100+ datasets found
  1. d

    Phone Number Data | APAC | 100M+ B2B Mobile Phone Numbers | 95%+ Accuracy

    • datarade.ai
    .json, .csv
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    Forager.ai, Phone Number Data | APAC | 100M+ B2B Mobile Phone Numbers | 95%+ Accuracy [Dataset]. https://datarade.ai/data-products/apac-b2b-mobile-data-90m-95-accuracy-api-bi-weekly-up-forager-ai
    Explore at:
    .json, .csvAvailable download formats
    Dataset provided by
    Forager.ai
    Area covered
    Ghana, Bhutan, Uruguay, San Marino, Belarus, Libya, El Salvador, Bahamas, Burkina Faso, Georgia
    Description

    Global B2B Mobile Phone Number Database | 100M+ Verified Contacts | 95% Accuracy Forager.ai provides the world’s most reliable mobile phone number data for businesses that refuse to compromise on quality. With 100 million+ professionally verified mobile numbers refreshed every 3 weeks, our database ensures 95% accuracy – so your teams never waste time on dead-end leads.

    Why Our Data Wins ✅ Accuracy You Can Trust 95% of mobile numbers are verified against live carrier records and tied to current job roles. Say goodbye to “disconnected number” voicemails.

    ✅ Depth Beyond Digits Each contact includes 150+ data points:

    Direct mobile numbers

    Current job title, company, and department

    Full career history + education background

    Location data + LinkedIn profiles

    Company size, industry, and revenue

    ✅ Freshness Guaranteed Bi-weekly updates combat job-hopping and role changes – critical for sales teams targeting decision-makers.

    ✅ Ethically Sourced & Compliant First-party collected data with full GDPR/CCPA compliance.

    Who Uses This Data?

    Sales Teams: Cold-call C-suite prospects with verified mobile numbers.

    Marketers: Run hyper-personalized SMS/WhatsApp campaigns.

    Recruiters: Source passive candidates with up-to-date contact intel.

    Data Vendors: License premium datasets to enhance your product.

    Tech Platforms: Power your SaaS tools via API with enterprise-grade B2B data.

    Flexible Delivery, Instant Results

    API (REST): Real-time integration for CRMs, dialers, or marketing stacks

    CSV/JSON: Campaign-ready files.

    PostgreSQL: Custom databases for large-scale enrichment

    Compliance: Full audit trails + opt-out management

    Why Forager.ai? → Proven ROI: Clients see 62% higher connect rates vs. industry averages (request case studies). → No Guesswork: Test-drive free samples before committing. → Scalable Pricing: Pay per record, license datasets, or get unlimited API access.

    B2B Mobile Phone Data | Verified Contact Database | Sales Prospecting Lists | CRM Enrichment | Recruitment Phone Numbers | Marketing Automation | Phone Number Datasets | GDPR-Compliant Leads | Direct Dial Contacts | Decision-Maker Data

    Need Proof? Contact us to see why Fortune 500 companies and startups alike trust Forager.ai for mission-critical outreach.

  2. b

    Phone Number Data | USA Coverage | 765 Mil+ Numbers

    • data.bigdbm.com
    + more versions
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    BIGDBM, Phone Number Data | USA Coverage | 765 Mil+ Numbers [Dataset]. https://data.bigdbm.com/products/bigdbm-us-consumer-phone-package-bigdbm
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    Dataset authored and provided by
    BIGDBM
    Area covered
    United States
    Description

    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 cleansed using telecom carrier data.

  3. d

    Alesco Phone ID Database - Phone Data with over 860 Million Phone Number...

    • datarade.ai
    .csv, .xls, .txt
    Updated Jul 5, 2018
    + more versions
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    Alesco Data (2018). Alesco Phone ID Database - Phone Data with over 860 Million Phone Number with Carrier Name, covers 94% of the US population - available for licensing! [Dataset]. https://datarade.ai/data-products/alesco-phone-id-database-the-industry-s-largest-and-most-ac-alesco-data
    Explore at:
    .csv, .xls, .txtAvailable download formats
    Dataset updated
    Jul 5, 2018
    Dataset authored and provided by
    Alesco Data
    Area covered
    United States
    Description

    The Alesco Phone ID Database data ties together a consumer's true identity, and with linkage to the Alesco Power Identity Graph, we are perfectly positioned to help customers solve today's most challenging marketing, analytics, and identity resolution problems.

    Our proprietary Phone ID database combines public and private sources and validates phone numbers against current and historical data 24 hours a day, 365 days a year.

    With over 650 million unique phone numbers, device and service information, our one-of-a-kind solutions are now available for your marketing and identity resolution challenges in both B2C and B2B applications!

    • Alesco Phone ID provides more than 860 million phone numbers monthly linked to a consumer or business name and includes landline, mobile phone number, VoIP, private and business phone numbers — all permissibly obtained and privacy-compliant and linked to other Alesco data sets

    • How we do it: Alesco Phone ID is multi-sourced with daily information and delivered monthly or quarterly to clients. Our proprietary machine learning and advanced analytics processes ensure quality levels far above industry standards. Alesco processes over 100 million phone signals per day, compiling, normalizing, and standardizing phone information from 37 input sources.

    • Accuracy: Each of Alesco’s phone data sources are vetted to ensure they are authoritative, giving you confidence in the accuracy of the information. Every record is validated, verified and processed to ensure the widest, most reliable coverage combined with stunning precision.

    Ease of use: Alesco’s Phone ID Database is available as an on-premise phone database license, giving you full control to host and access this powerful resource on-site. Ongoing updates are provided on a monthly basis ensure your data is up to date.

  4. d

    B2B Leads Database | 500M+ B2B Contact Profiles | 100M+ B2B Mobile Numbers |...

    • datarade.ai
    .csv, .xls
    Updated Feb 24, 2022
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    Lead for Business (2025). B2B Leads Database | 500M+ B2B Contact Profiles | 100M+ B2B Mobile Numbers | 100% Real-Time Verified Contact Data [Dataset]. https://datarade.ai/data-products/b2b-leads-database-b2b-contact-database-b2b-contact-direc-lead-for-business
    Explore at:
    .csv, .xlsAvailable download formats
    Dataset updated
    Feb 24, 2022
    Dataset authored and provided by
    Lead for Business
    Area covered
    Martinique, Palestine, Finland, Northern Mariana Islands, Jersey, South Sudan, Armenia, Isle of Man, Mozambique, Trinidad and Tobago
    Description

    • 500M B2B Contacts • 35M Companies • 20+ Data Points to Filter Your Leads • 100M+ Contact Direct Dial and Mobile Number • Lifetime Support Until You 100% Satisfied

    We are the Best b2b database providers for high-performance sales teams. If you get a fake by any chance, you have nothing to do with them. Nothing is more frustrating than receiving useless data for which you have paid money.

    Every 15 days, our devoted team updates our b2b leads database. In addition, we are always available to assist our clients with whatever data they are working with in order to ensure that our service meets their needs. We keep an eye on our b2b contact database to keep you informed and provide any assistance you require.

    With our simple-to-use system and up-to-date B2B contact list, we hope to make your job easier. You’ll be able to filter your data at Lfbbd based on the industry you work in. For example, you can choose from real estate companies or just simply tap into the healthcare business. Our database is updated on a regular basis, and you will receive contact information as soon as possible.

    Use our information to quickly locate new business clients, competitors, and suppliers. We’ve got your back, no matter what precise requirements you have.

    We have over 500 million business-to-business contacts that you may segment based on your marketing and commercial goals. We don’t stop there; we’re always gathering leads from the right tool so you can reach out to a big database of your clients without worrying about email constraints.

    Thanks to our database, you may create your own campaign and send as many email or automated messages as you want. We collect the most viable b2b database to help you go a long way, as we seek to increase your business and enhance your sales.

    The majority of our clients choose us since we have competitive costs when compared to others. In this digital era, marketing is more advanced, and customers are less willing to pay more for a service that produces poor results.

    That’s why we’ve devised the most effective b2b database strategy for your company. You can also tailor your database and pricing to meet your specific business requirements.

    • Connect directly with the right decision-makers, using the most accurate database of emails and direct dials. Build a clean prospecting list that you can plug into your sales tools and generate new leads from, right away • Over 500 million business contacts worldwide. • You could filter your targeted leads by 20+ criteria including job title, industry, location, Revenue, Technology, and more. • Find the email addresses of the professionals you want to contact one by one or in bulk.

  5. i

    Global Financial Inclusion (Global Findex) Database 2021 - Pakistan

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Dec 16, 2022
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    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Pakistan [Dataset]. https://datacatalog.ihsn.org/catalog/10490
    Explore at:
    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Pakistan
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    Did not include Azad Jammu and Kashmir (AJK) and Gilgit-Baltistan. The excluded area represents approximately 5 percent of the total population. Gender-matched sampling was used during the final stage of selection.

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Pakistan is 1002.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  6. Real-Time Verified Search Fund Data | 200mm US Records | Personal Emails &...

    • datarade.ai
    .csv, .xls
    Updated Jul 23, 2024
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    Wiza (2024). Real-Time Verified Search Fund Data | 200mm US Records | Personal Emails & 100mm Mobile Phone Numbers | Live-Sourced Linkedin Data [Dataset]. https://datarade.ai/data-products/wiza-real-time-verified-search-fund-data-200mm-us-records-wiza
    Explore at:
    .csv, .xlsAvailable download formats
    Dataset updated
    Jul 23, 2024
    Dataset provided by
    Wiza, Inc
    Authors
    Wiza
    Area covered
    United States
    Description

    Stop relying on outdated and inaccurate databases and let Wiza be your source of truth for all deal sourcing and founder / CEO outreach.

    Why we're different: The search fund market is dynamic and competitive - Wiza is not a static financial database that gets refreshed on occasion. Every datapoint is sourced and verified the moment that you receive the information. We verify deliverability of every single email ahead of providing the data, and we ensure that each person in your dataset has 100% job title and company accuracy by leveraging Linkedin Data sourced through their live Linkedin profile.

    Key Features:

    Comprehensive Data Coverage: Stop contacting the same people as everyone else. Wiza's search fund Data is sourced live, not stored in a limited database. When you tell us the type of company or person you would like to contact, we leverage Linkedin Data (the largest, most accurate database in the world) to find everyone who matches your ICP, and then we source the contact data and company data in real-time.

    High-Quality, Accurate Data: Wiza ensures accuracy of all datapoints by taking a few key steps that other data providers fail to take: (1) Every email is SMTP verified ahead of delivery, ensuring they will not bounce (2) Every person's Linkedin profile is checked live to ensure we have 100% job title, company, location, etc. accuracy, ahead of providing any data (3) Phone numbers are constantly being verified with AI to ensure accuracy

    Linkedin Data: Wiza is able to provide Linkedin Data points, sourced live from each person's Linkedin profile, including Subtitle, Bio, Job Title, Job Description, Skills, Languages, Certifications, Work History, Education, Open to Work, Premium Status, and more!

    Personal Data: Wiza has access to industry leading volumes of B2C Contact Data, meaning you can find gmail/yahoo/hotmail email addresses, and mobile phone number data to contact your potential partners.

  7. Number of mobile search users in China 2011-2020

    • statista.com
    Updated Feb 23, 2023
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    Statista (2023). Number of mobile search users in China 2011-2020 [Dataset]. https://www.statista.com/statistics/253503/number-of-mobile-search-users-in-china/
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    Dataset updated
    Feb 23, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    This statistic shows the number of mobile search users in China from 2011 to 2020. By the end of 2020, over 768 million people in China used mobile phones to search the web, representing 78 percent of the total mobile users.

  8. R

    Reverse Phone Number Lookup Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Mar 15, 2025
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    Archive Market Research (2025). Reverse Phone Number Lookup Report [Dataset]. https://www.archivemarketresearch.com/reports/reverse-phone-number-lookup-59374
    Explore at:
    doc, pdf, pptAvailable download formats
    Dataset updated
    Mar 15, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The reverse phone number lookup market is experiencing robust growth, driven by increasing concerns over online privacy and safety, the rise of scams and harassment via unknown numbers, and the need for efficient background checks. The market's size in 2025 is estimated at $1.5 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant growth is fueled by several factors. The increasing adoption of smartphones and readily available mobile apps offering this service contributes significantly. Furthermore, businesses across various sectors, from law enforcement and debt collection agencies to background check companies and private investigators, rely on reverse phone lookup services for verifying identities and locating individuals. This widespread adoption across both personal and enterprise applications boosts market expansion. The market segmentation, comprised of cloud-based and on-premise solutions, alongside personal and enterprise applications, indicates diverse user needs and preferences, further fueling the market's growth potential. However, market growth is not without challenges. Data privacy concerns and regulations, such as GDPR and CCPA, pose significant restraints. The potential for inaccuracies in the data provided by some services and the emergence of sophisticated caller ID spoofing techniques also present challenges. Despite these restraints, the overall trend indicates a continuously expanding market, with ongoing technological advancements likely to enhance accuracy and user experience, driving further growth in the coming years. The projected market size in 2033 is estimated to surpass $5 billion, emphasizing the substantial growth potential and market attractiveness. Continued innovation and adaptation to evolving regulatory landscapes will be crucial for sustained success in this dynamic sector.

  9. d

    815 Million Global Contact Data - B2B / Email / Mobile Phone / LinkedIn URL...

    • datarade.ai
    .json, .csv
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    RampedUp Global Data Solutions, 815 Million Global Contact Data - B2B / Email / Mobile Phone / LinkedIn URL - RampedUp [Dataset]. https://datarade.ai/data-products/global-contact-data-personal-and-professional-840-million-rampedup-global-data-solutions
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    .json, .csvAvailable download formats
    Dataset authored and provided by
    RampedUp Global Data Solutions
    Area covered
    Pakistan, Haiti, Greece, Sint Eustatius and Saba, Bolivia (Plurinational State of), Grenada, Chad, Uganda, United States Minor Outlying Islands, Ireland
    Description

    Sign Up for a free trial: https://rampedup.io/sign-up-%2F-log-in - 7 Days and 50 Credits to test our quality and accuracy.

    These are the fields available within the RampedUp Global dataset.

    CONTACT DATA: Personal Email Address - We manage over 115 million personal email addresses Professional Email - We manage over 200 million professional email addresses Home Address - We manage over 20 million home addresses Mobile Phones - 65 million direct lines to decision makers Social Profiles - Individual Facebook, Twitter, and LinkedIn Local Address - We manage 65M locations for local office mailers, event-based marketing or face-to-face sales calls.

    JOB DATA: Job Title - Standardized titles for ease of use and selection Company Name - The Contact's current employer Job Function - The Company Department associated with the job role Title Level - The Level in the Company associated with the job role Job Start Date - Identify people new to their role as a potential buyer

    EMPLOYER DATA: Websites - Company Website, Root Domain, or Full Domain Addresses - Standardized Address, City, Region, Postal Code, and Country Phone - E164 phone with country code Social Profiles - LinkedIn, CrunchBase, Facebook, and Twitter

    FIRMOGRAPHIC DATA: Industry - 420 classifications for categorizing the company’s main field of business Sector - 20 classifications for categorizing company industries 4 Digit SIC Code - 239 classifications and their definitions 6 Digit NAICS - 452 classifications and their definitions Revenue - Estimated revenue and bands from 1M to over 1B Employee Size - Exact employee count and bands Email Open Scores - Aggregated data at the domain level showing relationships between email opens and corporate domains. IP Address -Company level IP Addresses associated to Domains from a DNS lookup

    CONSUMER DATA: Education - Alma Mater, Degree, Graduation Date Skills - Accumulated Skills associated with work experience
    Interests - Known interests of contact Connections - Number of social connections. Followers - Number of social followers

    Download our data dictionary: https://rampedup.io/our-data

  10. P

    Poland Mobile Phone: No of SMS

    • ceicdata.com
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    CEICdata.com, Poland Mobile Phone: No of SMS [Dataset]. https://www.ceicdata.com/en/poland/mobile-phone-statistics/mobile-phone-no-of-sms
    Explore at:
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    Poland
    Variables measured
    Phone Statistics
    Description

    Poland Mobile Phone: Number of SMS data was reported at 50,496.000 Unit mn in 2016. This records a decrease from the previous number of 52,400.000 Unit mn for 2015. Poland Mobile Phone: Number of SMS data is updated yearly, averaging 48,596.500 Unit mn from Dec 2003 (Median) to 2016, with 14 observations. The data reached an all-time high of 52,712.000 Unit mn in 2012 and a record low of 5,293.700 Unit mn in 2003. Poland Mobile Phone: Number of SMS data remains active status in CEIC and is reported by Central Statistical Office. The data is categorized under Global Database’s Poland – Table PL.TB001: Mobile Phone Statistics.

  11. Bahrain Number of Subscriber Mobile

    • ceicdata.com
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    CEICdata.com, Bahrain Number of Subscriber Mobile [Dataset]. https://www.ceicdata.com/en/indicator/bahrain/number-of-subscriber-mobile
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    Bahrain
    Description

    Key information about Bahrain Number of Subscriber Mobile

    • Bahrain Number of Subscriber Mobile was reported at 2,420,000.000 Person in Dec 2023
    • This records an increase from the previous number of 2,140,000.000 Person for Dec 2022
    • Bahrain Number of Subscriber Mobile data is updated yearly, averaging 75,303.000 Person from Dec 1960 to 2023, with 52 observations
    • The data reached an all-time high of 2,990,000.000 Person in 2016 and a record low of 0.000 Person in 1985
    • Bahrain Number of Subscriber Mobile data remains active status in CEIC and is reported by World Bank
    • The data is categorized under World Trend Plus’s Association: Telecommunication Sector – Table BH.World Bank.WDI: Telecommunication

    Mobile cellular telephone subscriptions are subscriptions to a public mobile telephone service that provide access to the PSTN using cellular technology. The indicator includes (and is split into) the number of postpaid subscriptions, and the number of active prepaid accounts (i.e. that have been used during the last three months). The indicator applies to all mobile cellular subscriptions that offer voice communications. It excludes subscriptions via data cards or USB modems, subscriptions to public mobile data services, private trunked mobile radio, telepoint, radio paging and telemetry services.;International Telecommunication Union (ITU) World Telecommunication/ICT Indicators Database;Sum;Please cite the International Telecommunication Union for third-party use of these data.

  12. w

    Global Financial Inclusion (Global Findex) Database 2021 - Sweden

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Dec 16, 2022
    + more versions
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    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Sweden [Dataset]. https://microdata.worldbank.org/index.php/catalog/4711
    Explore at:
    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Sweden
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Sweden is 1006.

    Mode of data collection

    Landline and mobile telephone

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  13. Global Phone Number buyers list and Global importers directory of Phone...

    • volza.com
    csv
    Updated Jun 19, 2025
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    Volza FZ LLC (2025). Global Phone Number buyers list and Global importers directory of Phone Number [Dataset]. https://www.volza.com/p/phone-number/buyers/buyers-in-india/
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 19, 2025
    Dataset provided by
    Volza
    Authors
    Volza FZ LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Count of exporters, Count of importers, Count of shipments, Sum of import value, 2014-01-01/2021-09-30
    Description

    16 Active Global Phone Number buyers list and Global Phone Number importers directory compiled from actual Global import shipments of Phone Number.

  14. d

    Consumer Marketing Data, B2C Contact Data - Contact Append - API, USA, CCPA...

    • datarade.ai
    .json, .csv
    Updated Mar 11, 2023
    + more versions
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    Versium (2023). Consumer Marketing Data, B2C Contact Data - Contact Append - API, USA, CCPA Compliant [Dataset]. https://datarade.ai/data-products/versium-reach-b2c-consumer-emails-api-usa-gdpr-and-ccpa-versium
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Mar 11, 2023
    Dataset authored and provided by
    Versium
    Area covered
    United States
    Description

    With Versium REACH's Contact Append or Contact Append Plus you can add consumer contact data, including multiple phone numbers or mobile-only to your list of customers or prospects. With Versium REACH you are connected to our proprietary database of over 300+ million consumers, 1 Billion emails, and over 150 million households in the United States. Through either our API or platform you can have contact data appended to your records with any of the following supplied values; Email Address Phone Postal Address, City, State, ZIP First Name, Last Name, City, State First Name, Last Name, ZIP

  15. R

    Russia No of Mobile Phone Subscribers per 1000 Persons: CF: Bryansk Region

    • ceicdata.com
    Updated Apr 12, 2019
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    CEICdata.com (2019). Russia No of Mobile Phone Subscribers per 1000 Persons: CF: Bryansk Region [Dataset]. https://www.ceicdata.com/en/russia/number-of-mobile-phone-subscribers-per-1000-persons-by-region
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    Dataset updated
    Apr 12, 2019
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    Russia
    Variables measured
    Phone Statistics
    Description

    No of Mobile Phone Subscribers per 1000 Persons: CF: Bryansk Region data was reported at 1,670.900 Unit in 2016. This records a decrease from the previous number of 1,742.600 Unit for 2015. No of Mobile Phone Subscribers per 1000 Persons: CF: Bryansk Region data is updated yearly, averaging 1,108.200 Unit from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 1,742.600 Unit in 2015 and a record low of 2.700 Unit in 2000. No of Mobile Phone Subscribers per 1000 Persons: CF: Bryansk Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Transport and Telecommunications Sector – Table RU.TG009: Number of Mobile Phone Subscribers: per 1000 Persons: by Region.

  16. w

    Global Financial Inclusion (Global Findex) Database 2021 - Venezuela, RB

    • microdata.worldbank.org
    • datacatalog.ihsn.org
    • +1more
    Updated Dec 16, 2022
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    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Venezuela, RB [Dataset]. https://microdata.worldbank.org/index.php/catalog/4727
    Explore at:
    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Venezuela
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Venezuela, RB is 1000.

    Mode of data collection

    Landline and mobile telephone

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  17. w

    Global Financial Inclusion (Global Findex) Database 2021 - Chad

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Jun 8, 2023
    + more versions
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    Development Research Group, Finance and Private Sector Development Unit (2023). Global Financial Inclusion (Global Findex) Database 2021 - Chad [Dataset]. https://microdata.worldbank.org/index.php/catalog/5849
    Explore at:
    Dataset updated
    Jun 8, 2023
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2022
    Area covered
    Chad
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world’s most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of almost 145,000 people in 139 economies, representing 97 percent of the world’s population. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    Because of security issues and difficult terrain, seven regions are excluded from the sampling: Lac, Ouaddaï, Wadi Fira, Bourkou, Ennedi, Tibesti, Salamat. In addition, the North Kanem and Bahr El Gazal North districts were excluded due to accessibility issues. Quartiers/villages with less than 50 inhabitants are also excluded from sampling. The excluded areas represent 23% of the population.

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19–related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Additionally, phone surveys were not a viable option in 16 economies in 2021, which were then surveyed in 2022.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Chad is 1000.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  18. Global Mobile Phone buyers list and Global importers directory of Mobile...

    • volza.com
    csv
    Updated Jun 27, 2025
    + more versions
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    Volza FZ LLC (2025). Global Mobile Phone buyers list and Global importers directory of Mobile Phone [Dataset]. https://www.volza.com/p/mobile-phone/buyers/buyers-in-united-states/coo-india/
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 27, 2025
    Dataset provided by
    Volza
    Authors
    Volza FZ LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Count of exporters, Count of importers, Count of shipments, Sum of import value, 2014-01-01/2021-09-30
    Description

    292 Active Global Mobile Phone buyers list and Global Mobile Phone importers directory compiled from actual Global import shipments of Mobile Phone.

  19. w

    Global Financial Inclusion (Global Findex) Database 2021 - Burkina Faso

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Dec 16, 2022
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    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Burkina Faso [Dataset]. https://microdata.worldbank.org/index.php/catalog/4622
    Explore at:
    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Burkina Faso
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    Some communities in the East and Sahel regions were excluded for security reasons. The areas represent 4 percent of the total population.

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Burkina Faso is 1000.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  20. Number of individuals by mobile phone usage purposes and activity status,...

    • data.europa.eu
    html, unknown
    Updated May 13, 2022
    + more versions
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    VLADA REPUBLIKE SLOVENIJE STATISTIČNI URAD REPUBLIKE SLOVENIJE (2022). Number of individuals by mobile phone usage purposes and activity status, Slovenia, annually [Dataset]. https://data.europa.eu/data/datasets/surs2979515s?locale=en
    Explore at:
    html, unknownAvailable download formats
    Dataset updated
    May 13, 2022
    Dataset provided by
    Government of Slovenia
    Authors
    VLADA REPUBLIKE SLOVENIJE STATISTIČNI URAD REPUBLIKE SLOVENIJE
    Area covered
    Slovenia
    Description

    This database automatically includes metadata, the source of which is the GOVERNMENT OF THE REPUBLIC OF SLOVENIA STATISTICAL USE OF THE REPUBLIC OF SLOVENIA and corresponding to the source database entitled “Number of individuals by mobile phone usage purposes and activity status, Slovenia, annually”.

    Actual data are available in Px-Axis format (.px). With additional links, you can access the source portal page for viewing and selecting data, as well as the PX-Win program, which can be downloaded free of charge. Both allow you to select data for display, change the format of the printout, and store it in different formats, as well as view and print tables of unlimited size, as well as some basic statistical analyses and graphics.

Share
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Forager.ai, Phone Number Data | APAC | 100M+ B2B Mobile Phone Numbers | 95%+ Accuracy [Dataset]. https://datarade.ai/data-products/apac-b2b-mobile-data-90m-95-accuracy-api-bi-weekly-up-forager-ai

Phone Number Data | APAC | 100M+ B2B Mobile Phone Numbers | 95%+ Accuracy

Explore at:
.json, .csvAvailable download formats
Dataset provided by
Forager.ai
Area covered
Ghana, Bhutan, Uruguay, San Marino, Belarus, Libya, El Salvador, Bahamas, Burkina Faso, Georgia
Description

Global B2B Mobile Phone Number Database | 100M+ Verified Contacts | 95% Accuracy Forager.ai provides the world’s most reliable mobile phone number data for businesses that refuse to compromise on quality. With 100 million+ professionally verified mobile numbers refreshed every 3 weeks, our database ensures 95% accuracy – so your teams never waste time on dead-end leads.

Why Our Data Wins ✅ Accuracy You Can Trust 95% of mobile numbers are verified against live carrier records and tied to current job roles. Say goodbye to “disconnected number” voicemails.

✅ Depth Beyond Digits Each contact includes 150+ data points:

Direct mobile numbers

Current job title, company, and department

Full career history + education background

Location data + LinkedIn profiles

Company size, industry, and revenue

✅ Freshness Guaranteed Bi-weekly updates combat job-hopping and role changes – critical for sales teams targeting decision-makers.

✅ Ethically Sourced & Compliant First-party collected data with full GDPR/CCPA compliance.

Who Uses This Data?

Sales Teams: Cold-call C-suite prospects with verified mobile numbers.

Marketers: Run hyper-personalized SMS/WhatsApp campaigns.

Recruiters: Source passive candidates with up-to-date contact intel.

Data Vendors: License premium datasets to enhance your product.

Tech Platforms: Power your SaaS tools via API with enterprise-grade B2B data.

Flexible Delivery, Instant Results

API (REST): Real-time integration for CRMs, dialers, or marketing stacks

CSV/JSON: Campaign-ready files.

PostgreSQL: Custom databases for large-scale enrichment

Compliance: Full audit trails + opt-out management

Why Forager.ai? → Proven ROI: Clients see 62% higher connect rates vs. industry averages (request case studies). → No Guesswork: Test-drive free samples before committing. → Scalable Pricing: Pay per record, license datasets, or get unlimited API access.

B2B Mobile Phone Data | Verified Contact Database | Sales Prospecting Lists | CRM Enrichment | Recruitment Phone Numbers | Marketing Automation | Phone Number Datasets | GDPR-Compliant Leads | Direct Dial Contacts | Decision-Maker Data

Need Proof? Contact us to see why Fortune 500 companies and startups alike trust Forager.ai for mission-critical outreach.

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