Campbell County

Here are key demographics for Campbell County, South Dakota (U.S. Census Bureau; primarily 2020 Decennial Census and 2018–2022 ACS 5-year estimates; rounded):

Population size

• Total population: 1,377 (2020 Census)
• 2023 estimate: ~1,300

Age

• Median age: ~51 years
• Under 18: ~19%
• 18–64: ~51%
• 65 and over: ~30%

Gender

• Male: ~52%
• Female: ~48%

Race/ethnicity

• White (non-Hispanic): ~96%
• American Indian/Alaska Native: ~1–2%
• Two or more races: ~1–2%
• Hispanic/Latino (any race): ~2%
• Black/African American, Asian, other: each ~0–1%

Household data

• Households: ~640–660
• Average household size: ~2.1
• Family households: ~60–62% of households
• Married-couple families: ~50–55% of households
• Nonfamily households: ~38–40%
• One-person households: ~34%
• Householder living alone age 65+: ~17%

Note: Figures reflect the latest available Census/ACS estimates for a small population county; small-sample variability may cause minor year-to-year shifts.

Campbell County, SD snapshot (estimates)

• Population: ~1,370 (2020), density ~1.8 people/sq mi across ~770 sq mi.
• Estimated email users: 950–1,100 adults (out of ~1,100 adults), based on rural SD internet/email adoption rates.
• Age distribution of email users:
  • 18–29: 12–15%
  • 30–49: 28–32%
  • 50–64: 26–30%
  • 65+: 22–28% (lower adoption but large local share raises this slice)
• Gender split among users: roughly even; ~50–52% male, ~48–50% female.
• Digital access trends:
  • Household broadband subscription likely 75–82% (ACS-based for very rural SD).
  • 10–15% are smartphone-only internet users; fixed wireless and satellite are common where wired service is limited.
  • Ongoing fiber buildouts via South Dakota’s ConnectSD (2021–2024) are improving speeds and reliability; gradual uptick in subscriptions.
• Connectivity context: Very low settlement density raises last‑mile costs and coverage gaps; community anchors (schools, libraries) and public Wi‑Fi help bridge access for some residents.

Notes: Figures are modeled from 2020 Census/ACS, state broadband reports, and national email adoption (Pew); exact county-level email counts are not directly surveyed.

Below is a county-level picture built from Census/ACS population, rural tech-adoption research, statewide carrier footprints, and typical rural utilization patterns. Figures are estimates with ranges to reflect uncertainty in such a small, rural county.

Quick profile

• Population baseline: ~1,350–1,450 residents (2020 Census was 1,408; slight decline since).
• Settlement pattern: Very rural, with residents concentrated in Herreid, Pollock, and Mound City; large farm/ranch areas between towns; cross‑border ties to North Dakota.
• Age structure: Older than the state average; a high share of 65+ and relatively few 18–34.

Estimated mobile phone users

• Any mobile phone (smartphone or basic): 1,100–1,250 users (roughly 80–88% of residents; lower than statewide).
• Smartphones: 950–1,120 users (about 70–80% of residents; meaningfully lower than the ~85–90% typical in SD’s cities).
• Cellular‑primary home internet households: ~115–160 households (roughly 18–25% of households) rely mainly on cellular or satellite rather than wired service—higher than statewide due to sparse last‑mile options outside town centers.

Demographic breakdown (ownership/use patterns)

• By age
  • 18–34: Smartphone adoption ~95–98%; heavy app/social/video use; unlimited data plans common.
  • 35–64: Smartphone adoption ~88–92%; mix of postpaid family plans; hotspots used for field work and school.
  • 65+: Smartphone adoption ~50–60%; higher basic/flip‑phone use (15–25%); more voice/SMS‑centric behavior and smaller data buckets.
• By geography
  • In‑town residents (Herreid, Pollock, Mound City): Higher smartphone and 5G adoption; better indoor coverage and more wired alternatives.
  • Farm/ranch households: More device sharing, external antennas/boosters, and reliance on hotspots or satellite; slower upgrade cycles.
• Cultural/occupational factors
  • Agriculture and trucking drive daytime, seasonal peaks during planting/harvest and along highway corridors.
  • Communal/religious communities present in the region can have different norms regarding personal smartphones, slightly reducing per‑capita adoption relative to the state.

Carrier and plan mix (indicative)

• Carrier share: Verizon often leads in this border/rural area, AT&T a strong second, T‑Mobile more limited; rough pattern: Verizon 45–55%, AT&T 30–40%, T‑Mobile/others 5–15%.
• Plans: Postpaid family plans dominate; prepaid share somewhat higher than in urban SD but still minority (roughly 15–25%). External antennas/boosters are more common than statewide.

Digital infrastructure and coverage

• Macro cell sites: On the order of 4–7 in‑county macros, with additional coverage spilling in from neighboring counties and ND sites. Coverage is good on primary corridors and in towns; patchier between them and along Lake Oahe/Missouri River bluffs.
• 4G LTE: Broad outdoor coverage; indoor reliability varies in metal‑roof buildings and at the edges of town; farmsteads often need boosters.
• 5G:
  • Present mainly as low‑band/DSS from Verizon/AT&T; T‑Mobile low‑band with pockets of mid‑band nearer highways/towns. No mmWave.
  • Typical real‑world speeds: low‑band 5G that feels like strong LTE; mid‑band pockets can be faster near towns, but countywide availability lags cities.
• Backhaul: Mix of microwave and limited fiber; fiber concentrated in/near towns and along main routes. This constrains 5G capacity growth outside towns compared with Sioux Falls/Rapid City.
• Home broadband landscape: Town centers may have fiber or cable from regional providers; many rural addresses depend on LTE/5G fixed wireless or satellite (Starlink, Viasat/Hughes). T‑Mobile Home Internet and Verizon 5G Home are spotty to moderate, tied to sector capacity and signal quality.

Usage patterns versus South Dakota overall (what’s different)

• Lower smartphone penetration and lower per‑line data consumption than urban SD, driven by older demographics and weaker 5G capacity off‑corridor.
• Higher share of basic/flip‑phone users among seniors; longer device replacement cycles.
• Greater reliance on cellular hotspots for home/work connectivity outside towns; cellular‑primary households are more common than the state average.
• Coverage is more uneven: robust on corridors/in towns but notable dead zones between them; 5G is largely low‑band with fewer mid‑band capacity sites than state metros.
• Seasonal and cross‑border effects are stronger: traffic spikes tied to ag cycles, recreation on Lake Oahe, and cross‑state movement to/from North Dakota; residents often pick carriers based on border‑area coverage rather than SD‑only performance.

Implications

• For outreach and services: Keep SMS/voice channels prominent; don’t assume consistent high‑throughput 5G outside towns.
• For network investment: Biggest gains come from additional mid‑band 5G sectors and fiber backhaul on rural macros; targeted small cells in town centers.
• For digital equity: Senior‑focused training and device support, plus expanded fixed wireless or fiber to farmsteads, would narrow the gap with the rest of SD.

Notes on methodology

• Estimates combine county population/age structure, national/rural tech‑adoption rates, and known rural carrier footprints in northern SD/ND border areas. Small‑area figures are presented as ranges due to limited public, granular datasets for a county this size.

Below is a concise, directional snapshot. Because platform companies and public sources don’t publish county-level social media metrics, figures are estimates built from Pew Research Center’s latest U.S. social media use by age/gender, rural-urban adjustments, and typical patterns in rural South Dakota. Use ranges as guideposts.

Overall usage (adults 18+)

• Active on at least one platform monthly: 65–75%
• Daily social media users: 55–65%
• Average platforms used per person: 2–3

Most-used platforms among adults (estimated share of adults)

• Facebook: 55–65% (daily 40–50%); Messenger: 45–55%
• YouTube: 60–70% (weekly 55–65%)
• Instagram: 25–35%
• Snapchat: 20–30% (heavily <30)
• TikTok: 20–30% (daily 15–20%)
• Pinterest: 20–30% (skews female)
• X (Twitter): 10–15%
• LinkedIn: 10–15%
• Reddit: 8–12%

Age profile (estimated share using any social media; top platforms)

• Teens (13–17): 85–95%; Snapchat, TikTok, YouTube; Instagram next; Facebook minimal
• 18–29: 90%+; YouTube, Instagram, Snapchat, TikTok; Facebook for groups/Marketplace
• 30–49: 80–90%; Facebook and YouTube dominant; Instagram/Pinterest secondary; TikTok rising
• 50–64: 65–75%; Facebook, YouTube; some Pinterest
• 65+: 45–55%; Facebook, YouTube; reliance on Messenger

Gender patterns (within-gender adoption tendencies)

• Women: higher on Facebook (60–70%) and Pinterest (25–35%); Instagram 30–40%; TikTok 22–32%
• Men: higher on YouTube (65–75%), Facebook 50–60%; X 12–18%; Reddit 10–15%

Behavioral trends to expect in Campbell County

• Facebook is the community hub: local news, school and church updates, ag and buy/sell groups; Marketplace widely used.
• Messaging-first behavior: Many residents DM via Messenger to ask questions or book; fewer public comments.
• Video consumption > creation: Short, captioned clips perform best (weather, local sports, farm how‑tos, county events).
• Trust is local: Posts naming local people/places and practical info outperform generic content.
• Mobile-first, bandwidth-aware: Keep videos short/light; add captions; image carousels work well in low-connectivity pockets.
• Peak attention windows: early mornings and evenings; weekend afternoons for community and event content.
• Seasonal spikes: planting/harvest and severe weather drive surges to local government, extension, and news pages.
• Privacy cautious: Preference for DMs or phone over web forms; clear, low-friction calls to action work best.
• Targeting radius: 25–50 miles around towns captures most reachable audience; lookalikes can be thin due to small base.

Notes and methods

• Figures are modeled from national platform use (Pew), rural adjustments, and South Dakota’s older age profile outside major metros. County-specific platform data are not publicly released; treat as estimates. If you can share current ACS age/sex counts for Campbell County, we can refine these ranges.