4–7% of households in 2025, down from roughly 7–10% in 2021–2022 as new fiber reached previously unserved areas. Statewide smartphone-dependence is flatter and a bit higher in many rural counties; Goochland’s rate is falling faster because of accelerated fiber buildouts.

Demographic patterns (how usage differs inside the county)

• Age:
  • 18–34: near-universal smartphone ownership (≈97–99%); heavy app and streaming use; common as a backup to home broadband rather than a substitute in the east.
  • 35–64: very high ownership (≈93–96%); multiple lines per household; frequent hotspotting for travel/commute.
  • 65+: high but lagging (≈78–85%); rapid growth, driven by telehealth/alerts. This cohort pulls the countywide rate slightly below the statewide average despite strong adoption in younger groups.
• Income and housing:
  • Higher-income, owner-occupied households (prevalent in eastern/suburban Goochland) show near-universal smartphone ownership and typically pair it with wired broadband.
  • Lower-income and more rural households (central/western Goochland) historically showed higher smartphone-only internet reliance; that reliance is receding as fiber and fixed wireless reach those areas.
• Geography within the county:
  • East (Manakin-Sabot/eastern corridors): looks like suburban Richmond—dense 4G/5G, high speeds, high device penetration, and low smartphone-dependence.
  • Central/west (Goochland Courthouse, Hadensville/Columbia): more coverage variability and historically higher mobile-only internet use; improving quickly with new fiber and better low-/mid-band 5G.

Digital infrastructure points

• Cellular coverage and performance:
  • 5G low-band is broadly available; mid-band 5G (C-band/2.5 GHz) is strongest along I-64 and the eastern half of the county; mmWave is rare.
  • Speeds typically range from 20–80 Mbps on low-band LTE/5G in rural stretches to 200–400+ Mbps on mid-band 5G near major corridors and population centers. Indoor performance can dip in larger-lot, wooded areas.
  • Site density is lower than the state average (Virginia’s average is pulled up by NOVA/Hampton Roads), so Goochland relies more on macro sites, with fewer small cells outside the eastern edge.
• Fixed broadband overlap (key to mobile usage patterns):
  • Eastern Goochland has long had cable broadband; mobile is a complement.
  • County-backed fiber projects (notably partnerships involving All Points Broadband and Dominion Energy) from 2022–2025 are converting many formerly unserved rural addresses to fiber-to-the-home, reducing smartphone-only reliance.
  • Fixed wireless access (T‑Mobile/Verizon) is available along main corridors and serves as a stopgap or competitive alternative where cable/fiber is absent or newly arriving.

How Goochland differs from Virginia overall

• Sharper east–west split: The county combines suburban-grade 5G and broadband in the east with rural constraints in the west, creating bigger within-county performance gaps than the typical Virginia county.
• Faster decline in smartphone-dependence: Thanks to aggressive fiber builds, the share of mobile-only households is dropping more quickly than the statewide rural average.
• Slightly lower overall adoption pressure from age: An older age profile than the state average tempers countywide smartphone adoption a bit, even though younger and higher-income segments are at or above state levels.
• Coverage density: Fewer cell sites per square mile than urban Virginia leads to more noticeable dead spots off main corridors, even as mid-band 5G expands.

Notes on method and confidence

• Estimates blend American Community Survey device/connection indicators (5‑year for small geographies), Pew statewide/rural adoption patterns, FCC mobile coverage filings, and Virginia broadband grant activity. Small-sample margins and fast-moving 5G/fiber deployments mean local conditions can outperform or lag these ranges by neighborhood.

Below is a concise, decision-ready view of social media usage in Goochland County, VA. County-specific platform data aren’t publicly reported, so figures are modeled from recent U.S./Virginia patterns (Pew Research Center 2023–2024; ACS) and should be treated as directional.

Headline user stats

• Population context: Small, suburban–rural county; median age mid‑40s; high homeownership and commuting ties to the Richmond metro.
• Estimated adult social media users: ~70–80% of adults. For a county of roughly mid‑20Ks population with a large adult share, that equates to approximately 15K–18K adults on at least one platform.
• Device behavior: Predominantly mobile; video is the default format (short‑form and YouTube).

Age breakdown (share of adults in each group using at least one social platform; modeled on U.S. usage)

• 18–29: ~85–90% use social media. Heaviest on YouTube, Instagram, Snapchat, TikTok.
• 30–49: ~80–85%. Facebook and YouTube are anchors; growing Instagram and TikTok use.
• 50–64: ~70–78%. Facebook and YouTube dominant; Pinterest meaningful among women.
• 65+: ~45–55%. Facebook first; YouTube second; smaller but active local‑info usage (e.g., neighborhood apps/groups).

Gender notes

• Overall social usage is similar by gender.
• Platform skews: Pinterest skews female; Reddit and (to a lesser extent) LinkedIn skew male; Facebook and Instagram are broadly balanced; TikTok slightly female.

Most‑used platforms (estimated percent of adults; expect similar levels locally)

• YouTube: ~80–85%
• Facebook: ~65–70%
• Instagram: ~40–50%
• TikTok: ~30–35%
• Pinterest: ~30–35% (heavily female)
• LinkedIn: ~25–30% (higher among college‑educated/professionals; commuters to Richmond)
• Snapchat: ~25–30% (concentrated under 30)
• X/Twitter: ~20–23%
• Neighborhood apps (e.g., Nextdoor/Facebook Groups): pockets of high engagement in subdivisions; no reliable percent estimate

Behavioral trends to know

• Local information first: High engagement with county/sheriff/schools, road/utility updates, weather alerts, lost/found pets, and community events. Facebook Groups/Pages function as the de facto local bulletin board; neighborhood apps used for HOA updates and contractor recommendations.
• Marketplace and referrals: Facebook Marketplace and buy/sell/trade groups are primary channels for local commerce; word‑of‑mouth posts drive service-provider discovery (home, landscaping, pet/equine services).
• Video‑led consumption: Short vertical video (Reels/TikTok/Shorts) for quick updates and local highlights; YouTube for how‑to (home/garden, outdoors, DIY) and sports recaps (youth/high school).
• Time-of-day patterns: Evenings (7–10 pm) and weekends see the highest local engagement; school‑year rhythms affect weekday spikes (early morning bus/weather checks; late afternoon/evening sports).
• Community identity: Content featuring recognizable places, local teams, churches, and volunteer/civic groups performs best; “neighbors helping neighbors” tone outperforms overt sales.
• Demographic tilt: Older homeowners remain Facebook‑centric; younger residents split time across Instagram, TikTok, and Snapchat; professionals maintain LinkedIn for regional networking (Richmond metro employment base).
• Privacy/news: Many older users rely on Facebook for local news; some skepticism of TikTok among older cohorts.

How to localize these estimates quickly

• Use platform ad planners (Meta, TikTok, Snapchat, LinkedIn) with Goochland geo targeting to pull real‑time “estimated audience” counts by age/gender; this provides the most actionable local percentages without running ads.

Sources and method note

• Estimates synthesized from Pew Research Center’s 2023–2024 U.S. social media use reports and U.S. Census/ACS demographics; county‑level platform data are not directly published. Treat figures as directional and validate with platform audience tools for Goochland targeting.