Global Telemarketing Data | 95% Phone & Email Accuracy | 270M+ Verified Contacts Forager.ai redefines telemarketing success with the world’s most actionable contact database. We combine 100M+ mobile numbers and 170M+ verified emails with deep company insights – all updated every 14 days to maintain 95% accuracy rates that outperform legacy providers.

Why Telemarketing Teams Choose Us ✅ Dual-Channel Verified Every record confirms both working mobile numbers AND valid Personal email or Work email addresses – critical for multi-touch campaigns.

✅ Decision-Maker Intel 41% of contacts hold budget authority (Director to C-Suite) with:

Direct mobile numbers

Verified corporate emails

Department hierarchy mapping

Purchase intent signals

✅ Freshness Engine Bi-weekly verification sweeps catch: ✖ Job changers (23% of database monthly) ✖ Company restructuring ✖ Number/email deactivations

✅ Compliance Built-In Automated opt-out management + full GDPR/CCPA documentation.

Your Complete Telemarketing Toolkit Core Data Points: ✔ Direct dial mobile/work numbers ✔ Verified corporate email addresses ✔ Job title & decision-making authority ✔ Company size/revenue/tech stack ✔ Department structure & team size ✔ Location data (HQ/local offices) ✔ LinkedIn/Social media validation

Proven Use Cases • Cold Calling 2.0: Target CROs with mobile numbers + know their tech stack before dialing • Email-to-Call Sequencing: Match verified emails to mobile numbers for 360° outreach • List Hygiene: Clean existing CRM contacts against our live database • Market Expansion: Target specific employee counts (50-200 person companies) • Event Follow-Ups: Re-engage webinar/trade show leads with updated contact info

Enterprise-Grade Delivery

Real-Time API: Connect to Five9/Aircall/Salesforce

CRM-Ready Files: CSV with custom fields

Compliance Hub: Automated opt-out tracking

PostgreSQL Sync/ JSON files: 2-3 weeks updates for large datasets

Why We Outperform Competitors → 62% Connect Rate: Actual client result vs. industry 38% average → 3:1 ROI Guarantee: We’ll prove value or extend your license → Free Audit: Upload 10K contacts – we’ll show % salvageable

Need Convincing? Free API test account → Experience our accuracy firsthand. See why 89% of trial users convert to paid plans.

Telemarketing Data | Verified Contact Database | Cold Calling Lists | Phone & Email Data | Decision-Maker Contacts | CRM Enrichment | GDPR-Compliant Leads | B2B Contact Data | Sales Prospecting | ABM Targeting

This dataset on mobile phone coverage is no longer current. It was published by Ofcom in 2013. More recent mobile phone coverage data is available in our 2017 Connected Nations report (formerly called Infrastructure Report), both on www.data.gov.uk and on the Ofcom website at https://www.ofcom.org.uk/research-and-data/multi-sector-research/infrastructure-research/connected-nations-2017

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

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.

Northern Territory remote areas with mobile network coverage. Data includes coverage in Aboriginal communities, remote villages, tourism locations and highway locations. Coverage is by macro cell tower, small cell installation or proximity to macro cell coverage. Cities and towns excluded from dataset Darwin, Palmerston, Tennant Creek, Katherine, Alice Springs, Nhulunbuy and Jabiru.

The Consumer Mobile Device file contains MAIDs connected to an individual in the Consumer Database. The fields available include latitude and longitude, device type, hashed emails, and plain-text emails.

This is updated monthly from a database containing billions of MAID<>email linkages.

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

Mobile phone expansion, especially in cities like Hamm, is crucial for digital infrastructure and social and economic growth. A high-performance mobile network is indispensable in a networked world where digital communication and data transmission are becoming increasingly important. Hamm benefits enormously from a well-developed mobile network that enables fast telephony and Internet access via mobile devices. This is particularly important for companies that rely on smooth communication and for citizens in everyday life and at work. With the increasing demand for mobile services and new technologies such as the Internet of Things and 5G, comprehensive expansion is essential to meet demand and maintain Germany's competitiveness as a leading location for innovation and technology. The dataset contains information about 4G and 5G mobile coverage in the city of Hamm.

A large body of research has demonstrated that land use and urban form can have a significant effect on transportation outcomes. People who live and/or work in compact neighborhoods with a walkable street grid and easy access to public transit, jobs, stores, and services are more likely to have several transportation options to meet their everyday needs. As a result, they can choose to drive less, which reduces their emissions of greenhouse gases and other pollutants compared to people who live and work in places that are not location efficient. Walking, biking, and taking public transit can also save people money and improve their health by encouraging physical activity. The Smart Location Database summarizes several demographic, employment, and built environment variables for every census block group (CBG) in the United States. The database includes indicators of the commonly cited “D” variables shown in the transportation research literature to be related to travel behavior. The Ds include residential and employment density, land use diversity, design of the built environment, access to destinations, and distance to transit. SLD variables can be used as inputs to travel demand models, baseline data for scenario planning studies, and combined into composite indicators characterizing the relative location efficiency of CBG within U.S. metropolitan regions. This update features the most recent geographic boundaries (2019 Census Block Groups) and new and expanded sources of data used to calculate variables. Entirely new variables have been added and the methods used to calculate some of the SLD variables have changed. More information on the National Walkability index: https://www.epa.gov/smartgrowth/smart-location-mapping More information on the Smart Location Calculator: https://www.slc.gsa.gov/slc/

Database of the calculated outdoor mobile coverage predictions for each mobile operator and for each mobile technology type.

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.

Mobile phone location data is a newly emerging data source of great potential to support human mobility research. However, recent studies have indicated that many users can be easily re-identified based on their unique activity patterns. Privacy protection procedures will usually change the original data and cause a loss of data utility for analysis purposes. Therefore, the need for detailed data for activity analysis while avoiding potential privacy risks presents a challenge. The aim of this study is to reveal the re-identification risks from a Chinese city’s mobile users and to examine the quantitative relationship between re-identification risk and data utility for an aggregated mobility analysis. The first step is to apply two reported attack models, the top N locations and the spatio-temporal points, to evaluate the re-identification risks in Shenzhen City, a metropolis in China. A spatial generalization approach to protecting privacy is then proposed and implemented, and spatially aggregated analysis is used to assess the loss of data utility after privacy protection. The results demonstrate that the re-identification risks in Shenzhen City are clearly different from those in regions reported in Western countries, which prove the spatial heterogeneity of re-identification risks in mobile phone location data. A uniform mathematical relationship has also been found between re-identification risk (x) and data (y) utility for both attack models: y = -axb+c, (a, b, c>0; 0

Corrosion is a serious problem that has enormous costs for the nation (4.2% GDP in 2007) and worldwide. Kennedy Space Center is located in one of the most naturally corrosive areas in the world. Acidic exhaust from the solid rocket boosters aggravates these natural conditions. New space vehicles are likely to use the same solid rocket fuel used to launch the Space Shuttle. Launching facilities and ground support equipment will continue to need corrosion protection.

Current research is focused on encapsulating environmentally friendly corrosion inhibitors and incorporating them into commercially available coatings to test their effectiveness. Accelerated corrosion tests have shown that corrosion-activated release microcapsules and particles can be used as inhibitor delivery systems to improve the corrosion protection of several commercially available coatings. This work is being conducted in collaboration with several industry partners who are interested in the NASA-developed smart coating technology.

This is a MD iMAP hosted service layer. Find more information at http://imap.maryland.gov. Polygon layer displays areas where mobile wireless broadband service is available. Last Updated: 10/2014 Feature Service Layer Link: https://mdgeodata.md.gov/imap/rest/services/UtilityTelecom/MD_BroadbandServiceAreas/MapServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

Percentage of Internet users who have taken actions to protect a laptop, computer or mobile device from cyber security incidents, by type of protection.

suburban and rural areas.

Centre for Appropriate Technology (CfAT) mobile phone hotspots are a low tech solution that extends the reach of mobile phone coverage. Hotspots are manufactured in Alice Springs using CfAT's Aboriginal workforce. NTG funded the install of 34 mobile phone hotspots in Central Australia and the Top End.

Abstract: The aim of this study is to gain insights into the attitudes of the population towards big data practices and the factors influencing them. To this end, a nationwide survey (N = 1,331), representative of the population of Germany, addressed the attitudes about selected big data practices exemplified by four scenarios, which may have a direct impact on the personal lifestyle. The scenarios contained price discrimination in retail, credit scoring, differentiations in health insurance, and differentiations in employment. The attitudes about the scenarios were set into relation to demographic characteristics, personal value orientations, knowledge about computers and the internet, and general attitudes about privacy and data protection. Another focus of the study is on the institutional framework of privacy and data protection, because the realization of benefits or risks of big data practices for the population also depends on the knowledge about the rights the institutional framework provided to the population and the actual use of those rights. As results, several challenges for the framework by big data practices were confirmed, in particular for the elements of informed consent with privacy policies, purpose limitation, and the individuals’ rights to request information about the processing of personal data and to have these data corrected or erased. TechnicalRemarks: TYPE OF SURVEY AND METHODS The data set includes responses to a survey conducted by professionally trained interviewers of a social and market research company in the form of computer-aided telephone interviews (CATI) from 2017-02 to 2017-04. The target population was inhabitants of Germany aged 18 years and more, who were randomly selected by using the sampling approaches ADM eASYSAMPLe (based on the Gabler-Häder method) for landline connections and eASYMOBILe for mobile connections. The 1,331 completed questionnaires comprise 44.2 percent mobile and 55.8 percent landline phone respondents. Most questions had options to answer with a 5-point rating scale (Likert-like) anchored with ‘Fully agree’ to ‘Do not agree at all’, or ‘Very uncomfortable’ to ‘Very comfortable’, for instance. Responses by the interviewees were weighted to obtain a representation of the entire German population (variable ‘gewicht’ in the data sets). To this end, standard weighting procedures were applied to reduce differences between the sample and the entire population with regard to known rates of response and non-response depending on household size, age, gender, educational level, and place of residence. RELATED PUBLICATION AND FURTHER DETAILS The questionnaire, analysis and results will be published in the corresponding report (main text in English language, questionnaire in Appendix B in German language of the interviews and English translation). The report will be available as open access publication at KIT Scientific Publishing (https://www.ksp.kit.edu/). Reference: Orwat, Carsten; Schankin, Andrea (2018): Attitudes towards big data practices and the institutional framework of privacy and data protection - A population survey, KIT Scientific Report 7753, Karlsruhe: KIT Scientific Publishing. FILE FORMATS The data set of responses is saved for the repository KITopen at 2018-11 in the following file formats: comma-separated values (.csv), tapulator-separated values (.dat), Excel (.xlx), Excel 2007 or newer (.xlxs), and SPSS Statistics (.sav). The questionnaire is saved in the following file formats: comma-separated values (.csv), Excel (.xlx), Excel 2007 or newer (.xlxs), and Portable Document Format (.pdf). PROJECT AND FUNDING The survey is part of the project Assessing Big Data (ABIDA) (from 2015-03 to 2019-02), which receives funding from the Federal Ministry of Education and Research (BMBF), Germany (grant no. 01IS15016A-F). http://www.abida.de

This dataset contains data of mobile network coverage in India.

Data has been sourced from https://opencellid.org/ The world's largest Open Database of Cell Towers Locate devices without GPS, explore Mobile Operator coverage and more!

Radio: The generation of broadband cellular network technology (Eg. LTE, GSM)

MCC: Mobile country code.

MNC: Mobile network code.

LAC/TAC/NID: Location Area Code

CID: This is a unique number used to identify each Base transceiver station or sector of BTS

Longitude:This is a geographic coordinate that specifies the east-west position of a point on the Earth's surface

Latitude:This is a geographic coordinate that specifies the north–south position of a point on the Earth's surface.

Range: Approximate area within which the cell could be. (In meters)

Samples: Number of measures processed to get a particular data point

Changeable=1: The location is determined by processing samples

Changeable=0: The location is directly obtained from the telecom firm

Created: When a particular cell was first added to database (UNIX timestamp)

Updated: When a particular cell was last seen (UNIX timestamp)

AverageSignal: To get the positions of cells, OpenCelliD processes measurements from data contributors. Each measurement includes GPS location of device + Scanned cell identifier (MCC-MNC-LAC-CID) + Other device properties (Signal strength). In this process, signal strength of the device is averaged. Most ‘averageSignal’ values are 0 because OpenCelliD simply didn’t receive signal strength values.

This dataset provides data on mobile sites and coverage maps within Australia and is sourced from information collected under the ACCC’s Audit of Telecommunications Infrastructure Assets – Record Keeping Rules (Infrastructure RKR). \r The information is collected from the three national Mobile Network Operators (MNOs), Singtel Optus Pty Limited (ACN 052 833 208) (Optus), Telstra Corporation Limited (ACN 051 775 556) (Telstra), TPG Telecom Limited (ACN 093 058 069) (TPG). \r \r *Please note, the ACCC has aggregated the frequency band coverage maps submitted by the MNOs to create additional technology level coverage maps which are available below (where the technology level maps were not provided by the MNOs). Further information on this is provided in the data interpretation guide (below) that supports this data release.\r \r All the files below can be downloaded and most of them can be manually uploaded and viewed on National Map (https://nationalmap.gov.au). Due to their significant size, a majority of Optus' technology level coverage map files may not be viewable in National Map. This also applies to some of Optus’ frequency band coverage map files. As such another mapping tool may be required to view these large Optus files. \r \r Updates:\r \r 8/9/22\r \r - The following mobile sites spreadsheets were subject to a very small number of revisions: Telstra 2020, Telstra 2021, Optus 2020 and Optus 2021\r \r - The data interpretation guide was updated\r \r - All coverage map file names have been amended to indicate their standard of coverage (see data interpretation guide for more information)

This dataset provides the GPS Co-ordinates of small cell mobile phone services in remote Northern Territory locations. For more information please visit the Northern Territory Government Open Data Portal.