Davison County

Key demographics for Davison County, South Dakota (latest U.S. Census Bureau estimates; population as of 2023, other details from ACS 2019–2023 5-year):

• Population: ~20,800 (2023 estimate)
• Age:
  • Median age: ~38–39
  • Under 18: ~22%
  • 65 and over: ~18%
• Sex:
  • Male: ~50%
  • Female: ~50%
• Race and ethnicity:
  • White (non-Hispanic): ~89–90%
  • American Indian and Alaska Native: ~5%
  • Black or African American: ~1%
  • Asian: ~1%
  • Two or more races: ~3–4%
  • Hispanic or Latino (of any race): ~3%
• Households:
  • Number of households: ~8,600
  • Average household size: ~2.3
  • Family households: ~57–60% of households
  • Married-couple families: ~45–48% of households
  • Nonfamily households: ~40–43% of households

Sources: U.S. Census Bureau Population Estimates (Vintage 2023) and American Community Survey 2019–2023 5-year estimates.

Davison County, SD email usage (estimates)

• Population base: ~20,000 residents; majority live in Mitchell, yielding higher connectivity than rural townships.
• Estimated email users: 14,000–16,000 residents (roughly 70–80% of total; ~90%+ of adults).
• Age distribution of email users:
  • 13–17: ~5–8% (school-driven accounts; lower daily use)
  • 18–34: ~25–30% (near-universal adoption)
  • 35–64: ~40–48% (very high adoption)
  • 65+: ~18–22% (adoption high but less frequent use)
• Gender split: Approximately even (about 50/50 overall; women slightly higher among older cohorts).
• Digital access trends:
  • Home broadband subscription likely in the low-to-mid 80% of households (ACS-like rates for similar micropolitan counties).
  • 10–15% of households are smartphone-only internet users.
  • Strong mobile coverage along the I‑90 corridor and in Mitchell; rural areas see more variability in speeds and reliability.
  • Public access options (libraries, schools, municipal Wi‑Fi) supplement connectivity for lower-income and rural residents.
• Local density/connectivity facts: County density roughly 45–50 people per sq. mile; Mitchell concentrates ~70–80% of residents, supporting better broadband availability, while outlying areas face typical rural last‑mile constraints.

Summary: Mobile phone usage in Davison County, South Dakota (focus on ways it differs from statewide patterns)

At-a-glance user estimates (directional, 2025)

• Population and households: ~20–21k residents; ~8.4–8.8k households.
• Mobile phone users (any cell): ~17–18k residents use a cell phone.
• Smartphone users: ~15–16k residents.
• Mobile-only home internet households (smartphone/cellular as primary, no fixed broadband): ~10–13% of households (≈850–1,100). This is likely a bit lower than the South Dakota average because Mitchell has strong cable/fiber availability.
• Daytime devices: Traffic along I-90 and Mitchell’s role as a regional service/retail hub push daytime device counts well above resident-only figures on weekdays and event weekends.

What’s different from South Dakota overall

• Better coverage and capacity: Proximity to I-90 and a small urban core (Mitchell) mean denser macro sites, earlier mid-band 5G deployment, and generally higher in-town speeds than many rural SD counties.
• Lower smartphone-only dependence: Strong fixed broadband (citywide fiber/cable; rural fiber co-op footprints) keeps the share of mobile-only households lower than the statewide average.
• Slightly higher smartphone adoption among older adults: Access to healthcare systems, retail, and banking in Mitchell nudges 65+ smartphone uptake above the SD rural norm.
• Less tribal/remote context: A smaller share of American Indian/Alaska Native residents than the state overall means some statewide digital equity challenges (e.g., very remote coverage gaps) are less pronounced locally; the digital divide skews more by income and rural distance from Mitchell.
• Event- and corridor-driven load: Seasonal tourism and Corn Palace/event traffic create sharper, predictable mobile demand spikes than seen in many peer counties.

Demographic breakdown (patterns and implications)

• Age
  • 18–29: Very high smartphone ownership (≈95%+), boosted by the local college population; heavy use of social, streaming, and app-based mobility/food services.
  • 30–64: High ownership (≈90–95%); strong use of mobile banking, retail, and work messaging.
  • 65+: Estimated 70–80% smartphone ownership, a few points higher than many rural SD counties due to proximity to services and providers that encourage patient portals and two-factor auth.
• Income
  • < $35k: High smartphone ownership but higher likelihood of smartphone-only home internet; prepaid plans and MVNOs are common.
  • Middle and higher incomes: Greater device bundling (postpaid family plans, tablets/wearables), lower smartphone-only dependence thanks to fixed broadband availability.
• Education and students
  • College students push multi-device usage (phones + laptops/tablets) and drive demand for high-capacity mid-band 5G near campus and downtown.
• Race/ethnicity
  • American Indian/Alaska Native share is below the statewide average; aggregate county adoption rates therefore track closer to statewide white, non-Hispanic patterns. Equity gaps remain, but are driven more by income and rural location than by reservation adjacency.
• Urban vs rural within the county
  • Mitchell: Near-universal 4G and broad mid-band 5G; faster speeds and better indoor penetration.
  • Rural townships: Reliable low-band 5G/LTE coverage with pockets of weaker signal in low-lying/wooded areas; more adoption of cellular home internet where fiber hasn’t reached yet.

Digital infrastructure notes

• Cellular networks
  • Carriers: All three national carriers serve the county; strongest capacity in Mitchell and along I-90/SD-37.
  • 5G: Mid-band 5G (e.g., C-band/n41) commonly available in Mitchell with typical in-town median speeds well into the 100–300 Mbps range; low-band 5G and LTE dominate in outlying areas.
  • Coverage gaps: Small dead zones and capacity dips can occur away from corridors and in river/valley terrain; these are fewer than in many western and north-central SD counties.
• Backhaul and fiber
  • I-90 and Mitchell benefit from multiple fiber routes (regional providers/co-ops), which supports higher-capacity cell sites and quicker 5G upgrades versus many rural parts of the state.
• Fixed broadband context (affects mobile dependence)
  • City of Mitchell: Predominantly fiber and cable internet from local/regional ISPs, which reduces smartphone-only households.
  • Rural fringe: Co-op fiber is expanding; where absent, households often use cellular fixed wireless (5G Home/LTE) rather than satellite—another way Davison differs from parts of rural SD that still lean on satellite.
• Public safety and alerts
  • NG911 and Wireless Emergency Alerts are active; severe-weather alerts contribute to high opt-in rates for notifications and location services.

Implications for planning and outreach

• Capacity planning should prioritize downtown Mitchell, campus areas, and I-90 interchanges for event-driven surges.
• Digital equity work should focus on low-income and rural pockets (signal quality indoors, device affordability, and digital skills), rather than reservation-focused strategies common elsewhere in SD.
• Business and public service apps can expect strong in-town 5G performance and reliable LTE in rural areas; design for offline/low-bandwidth use still helps farm and exurban users.

Method note: Figures are directional estimates synthesized from recent national adoption research (e.g., Pew) and typical ACS county patterns, adjusted for Davison County’s population mix and infrastructure.

Below is a concise, best-available view based on Davison County’s size and demographics, combined with U.S./South Dakota social-media adoption patterns. Exact county-level platform data isn’t directly published, so figures are estimates with ranges.

Snapshot

• Population: ~20,000 (Davison County; majority in Mitchell). Adults ~15,000–16,000.
• Estimated social media users:
  • Adults (18+): ~10,500–12,000 (about 70–75% of adults).
  • Teens (13–17): ~900–1,100 users (very high adoption, 80–90%+).
  • Combined: roughly 11,500–13,000 residents using at least one platform.

Most‑used platforms (share of local adults; ranges reflect rural Midwest patterns)

• YouTube: 70–80%
• Facebook: 60–70% (dominant for community/news, groups, Marketplace)
• Instagram: 35–45% (skews under 40)
• TikTok: 25–35% overall; 50–65% for under 30
• Snapchat: 25–35% overall; 55–70% among teens/college-age
• Pinterest: 25–30% (women-heavy)
• X/Twitter: 15–20% (news/sports niche)
• LinkedIn: 12–18% (hiring/professional—healthcare, education, manufacturing)

Age mix among local social users (share of the user base)

• Teens 13–17: 7–9%
• 18–24: 10–12%
• 25–34: 16–18%
• 35–44: 16–18%
• 45–54: 15–17%
• 55–64: 13–15%
• 65+: 15–18% Notes: Davison has a noticeable 18–24 presence (college), and strong 35–64 cohorts.

Gender breakdown

• Population is roughly even; social usage leans slightly female overall.
• Estimated among active users: 52–54% women, 46–48% men.
• Platform skew: women over‑indexed on Facebook/Pinterest/Instagram; men on YouTube/X.

Behavioral trends to know

• Facebook = community hub: school updates, local government, high‑school sports, church/volunteer groups, buy‑sell/Marketplace.
• Groups > Pages: Neighborhood and interest groups outperform page posts for reach and discussion.
• Event‑driven spikes: County/city events (e.g., festivals, sports, weather alerts) trigger big surges in Facebook and local Instagram Stories.
• Messaging first: Facebook Messenger and Snapchat are primary for quick coordination; many businesses field inquiries via Messenger.
• Short‑form video growth: Reels/TikTok used for local business promos, hiring (seasonal/retail/healthcare), and sports highlights.
• Practical content wins: Farm/ranch, hunting/fishing, home services, and weather/school closures get high engagement; how‑to on YouTube performs well.
• Timing: Best engagement typically 7–9 a.m., 11:30 a.m.–1 p.m., and 7–9 p.m.; weekends good for events and promotions.
• Ads: Facebook/Instagram deliver efficient local reach; YouTube pre‑roll and Google Local Services complement. LinkedIn useful for healthcare/education recruiting.

Notes on method and confidence

• Built from U.S. Census/ACS demographics for county size and age, plus Pew Research and national/state rural adoption rates; localized by rural Midwest patterns and platform skews. Use ranges as directional benchmarks, not exact counts.