74 datasets found
  1. Number of e-mail users worldwide 2018-2027

    • statista.com
    Updated Jun 20, 2025
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    Statista (2025). Number of e-mail users worldwide 2018-2027 [Dataset]. https://www.statista.com/statistics/255080/number-of-e-mail-users-worldwide/
    Explore at:
    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Despite the growth and prominence of mobile messengers and chat apps, e-mail is an integral part of daily online life. In 2023, the number of global e-mail users amounted to **** billion and is set to grow to **** billion users in 2027. Global e-mail audiencesIn 2023, approximately *** billion e-mails were sent and received every day worldwide. This figure is projected to increase to over *** billion daily e-mails in 2027. As of July 2022, Apple Mail Privacy accounted for over half of the e-mail opens, while mobile use of e-mails saw a significant decrease in their market shares. Apple MPP e-mail app was the most popular e-mail client, accounting for ** percent of e-mail opens. Gmail, the free e-mail service owned by Google, was ranked second with a ** percent open share. Malicious mailMany online users use e-mails for website and newsletter signups and brace themselves for the inevitable flood of spam and marketing communications. Whereas most unwanted e-mails are annoying yet ultimately benign, consumers are right to be wary of malicious e-mail that can be used to compromise their digital accounts and devices. In 2023, ** percent of fraud reports in the United States related to cases in which victims were contacted via e-mail.

  2. d

    Get access of 69 Million Professional's Email Database

    • datarade.ai
    .json, .csv
    Updated Feb 13, 2022
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    Bytescraper (2022). Get access of 69 Million Professional's Email Database [Dataset]. https://datarade.ai/data-products/get-access-of-69-million-professional-s-email-database-b2b-email-databases
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Feb 13, 2022
    Dataset authored and provided by
    Bytescraper
    Area covered
    Spain, Japan, Canada, New Zealand, India, United Kingdom, Italy, South Africa, Switzerland, Germany
    Description

    A good DATA is crucial for any business or organization to grow the network. This is because all relevant details about the company and user are stored in the database. Your companies have benefited from using our email database to extract their prospect's details.

    It is a well-known fact that LinkedIn gives you the opportunity to expand your business network. You can easily connect with your prospects, directly or through mutual connections, by using search keywords related to their name, company, profile, address, etc. However, we're a leading data provider, with us you do not need to do such a thing. Our Professional's email database contains all the necessary business information from your prospects. There are several ways to access them (especially email addresses and phone numbers).

    With our service, you can reach over 69 million records in 200+ countries. Our database is well organized and keeps information easily accessible, so you can use it. Easily increase your sales with reliable LinkedIn data that connects you directly to your goal, here we have worked hard to supply quality, reliable, sustainable email databases.

  3. d

    Email Address Data| Email Database | US Consumers | 650 million Consumer...

    • datarade.ai
    .csv, .txt
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    Stirista, Email Address Data| Email Database | US Consumers | 650 million Consumer Email Addresses [Dataset]. https://datarade.ai/data-products/email-address-data-email-database-us-consumers-564-milli-stirista
    Explore at:
    .csv, .txtAvailable download formats
    Dataset authored and provided by
    Stirista
    Area covered
    United States of America
    Description

    Andrew Wharton's Actionable US Consumer Email Database hosts over 650 million email addresses that have been active within the last 36 months. This database is fully CAN-SPAM compliant and 100% opted-in for Third Party Use.

    This Email Address database successfully connects you with your customers and/or prospects at their most recent, deliverable online address. and Increase impression rates, deliverability, and engagement in your digital campaigns.

    The Email Address Data is 100% populated with email address, HEMS (MD5, Sha1, Sha256) first name, last name, postal address (primary and secondary), IP Address, Time Stamp(s) for Last Registration, Verification, and First Seen. An enhanced version of the database is available with Date-of-Birth (where available), Phone (mobile and landline) and MAIDs to Hashed email conversion.

    The Andrews Wharton Actionable US Consumer Email Database is updated monthly. A complete replacement database or new adds are available as update files.

    Contact us at successdelivered@andrewswharton.com or visit us at www.andrewswharton.com to learn more about this dataset.

  4. Z

    Dataset of Survey on Current Email Management Practices

    • data.niaid.nih.gov
    Updated Jun 13, 2023
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    Sachdeva, Anisha (2023). Dataset of Survey on Current Email Management Practices [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_8028184
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    Dataset updated
    Jun 13, 2023
    Dataset authored and provided by
    Sachdeva, Anisha
    License

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

    Description

    This dataset contains anonymised survey responses from a comprehensive study conducted to explore current email management practices among users. The survey aimed to gain insights into how individuals handle and organize their email communications in various contexts. The survey questionnaire consisted of carefully designed questions related to email usage patterns, organisational strategies, folder structures, and automation utilised for email management. The survey also explored participants' preferences for automated rule-based filtering functionality and any challenges they face in effectively managing their mailbox.

    Researchers and professionals interested in email management and information organisation can leverage this dataset for research, analysis, and potential improvements in email client design and functionality.

    We kindly request that any publications or research utilising this dataset appropriately acknowledge and cite the original source to ensure proper attribution to the survey and its participants.

  5. w

    Enron Email Dataset

    • data.wu.ac.at
    gz
    Updated Oct 10, 2013
    + more versions
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    Global (2013). Enron Email Dataset [Dataset]. https://data.wu.ac.at/odso/datahub_io/OTE3MTliODMtNGEyZi00OTQ0LTgzYTQtNmJiZTgwMDg4NGJi
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    gzAvailable download formats
    Dataset updated
    Oct 10, 2013
    Dataset provided by
    Global
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    About

    From distribution page:

    This dataset was collected and prepared by the CALO Project (A Cognitive Assistant that Learns and Organizes). It contains data from about 150 users, mostly senior management of Enron, organized into folders. The corpus contains a total of about 0.5M messages. This data was originally made public, and posted to the web, by the Federal Energy Regulatory Commission during its investigation.

    The email dataset was later purchased by Leslie Kaelbling at MIT, and turned out to have a number of integrity problems. A number of folks at SRI, notably Melinda Gervasio, worked hard to correct these problems, and it is thanks to them (not me) that the dataset is available. The dataset here does not include attachments, and some messages have been deleted "as part of a redaction effort due to requests from affected employees". Invalid email addresses were converted to something of the form user@enron.com whenever possible (i.e., recipient is specified in some parse-able format like "Doe, John" or "Mary K. Smith") and to no_address@enron.com when no recipient was specified.

    I get a number of questions about this corpus each week, which I am unable to answer, mostly because they deal with preparation issues and such that I just don't know about. If you ask me a question and I don't answer, please don't feel slighted.

    I am distributing this dataset as a resource for researchers who are interested in improving current email tools, or understanding how email is currently used. This data is valuable; to my knowledge it is the only substantial collection of "real" email that is public. The reason other datasets are not public is because of privacy concerns. In using this dataset, please be sensitive to the privacy of the people involved (and remember that many of these people were certainly not involved in any of the actions which precipitated the investigation.)

    Downloads

    Download is "about 400Mb, tarred and gzipped".

    Openness

    Unknown.

  6. d

    US Consumer Marketing Data - 269M+ Consumer Records - 95% Email and Direct...

    • datarade.ai
    Updated Jun 1, 2022
    + more versions
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    Giant Partners (2022). US Consumer Marketing Data - 269M+ Consumer Records - 95% Email and Direct Dials Accuracy [Dataset]. https://datarade.ai/data-products/consumer-business-data-postal-phone-email-demographics-giant-partners
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    Dataset updated
    Jun 1, 2022
    Dataset authored and provided by
    Giant Partners
    Area covered
    United States
    Description

    Premium B2C Consumer Database - 269+ Million US Records

    Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.

    Core Database Statistics

    Consumer Records: Over 269 million

    Email Addresses: Over 160 million (verified and deliverable)

    Phone Numbers: Over 76 million (mobile and landline)

    Mailing Addresses: Over 116,000,000 (NCOA processed)

    Geographic Coverage: Complete US (all 50 states)

    Compliance Status: CCPA compliant with consent management

    Targeting Categories Available

    Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)

    Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options

    Property & Dwelling: Home ownership status, estimated home value, years in residence, property type (single-family, condo, apartment), and dwelling characteristics

    Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting

    Lifestyle & Interests: Purchase history, donation patterns, political preferences, health interests, recreational activities, and hobby-based targeting

    Behavioral Data: Shopping preferences, brand affinities, online activity patterns, and purchase timing behaviors

    Multi-Channel Campaign Applications

    Deploy across all major marketing channels:

    Email marketing and automation

    Social media advertising

    Search and display advertising (Google, YouTube)

    Direct mail and print campaigns

    Telemarketing and SMS campaigns

    Programmatic advertising platforms

    Data Quality & Sources

    Our consumer data aggregates from multiple verified sources:

    Public records and government databases

    Opt-in subscription services and registrations

    Purchase transaction data from retail partners

    Survey participation and research studies

    Online behavioral data (privacy compliant)

    Technical Delivery Options

    File Formats: CSV, Excel, JSON, XML formats available

    Delivery Methods: Secure FTP, API integration, direct download

    Processing: Real-time NCOA, email validation, phone verification

    Custom Selections: 1,000+ selectable demographic and behavioral attributes

    Minimum Orders: Flexible based on targeting complexity

    Unique Value Propositions

    Dual Spouse Targeting: Reach both household decision-makers for maximum impact

    Cross-Platform Integration: Seamless deployment to major ad platforms

    Real-Time Updates: Monthly data refreshes ensure maximum accuracy

    Advanced Segmentation: Combine multiple targeting criteria for precision campaigns

    Compliance Management: Built-in opt-out and suppression list management

    Ideal Customer Profiles

    E-commerce retailers seeking customer acquisition

    Financial services companies targeting specific demographics

    Healthcare organizations with compliant marketing needs

    Automotive dealers and service providers

    Home improvement and real estate professionals

    Insurance companies and agents

    Subscription services and SaaS providers

    Performance Optimization Features

    Lookalike Modeling: Create audiences similar to your best customers

    Predictive Scoring: Identify high-value prospects using AI algorithms

    Campaign Attribution: Track performance across multiple touchpoints

    A/B Testing Support: Split audiences for campaign optimization

    Suppression Management: Automatic opt-out and DNC compliance

    Pricing & Volume Options

    Flexible pricing structures accommodate businesses of all sizes:

    Pay-per-record for small campaigns

    Volume discounts for large deployments

    Subscription models for ongoing campaigns

    Custom enterprise pricing for high-volume users

    Data Compliance & Privacy

    VIA.tools maintains industry-leading compliance standards:

    CCPA (California Consumer Privacy Act) compliant

    CAN-SPAM Act adherence for email marketing

    TCPA compliance for phone and SMS campaigns

    Regular privacy audits and data governance reviews

    Transparent opt-out and data deletion processes

    Getting Started

    Our data specialists work with you to:

    1. Define your target audience criteria

    2. Recommend optimal data selections

    3. Provide sample data for testing

    4. Configure delivery methods and formats

    5. Implement ongoing campaign optimization

    Why We Lead the Industry

    With over two decades of data industry experience, we combine extensive database coverage with advanced targeting capabilities. Our commitment to data quality, compliance, and customer success has made us the preferred choice for businesses seeking superior B2C marketing performance.

    Contact our team to discuss your specific targeting requirements and receive custom pricing for your marketing objectives.

  7. Job Application Email (Anonymized & Feature-Rich)

    • kaggle.com
    Updated Apr 15, 2025
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    Rashmi Shree (2025). Job Application Email (Anonymized & Feature-Rich) [Dataset]. https://www.kaggle.com/datasets/rasho330/job-application-email-anonymized-and-feature-rich
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 15, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Rashmi Shree
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    This dataset consists of a curated and anonymized collection of real job application confirmation emails from a Gmail inbox. It includes confirmation emails, rejection notices, and other relevant correspondences. The dataset was originally curated to address the challenge of eliminating manual job application tracking, allowing for automatic tracking directly from the inbox, capturing application confirmations and rejection notifications.

    The dataset has been carefully pre-processed, cleaned, and enriched with derived features such as:

    1. đź“… Parsed Date and Time
    2. đź•’ Week, Month, and Year of Email
    3. ⏱️ Days Since Email Received
    4. đź“© Email Subject and Body
    5. 🏢 Company Name (Parsed from Subject/Body)
    6. 📊 Application Status Insights

    The dataset was originally curated to build a job application tracking agent that can automatically extract and track application updates—such as confirmations, rejections, interview invites, and assessment notifications—directly from the inbox. The goal was to enable users to easily interact with an AI assistant to analyze and manage their job search process more efficiently.

    ⚠️ Disclaimer: All personal identifiable information (PII) such as names and email addresses have been fully anonymized or redacted. This dataset is intended strictly for educational and research purposes. All personally identifiable information (PII) has been carefully anonymized. Any personal names found in the dataset have been replaced with the fictional name "Michael Gary Scott" as a placeholder. This character reference is used purely for fun and does not correspond to any real individual. Please ensure any further use of this dataset respects privacy and ethical data handling practices.

  8. Email CTR Prediction

    • kaggle.com
    Updated Nov 15, 2022
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    Sk4467 (2022). Email CTR Prediction [Dataset]. https://www.kaggle.com/datasets/sk4467/email-ctr-prediction
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 15, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Sk4467
    Description

    Most organizations today rely on email campaigns for effective communication with users. Email communication is one of the popular ways to pitch products to users and build trustworthy relationships with them. Email campaigns contain different types of CTA (Call To Action). The ultimate goal of email campaigns is to maximize the Click Through Rate (CTR). CTR = No. of users who clicked on at least one of the CTA / No. of emails delivered. This Dataset contains details of body length, sub length, mean paragraph , day of week, is weekend, etc.

  9. t

    Spam Mails Dataset - FAIR experiment

    • test.researchdata.tuwien.ac.at
    application/x-hdf5 +3
    Updated Apr 25, 2025
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    Nicolas Bernal; Nicolas Bernal; Nicolas Bernal; Nicolas Bernal (2025). Spam Mails Dataset - FAIR experiment [Dataset]. http://doi.org/10.70124/0e1sf-saz86
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    application/x-hdf5, png, txt, csvAvailable download formats
    Dataset updated
    Apr 25, 2025
    Dataset provided by
    TU Wien
    Authors
    Nicolas Bernal; Nicolas Bernal; Nicolas Bernal; Nicolas Bernal
    License

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

    Description

    Context

    The Spam Mail dataset is a collection of 5.171 emails that have been classified as spam or ham (non-spam). This dataset was originally created in 2006 for research purposes in the field of spam detection and filtering using machine learning techniques, specifically a Naive Bayes classifier as described in the paper "Spam Filtering with Naive Bayes - Which Naive Bayes?" by Metsis, Androutsopoulos, and Paliouras.
    The data was created using mainly the inbox of 6 users of the company "Enron" for the "ham" emails, and the "spam" emails were collected from various sources, including the SpamAssassin corpus, the Honeypot project, the spam collection of Bruce Guenter, and spam collected by the authors themselves.
    The emails were preprocessed to remove any html tags, and emails with non-latin characters were removed to avoid any possible bias since all "ham" emails are written with latin characters.
    The original data can be found in CSV format on Kaggle at: https://www.kaggle.com/datasets/venky73/spam-mails-dataset/data

    Project description

    In this project we will use the Spam Mail dataset to train a Neural Network model to classify emails as spam or ham. The dataset will be further preprocessed to remove any unnecessary characters like stopwords and punctuation.
    The emails will also be tokenized and converted into a format suitable for training the model, but this last step will be performed in the code itself so it is not included in the dataset.

    Files

    In this repository you will find the following files:
    - README.md: Project overview, dataset source, structure, and dependency information.
    - confusion_matrix.png: A confusion matrix that shows the performance of the model on the test set.
    - evaluation_metrics.txt: Text summary of evaluation metrics: accuracy, precision, recall, and F1-score.
    - test_predictions.csv: A CSV file that contains the predictions of the model on the test set.
    - top_spam_words.png: A bar chart showing the top 10 most frequent words in correctly predicted spam emails.
    - spam_classifier.h5: The trained model file, which can be used to make predictions on new emails.
  10. d

    Email Address Data | Validated Personal and Business Emails | 148MM+ US B2B...

    • datarade.ai
    .json, .csv, .xls
    Updated Feb 20, 2024
    + more versions
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    Salutary Data (2024). Email Address Data | Validated Personal and Business Emails | 148MM+ US B2B Contacts [Dataset]. https://datarade.ai/data-products/salutary-data-email-address-data-validated-personal-and-b-salutary-data
    Explore at:
    .json, .csv, .xlsAvailable download formats
    Dataset updated
    Feb 20, 2024
    Dataset authored and provided by
    Salutary Data
    Area covered
    United States of America
    Description

    Salutary Data is a boutique, B2B contact and company data provider that's committed to delivering high quality data for sales intelligence, lead generation, marketing, recruiting / HR, identity resolution, and ML / AI. Our database currently consists of 148MM+ highly curated B2B Contacts ( US only), along with over 4M+ companies, and is updated regularly to ensure we have the most up-to-date information.

    We can enrich your in-house data ( CRM Enrichment, Lead Enrichment, etc.) and provide you with a custom dataset ( such as a lead list) tailored to your target audience specifications and data use-case. We also support large-scale data licensing to software providers and agencies that intend to redistribute our data to their customers and end-users.

    What makes Salutary unique? - We offer our clients a truly unique, one-stop aggregation of the best-of-breed quality data sources. Our supplier network consists of numerous, established high quality suppliers that are rigorously vetted. - We leverage third party verification vendors to ensure phone numbers and emails are accurate and connect to the right person. Additionally, we deploy automated and manual verification techniques to ensure we have the latest job information for contacts. - We're reasonably priced and easy to work with.

    Products: API Suite Web UI Full and Custom Data Feeds

    Services: Data Enrichment - We assess the fill rate gaps and profile your customer file for the purpose of appending fields, updating information, and/or rendering net new “look alike” prospects for your campaigns. ABM Match & Append - Send us your domain or other company related files, and we’ll match your Account Based Marketing targets and provide you with B2B contacts to campaign. Optionally throw in your suppression file to avoid any redundant records. Verification (“Cleaning/Hygiene”) Services - Address the 2% per month aging issue on contact records! We will identify duplicate records, contacts no longer at the company, rid your email hard bounces, and update/replace titles or phones. This is right up our alley and levers our existing internal and external processes and systems.

  11. Enron Email Time-Series Network

    • zenodo.org
    csv
    Updated Jan 24, 2020
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    Volodymyr Miz; Benjamin Ricaud; Pierre Vandergheynst; Volodymyr Miz; Benjamin Ricaud; Pierre Vandergheynst (2020). Enron Email Time-Series Network [Dataset]. http://doi.org/10.5281/zenodo.1342353
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jan 24, 2020
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Volodymyr Miz; Benjamin Ricaud; Pierre Vandergheynst; Volodymyr Miz; Benjamin Ricaud; Pierre Vandergheynst
    License

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

    Description

    We use the Enron email dataset to build a network of email addresses. It contains 614586 emails sent over the period from 6 January 1998 until 4 February 2004. During the pre-processing, we remove the periods of low activity and keep the emails from 1 January 1999 until 31 July 2002 which is 1448 days of email records in total. Also, we remove email addresses that sent less than three emails over that period. In total, the Enron email network contains 6 600 nodes and 50 897 edges.

    To build a graph G = (V, E), we use email addresses as nodes V. Every node vi has an attribute which is a time-varying signal that corresponds to the number of emails sent from this address during a day. We draw an edge eij between two nodes i and j if there is at least one email exchange between the corresponding addresses.

    Column 'Count' in 'edges.csv' file is the number of 'From'->'To' email exchanges between the two addresses. This column can be used as an edge weight.

    The file 'nodes.csv' contains a dictionary that is a compressed representation of time-series. The format of the dictionary is Day->The Number Of Emails Sent By the Address During That Day. The total number of days is 1448.

    'id-email.csv' is a file containing the actual email addresses.

  12. p

    Brazil Email Data

    • listtodata.com
    .csv, .xls, .txt
    Updated Jul 17, 2025
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    The citation is currently not available for this dataset.
    Explore at:
    .csv, .xls, .txtAvailable download formats
    Dataset updated
    Jul 17, 2025
    Authors
    List to Data
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2025 - Dec 31, 2025
    Area covered
    Brazil, Belgium, United States
    Variables measured
    phone numbers, Email Address, full name, Address, City, State, gender,age,income,ip address,
    Description

    Brazil email data fuels your outreach with high-quality contacts, driving engagement and conversions in Austria’s dynamic business landscape. This high-quality database contains verified email addresses for effective marketing campaigns. Similarly, you can segment your audience for personalized messaging. In addition, this library is regularly checked for accuracy. Therefore, you can ensure your messages reach the right people. Moreover, this resource is perfect for businesses looking to expand within Brazil. Explore the ultimate resource for your marketing needs, visit List To Data, and unlock this database. Consequently, you can improve your marketing ROI.Brazil consumer email list provides access to the Brazilian market with our premium consumer email list. This comprehensive resource provides access to a vast network of potential customers. As a result, you can increase your brand visibility and drive sales. Moreover, our data is regularly updated and verified. Therefore, you can improve your marketing ROI. Consequently, you can target specific demographics and regions. Furthermore, this valuable resource allows you to connect with key decision-makers. Finally, List to Data offers this powerful dataset to fuel your business growth in Brazil.Brazil business email list is a premium database for connecting with professionals in Brazil. This resource includes verified leads to ensure your campaigns are impactful. Additionally, it is designed to optimize your outreach efforts. Moreover, the directory is updated regularly to reflect the latest market trends. Furthermore, it offers a cost-effective way to expand your business reach. As a result, you can improve engagement and drive sales. In addition, this library of contacts is perfect for B2B and B2C campaigns. Finally, rely on List To Data to provide a dataset that enhances your marketing strategy and grows your business.

  13. o

    Count of unique users per email app

    • opendataumea.opendatasoft.com
    • opendata.umea.se
    csv, excel, json
    Updated Sep 1, 2025
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    (2025). Count of unique users per email app [Dataset]. https://opendataumea.opendatasoft.com/explore/dataset/getemailappusageappsusercounts/analyze/
    Explore at:
    excel, csv, jsonAvailable download formats
    Dataset updated
    Sep 1, 2025
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Get the count of unique users per email app

  14. h

    Panza-emails

    • huggingface.co
    Updated Feb 19, 2025
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    IST Austria Distributed Algorithms and Systems Lab (2025). Panza-emails [Dataset]. https://huggingface.co/datasets/ISTA-DASLab/Panza-emails
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 19, 2025
    Dataset authored and provided by
    IST Austria Distributed Algorithms and Systems Lab
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    The Panza Emails dataset

    This dataset contains collections of emails of three authentic users (david, isabel, and marcus), with personal information (names, places, etc.) replaced by other ones for donor privacy. Except for these changes, the language of the emails is genuine. The intention of this dataset is to allow researchers to study strategies for text personalization. The data was donated explicitly for this purpose. This dataset is ethically collected and fully licensed for… See the full description on the dataset page: https://huggingface.co/datasets/ISTA-DASLab/Panza-emails.

  15. u

    Email app statistics

    • opendata.umea.se
    • opendataumea.opendatasoft.com
    csv, excel, json
    Updated Jul 1, 2025
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    (2025). Email app statistics [Dataset]. https://opendata.umea.se/explore/dataset/getemailappusageusercounts/
    Explore at:
    csv, json, excelAvailable download formats
    Dataset updated
    Jul 1, 2025
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Get the count of unique users that connected to Exchange Online using any email app.

  16. p

    China Email Data

    • listtodata.com
    .csv, .xls, .txt
    Updated Jul 17, 2025
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    List to Data (2025). China Email Data [Dataset]. https://listtodata.com/china-email-list
    Explore at:
    .csv, .xls, .txtAvailable download formats
    Dataset updated
    Jul 17, 2025
    Authors
    List to Data
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2025 - Dec 31, 2025
    Area covered
    China, United States
    Variables measured
    phone numbers, Email Address, full name, Address, City, State, gender,age,income,ip address,
    Description

    China email data delivers high-quality contacts, enabling you to expand your reach and dominate your market. Access the vast potential of China’s market with our China Email Data, a powerful database for global businesses. This resource offers verified leads across industries, ensuring your campaigns resonate with the right audience. At List to Data, we prioritize accuracy and reliability, delivering a directory that’s both comprehensive and actionable. Moreover, our material is regularly updated to reflect the latest market trends. Whether you’re expanding your reach or launching a new product, this dataset provides the foundation for success. Simplify your marketing efforts and boost engagement with this trusted library. Trust List to Data to deliver the tools you need for impactful outreach and lasting connections. China consumer email list may help you change your outreach efforts by ensuring your message reaches the appropriate people every time! This comprehensive resource provides access to a massive network of potential customers. As a result, you can increase your brand visibility and drive sales. Moreover, our data is regularly updated and verified. Therefore, you can improve your marketing ROI. Consequently, you can target specific demographics and regions. Furthermore, this valuable resource allows you to connect with key decision-makers. Finally, List to Data offers this powerful dataset to fuel your business growth in China. China business email list is a powerful resource for reaching professionals in China. This database provides verified leads to ensure your campaigns are effective. Additionally, it is designed to save time and maximize ROI. Moreover, the directory is regularly updated for accuracy. Furthermore, it offers a seamless way to expand your market reach. As a result, you can enhance your marketing efforts with reliable information. In addition, this library of contacts is tailored for both B2B and B2C outreach. Finally, trust List To Data to deliver a dataset that drives results and boosts your market presence.

  17. d

    US CEO Contact Data | 1.8MM+ CEO Profiles with Validated Work Email, Mobile...

    • datarade.ai
    .json, .csv, .xls
    Updated Aug 12, 2023
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    Salutary Data (2023). US CEO Contact Data | 1.8MM+ CEO Profiles with Validated Work Email, Mobile Phone + More [Dataset]. https://datarade.ai/data-products/salutary-data-us-ceo-contact-data-500k-ceo-profiles-with-salutary-data
    Explore at:
    .json, .csv, .xlsAvailable download formats
    Dataset updated
    Aug 12, 2023
    Dataset authored and provided by
    Salutary Data
    Area covered
    United States
    Description

    Salutary Data is a boutique, B2B contact and company data provider that's committed to delivering high quality data for sales intelligence, lead generation, marketing, recruiting / HR, identity resolution, and ML / AI. Our database currently consists of 148MM+ highly curated B2B Contacts ( US only), along with over 4MM+ companies, and is updated regularly to ensure we have the most up-to-date information.

    We can enrich your in-house data ( CRM Enrichment, Lead Enrichment, etc.) and provide you with a custom dataset ( such as a lead list) tailored to your target audience specifications and data use-case. We also support large-scale data licensing to software providers and agencies that intend to redistribute our data to their customers and end-users.

    What makes Salutary unique? - We offer our clients a truly unique, one-stop aggregation of the best-of-breed quality data sources. Our supplier network consists of numerous, established high quality suppliers that are rigorously vetted. - We leverage third party verification vendors to ensure phone numbers and emails are accurate and connect to the right person. Additionally, we deploy automated and manual verification techniques to ensure we have the latest job information for contacts. - We're reasonably priced and easy to work with.

    Products: API Suite Web UI Full and Custom Data Feeds

    Services: Data Enrichment - We assess the fill rate gaps and profile your customer file for the purpose of appending fields, updating information, and/or rendering net new “look alike” prospects for your campaigns. ABM Match & Append - Send us your domain or other company related files, and we’ll match your Account Based Marketing targets and provide you with B2B contacts to campaign. Optionally throw in your suppression file to avoid any redundant records. Verification (“Cleaning/Hygiene”) Services - Address the 2% per month aging issue on contact records! We will identify duplicate records, contacts no longer at the company, rid your email hard bounces, and update/replace titles or phones. This is right up our alley and levers our existing internal and external processes and systems.

  18. Ling-Spam Dataset

    • kaggle.com
    Updated Nov 15, 2019
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    Mandy Gu (2019). Ling-Spam Dataset [Dataset]. https://www.kaggle.com/mandygu/lingspam-dataset/notebooks
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 15, 2019
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Mandy Gu
    Description

    Context

    The Ling-Spam dataset is a collection of 2,893 spam and non-spam messages curated from the Linguist List. These messages focus on linguistic interests around job postings, research opportunities and software discussion.

    Content

    Header information are removed.

    • 2412 legitimate messages
    • 481 spam messages

    Acknowledgements

    All acknowledgements go to the original authors of "http://www.aueb.gr/users/ion/data/lingspam_public.tar.gz">A Memory-Based Approach to Anti-Spam Filtering for Mailing Lists.. The dataset was made publicly available as a part of that paper. The raw data, which is partitioned into subdirectories, is hosted here.

  19. H

    Data from: Normative data for email writing

    • dataverse.harvard.edu
    Updated Dec 19, 2014
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    Lindsey Thiel; Karen Sage; Paul Conroy (2014). Normative data for email writing [Dataset]. http://doi.org/10.7910/DVN/28204
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 19, 2014
    Dataset provided by
    Harvard Dataverse
    Authors
    Lindsey Thiel; Karen Sage; Paul Conroy
    License

    https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/28204https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/28204

    Time period covered
    2011 - 2014
    Area covered
    United Kingdom
    Description

    This data set includes emails from forty two healthy control participants ranging from 16 to 88 years of age (mean = 45.64) and 9 to 24 years of education (mean = 13.36). Three emails were produced by each participant, each within a time limit of three minutes. Emails were anonymised by replacing names, addresses and professions with different names, addresses and professions consisting of the same number of letters. Otherwise, the emails appear exactly as they were written, with no changes to layout, spaces, words, letter case or punctuation. It is expected that this normative data will be useful to clinicians and researchers working with adults with acquired language disorders in assessing email writing.

  20. Demo Notebook Send Email When New Data Found

    • se-national-government-developer-esrifederal.hub.arcgis.com
    Updated Jul 30, 2025
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    Esri National Government (2025). Demo Notebook Send Email When New Data Found [Dataset]. https://se-national-government-developer-esrifederal.hub.arcgis.com/documents/2ef05d8b9c694fcba83502475bad4d5e
    Explore at:
    Dataset updated
    Jul 30, 2025
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri National Government
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Author: Titus, Maxwell (mtitus@esri.com)Last Updated: 7/30/2025 Intended Environment: ArcGIS Notebooks on ArcGIS Online, ArcGIS Portal, or ArcGIS Pro. Purpose: This Notebook demonstrates a way to send out emails with ArcGIS Online (AGOL) or ArcGIS Portal based on whether new data entries have been detected. This does not require admin privileges to run this script. Requirements: There should be a:Hosted Feature Table or Layer to Monitor (e.g., a Survey123 Dataset)An ArcGIS Online or ArcGIS Portal with users who have their email associated with their accounts. This is more so an AGOL requirement as the method used for ArcGIS Portal is custom and can be adapted (though it is more difficult to use).

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Statista (2025). Number of e-mail users worldwide 2018-2027 [Dataset]. https://www.statista.com/statistics/255080/number-of-e-mail-users-worldwide/
Organization logo

Number of e-mail users worldwide 2018-2027

Explore at:
87 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 20, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

Despite the growth and prominence of mobile messengers and chat apps, e-mail is an integral part of daily online life. In 2023, the number of global e-mail users amounted to **** billion and is set to grow to **** billion users in 2027. Global e-mail audiencesIn 2023, approximately *** billion e-mails were sent and received every day worldwide. This figure is projected to increase to over *** billion daily e-mails in 2027. As of July 2022, Apple Mail Privacy accounted for over half of the e-mail opens, while mobile use of e-mails saw a significant decrease in their market shares. Apple MPP e-mail app was the most popular e-mail client, accounting for ** percent of e-mail opens. Gmail, the free e-mail service owned by Google, was ranked second with a ** percent open share. Malicious mailMany online users use e-mails for website and newsletter signups and brace themselves for the inevitable flood of spam and marketing communications. Whereas most unwanted e-mails are annoying yet ultimately benign, consumers are right to be wary of malicious e-mail that can be used to compromise their digital accounts and devices. In 2023, ** percent of fraud reports in the United States related to cases in which victims were contacted via e-mail.

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