The number of smartphone users in the United States was forecast to continuously increase between 2024 and 2029 by in total 17.4 million users (+5.61 percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach 327.54 million users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like Mexico and Canada.
This dataset contains mobile wireless download speed test results and areas where the PSD (Vermont Public Service Department) challenged mobile wireless service asserted by wireless carriers.DOWNLOAD SPEED TEST RESULTSResults from download speed tests that were conducted in September-December 2018 are contained by 6 point feature-classes, each with results for a particular carrier.PSD staff employed the android smartphone application G-NetTrack to conduct download speed tests at approximately 300 meter intervals along all federal-aid highways.The point feature-classes are very detailed and more suitable when zoomed into the neighborhood scale. All point feature-classes have the same field schema, which includes these fields: timestamp: Date and time at which the data point was collected. signal_str: Signal strength (RSRP in dBm). download_s: Download speed (in Mbps). latency: The round-trip time for a request to a website, in milliseconds.DRIVE-TEST BLOCKSDrive-test blocks (Utility_DriveTest_poly_Blocks) is a polygon feature-class that is composed of 1-kilometer blocks; it has a field for each of the 6 carriers; the fields show the average download speed recorded in each block for each carrier.The fields also include a composite field (All_) that contains averages of all carriers, masking variation in coverage between individual carriers. "999" indicates no test was conducted for the carrier in that block.Drive-test blocks are generalized information and are suitable when zoomed at various scales. A BLOCK DOES NOT INDICATE SERVICE THROUGHOUT A BLOCK; use the point feature-classes for detailed data and judge accordingly.WIRELESS CHALLENGE BLOCKSWireless Challenge Blocks (Utility_DriveTest_poly_VTMFCIIChallengeBlocks) depicts the status of each block in the submission of the PSD in the FCC Mobility Fund Phase II Challenge process. It shows challenges to mobile wireless service asserted by wireless carriersA value of 0 in the Area_1 field indicates that the challenge was rejected, either because a) the block is already largely eligible, or b) because no tests below 5 Mbps were submitted.DISCLAIMERVCGI and the State of VT make no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data.
The US Consumer Phone file contains phone numbers, mobile and landline, tied to an individual in the Consumer Database. The fields available include the phone number, phone type, mobile carrier, and Do Not Call registry status.
All phone numbers can be processed and cleansed using telecom carrier data. The telecom data, including phone and texting activity, porting instances, carrier scoring, spam, and known fraud activity, comprise a proprietary Phone Quality Level (PQL), which is a data-science derived score to ensure the highest levels of deliverability at a fraction of the cost compared to competitors.
We have developed this file to be tied to our Consumer Demographics Database so additional demographics can be applied as needed. Each record is ranked by confidence and only the highest quality data is used.
Note - all Consumer packages can include necessary PII (address, email, phone, DOB, etc.) for merging, linking, and activation of the data.
BIGDBM Privacy Policy: https://bigdbm.com/privacy.html
Knowing who your consumers are is essential for businesses, marketers, and researchers. This detailed demographic file offers an in-depth look at American consumers, packed with insights about personal details, household information, financial status, and lifestyle choices. Let's take a closer look at the data:
Personal Identifiers and Basic Demographics At the heart of this dataset are the key details that make up a consumer profile:
Unique IDs (PID, HHID) for individuals and households Full names (First, Middle, Last) and suffixes Gender and age Date of birth Complete location details (address, city, state, ZIP) These identifiers are critical for accurate marketing and form the base for deeper analysis.
Geospatial Intelligence This file goes beyond just listing addresses by including rich geospatial data like:
Latitude and longitude Census tract and block details Codes for Metropolitan Statistical Areas (MSA) and Core-Based Statistical Areas (CBSA) County size codes Geocoding accuracy This allows for precise geographic segmentation and localized marketing.
Housing and Property Data The dataset covers a lot of ground when it comes to housing, providing valuable insights for real estate professionals, lenders, and home service providers:
Homeownership status Dwelling type (single-family, multi-family, etc.) Property values (market, assessed, and appraised) Year built and square footage Room count, amenities like fireplaces or pools, and building quality This data is crucial for targeting homeowners with products and services like refinancing or home improvement offers.
Wealth and Financial Data For a deeper dive into consumer wealth, the file includes:
Estimated household income Wealth scores Credit card usage Mortgage info (loan amounts, rates, terms) Home equity estimates and investment property ownership These indicators are invaluable for financial services, luxury brands, and fundraising organizations looking to reach affluent individuals.
Lifestyle and Interests One of the most useful features of the dataset is its extensive lifestyle segmentation:
Hobbies and interests (e.g., gardening, travel, sports) Book preferences, magazine subscriptions Outdoor activities (camping, fishing, hunting) Pet ownership, tech usage, political views, and religious affiliations This data is perfect for crafting personalized marketing campaigns and developing products that align with specific consumer preferences.
Consumer Behavior and Purchase Habits The file also sheds light on how consumers behave and shop:
Online and catalog shopping preferences Gift-giving tendencies, presence of children, vehicle ownership Media consumption (TV, radio, internet) Retailers and e-commerce businesses will find this behavioral data especially useful for tailoring their outreach.
Demographic Clusters and Segmentation Pre-built segments like:
Household, neighborhood, family, and digital clusters Generational and lifestage groups make it easier to quickly target specific demographics, streamlining the process for market analysis and campaign planning.
Ethnicity and Language Preferences In today's multicultural market, knowing your audience's cultural background is key. The file includes:
Ethnicity codes and language preferences Flags for Hispanic/Spanish-speaking households This helps ensure culturally relevant and sensitive communication.
Education and Occupation Data The dataset also tracks education and career info:
Education level and occupation codes Home-based business indicators This data is essential for B2B marketers, recruitment agencies, and education-focused campaigns.
Digital and Social Media Habits With everyone online, digital behavior insights are a must:
Internet, TV, radio, and magazine usage Social media platform engagement (Facebook, Instagram, LinkedIn) Streaming subscriptions (Netflix, Hulu) This data helps marketers, app developers, and social media managers connect with their audience in the digital space.
Political and Charitable Tendencies For political campaigns or non-profits, this dataset offers:
Political affiliations and outlook Charitable donation history Volunteer activities These insights are perfect for cause-related marketing and targeted political outreach.
Neighborhood Characteristics By incorporating census data, the file provides a bigger picture of the consumer's environment:
Population density, racial composition, and age distribution Housing occupancy and ownership rates This offers important context for understanding the demographic landscape.
Predictive Consumer Indexes The dataset includes forward-looking indicators in categories like:
Fashion, automotive, and beauty products Health, home decor, pet products, sports, and travel These predictive insights help businesses anticipate consumer trends and needs.
Contact Information Finally, the file includes ke...
https://www.usa.gov/government-workshttps://www.usa.gov/government-works
This dataset contains Iowa households by presence and type of internet subscriptions for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B28002.
Internet presence includes the following: Total, Yes, and No.
Internet subscription type includes the following: Total; All Subscriptions; Broadband - Cable Fiber Optic/DSL; Satellite Internet Service; Other Service, No Other Type; Broadband - Any Type; No Subscription; Broadband - Cable Fiber Optic/DSL, No Other Type; Cellular Data Plan; No Internet Access; Satellite Internet Service, No Other Type; Dial-up, No Other Type; and Cellular Data Plan, No Other Type.
Various telecommunication datasets such as cellphone towers and service areas, land mobile station locations, AM, FM, and TV communication can be downloaded on an FCC page. Additionally, data files can be individually downloaded from the FCC Universal Licensing System data site. This data resource is intended to guide users toward the authoritative data source and to demonstrate at least one translation of that data into a spatial format.
The metadata for this translated dataset is here:
Antenna Structure Registration: antenna_structure_registration_mn.html
In addition, the Department of Homeland Security's Homeland Infrastructure Foundation - Level Data (HIFLD) program has an "Open Data" site, which includes a nationwide dataset on Cellular Towers derived from the FCC Universal Licensing System Database: https://hifld-geoplatform.opendata.arcgis.com/datasets/cellular-towers
license: apache-2.0 tags: - africa - sustainable-development-goals - world-health-organization - development
Individuals who own a mobile telephone (%)
Dataset Description
This dataset provides country-level data for the indicator "5.b.1 Individuals who own a mobile telephone (%)" across African nations, sourced from the World Health Organization's (WHO) data portal on Sustainable Development Goals (SDGs). The data is presented in a wide format, where each row… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/mobile-phone-ownership-for-african-countries.
Success.ai’s Phone Number Data offers direct access to over 50 million verified phone numbers for professionals worldwide, extracted from our expansive collection of 170 million profiles. This robust dataset includes work emails and key decision-maker profiles, making it an essential resource for companies aiming to enhance their communication strategies and outreach efficiency. Whether you're launching targeted marketing campaigns, setting up sales calls, or conducting market research, our phone number data ensures you're connected to the right professionals at the right time.
Why Choose Success.ai’s Phone Number Data?
Direct Communication: Reach out directly to professionals with verified phone numbers and work emails, ensuring your message gets to the right person without delay. Global Coverage: Our data spans across continents, providing phone numbers for professionals in North America, Europe, APAC, and emerging markets. Continuously Updated: We regularly refresh our dataset to maintain accuracy and relevance, reflecting changes like promotions, company moves, or industry shifts. Comprehensive Data Points:
Verified Phone Numbers: Direct lines and mobile numbers of professionals across various industries. Work Emails: Reliable email addresses to complement phone communications. Professional Profiles: Decision-makers’ profiles including job titles, company details, and industry information. Flexible Delivery and Integration: Success.ai offers this dataset in various formats suitable for seamless integration into your CRM or sales platform. Whether you prefer API access for real-time data retrieval or static files for periodic updates, we tailor the delivery to meet your operational needs.
Competitive Pricing with Best Price Guarantee: We provide this essential data at the most competitive prices in the industry, ensuring you receive the best value for your investment. Our best price guarantee means you can trust that you are getting the highest quality data at the lowest possible cost.
Targeted Applications for Phone Number Data:
Sales and Telemarketing: Enhance your telemarketing campaigns by reaching out directly to potential customers, bypassing gatekeepers. Market Research: Conduct surveys and research directly with industry professionals to gather insights that can shape your business strategy. Event Promotion: Invite prospects to webinars, conferences, and seminars directly through personal calls or SMS. Customer Support: Improve customer service by integrating accurate contact information into your support systems. Quality Assurance and Compliance:
Data Accuracy: Our data is verified for accuracy to ensure over 99% deliverability rates. Compliance: Fully compliant with GDPR and other international data protection regulations, allowing you to use the data with confidence globally. Customization and Support:
Tailored Data Solutions: Customize the data according to geographic, industry-specific, or job role filters to match your unique business needs. Dedicated Support: Our team is on hand to assist with data integration, usage, and any questions you may have. Start with Success.ai Today: Engage with Success.ai to leverage our Phone Number Data and connect with global professionals effectively. Schedule a consultation or request a sample through our dedicated client portal and begin transforming your outreach and communication strategies today.
Remember, with Success.ai, you don’t just buy data; you invest in a partnership that grows with your business needs, backed by our commitment to quality and affordability.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Liveness Detection Replay Dataset (3K+ Attacks, 1.5K People)
Liveness detection dataset of Replay attacks performed on Mobile devices. This dataset consists of 1,500 individuals who provided selfies, followed by 3,000 replay display attacks executed across 15 different mobile devices. These attacks are captured from a diverse range of devices, spanning low, medium, and high-end mobile phones, providing extensive variation in screen types, lighting, and environmental conditions… See the full description on the dataset page: https://huggingface.co/datasets/AxonData/Replay_attack_mobile.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 10 cities in the Mobile County, AL by American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Mobile by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Mobile. The dataset can be utilized to understand the population distribution of Mobile by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Mobile. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Mobile.
Key observations
Largest age group (population): Male # 20-24 years (7,389) | Female # 30-34 years (7,694). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Mobile Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 10 cities in the Mobile County, AL by Non-Hispanic Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
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The number of smartphone users in the United States was forecast to continuously increase between 2024 and 2029 by in total 17.4 million users (+5.61 percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach 327.54 million users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like Mexico and Canada.