Nymblr offers access to over 80 million US-based verified B2B contacts with valid work emails, personal emails, work phones & direct dials, and social profiles. Easily enrich your contact data in real-time with our APIs or provide us with flat files with your records and we'll do the work for you.

Nymblr makes it easy to enrich emails, phone numbers, social media profiles and receive additional data attributes including:

Job Title Seniority Level (C-Level/Owner, VP, Director, etc.) Job Department (Sales, Accounting, Marketing, Finance, etc.) Skills Company Name/Company Domain Company Industry Company SIC Company Revenue Company Size Location (State, and City)

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The aim of this paper is to investigate the re-use of research data deposited in digital data archive in the social sciences. The study examines the quantity, type, and purpose of data downloads by analyzing enriched user log data collected from Swiss data archive. The findings show that quantitative datasets are downloaded increasingly from the digital archive and that downloads focus heavily on a small share of the datasets. The most frequently downloaded datasets are survey datasets collected by research organizations offering possibilities for longitudinal studies. Users typically download only one dataset, but a group of heavy downloaders form a remarkable share of all downloads. The main user group downloading data from the archive are students who use the data in their studies. Furthermore, datasets downloaded for research purposes often, but not always, serve to be used in scholarly publications. Enriched log data from data archives offer an interesting macro level perspective on the use and users of the services and help understanding the increasing role of repositories in the social sciences. The study provides insights into the potential of collecting and using log data for studying and evaluating data archive use.

Data Enrichment Tool Market Outlook

The global data enrichment tool market size was valued at approximately USD 1.5 billion in 2023, and it is projected to reach around USD 5.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 16.3% during the forecast period. This substantial growth is driven by the increasing demand for accurate, comprehensive, and quality data to support business intelligence and analytics in various sectors.

Several factors contribute to the robust growth of the data enrichment tool market. One of the primary drivers is the proliferation of big data across industries. Organizations are constantly collecting vast amounts of data from various sources, and the need to refine this raw data into actionable insights has never been greater. Data enrichment tools play a crucial role in this transformation by enhancing and improving the quality of data, thereby enabling businesses to make informed decisions. The evolution of machine learning and artificial intelligence technologies has further augmented the capabilities of data enrichment tools, making them indispensable in the modern data-driven landscape.

Another significant growth factor is the increasing adoption of customer-centric business models. Enterprises are focusing on understanding their customers better to provide personalized experiences, and enriched data is key to achieving this goal. By integrating various data points and ensuring their accuracy and relevance, data enrichment tools help in building comprehensive customer profiles. This, in turn, leads to more effective marketing strategies, enhanced customer satisfaction, and improved retention rates. Additionally, the rise of e-commerce and digital platforms has necessitated the need for enriched data to gain a competitive edge in the market.

The regulatory landscape surrounding data privacy and security is also a pivotal factor influencing the growth of the data enrichment tool market. With stringent regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), organizations are under immense pressure to maintain high standards of data accuracy and compliance. Data enrichment tools assist in ensuring that the data used by companies is not only accurate but also compliant with these regulations. This aspect is particularly crucial for sectors such as BFSI and healthcare, where data integrity and privacy are paramount.

In the rapidly evolving landscape of data enrichment, the role of an Alternative Data Provider has become increasingly significant. These providers offer unique datasets that are not traditionally available through conventional data sources. By leveraging alternative data, organizations can gain a competitive edge by uncovering hidden patterns and insights that might otherwise go unnoticed. This data can include information from social media, satellite imagery, web traffic, and more, providing a more comprehensive view of market trends and consumer behavior. The integration of alternative data into enrichment tools allows businesses to enhance their analytical capabilities, leading to more informed decision-making and strategic planning. As the demand for diverse and high-quality data continues to grow, the influence of Alternative Data Providers is expected to expand, offering new opportunities for innovation and growth in the data enrichment tool market.

From a regional perspective, North America holds the largest share of the data enrichment tool market. The presence of major technology players and the high adoption rate of advanced analytics solutions in this region significantly contribute to its dominance. However, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period. The rapid digital transformation, increasing internet penetration, and the burgeoning e-commerce industry in countries like China and India are key factors driving the market in this region. Europe and Latin America also present substantial growth opportunities due to the increasing focus on data-driven decision-making processes across industries.

Component Analysis

The data enrichment tool market is segmented by components into software and services. The software component dominates the market due to the increasing adoption of sophisticated data enrichment platforms that offer advanced features like machine learning integration, real-time data processing, and extensive data analytics capabilities. These software s

Stay updated with Market Research Intellect's Data Enrichment Tool Market Report, valued at USD 3.5 billion in 2024, projected to reach USD 9.2 billion by 2033 with a CAGR of 12.5% (2026-2033).

OpenWeb Ninja's Company Website Contacts Scraper API extracts/scrapes B2B Contact Data such as B2B Email Data, Phone Number Data, and Social Contacts from a website domain in real-time.

The API pulls public data from a company website domain & related sources on the web and returns email addresses, phone numbers, Facebook URL, TikTok URL, Instagram URL, LinkedIn URL, Twitter URL, Youtube Channel URL, GitHub URL, and Pinterest URL, when available.

OpenWeb Ninja's Company Website Contacts Scraper API's B2B Contact Data, Phone Number Data, and Social Contacts Data is typically used for: - B2B Contact Enrichment - B2B Email Marketing - B2B Lead Generation - Ads Targeting - Marketing/Sales Data Enrichment

OpenWeb Ninja's Company Website Contacts Scraper API Stats & Capabilities: - 1000+ Emails and Phone Numbers per company website domain are supported - 8 Social networks covered: Facebook, TikTok, Instagram, LinkedIn, Twitter, Youtube, GitHub, and Pinterest. - Scrapes all website pages, quickly. - Support for getting website domain by company name

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.

From our comprehensive US Data Lake, we proudly present 23M+ high-quality US decision-makers and influencers.

Take your ABM strategy to the next level, build a strong pipeline and close deals by laser targeting key decision-makers and influencers based on their department, job functions, job responsibilities, interest areas and expertise, then utilise essential prospect information, including verified work email addresses and business phone and social links.

Our data is sourced directly from executives, businesses, official sources and registries, standardised, de-duped, and verified, and then processed through vigorous compliance procedures for GDPR/PECR on a legitimate interest basis and RTBI etc. This results in a highly accurate single source of quality and compliant B2B data.

It is with our B2B Live Data Lake that we can enrich your CRM data, supply new prospect data, verify leads, and provide you with a custom dataset tailored to your target audience specifications. We also cater for big data licensing to software providers and agencies that intend to supply our data to their customers and use it in their software solutions.

and much more

Why Choose 1 Stop Data?

• We offer our clients a unique, single source of quality and compliant data.
• We don't rely on 3rd party vendors.
• We utilise extensive verification processes to help ensure phone numbers and emails are accurate and connect to the right person.
• We are budget-friendly and our team are highly experienced.

Products and Services:

The oscar4.io web platform for self-service data on demand Bulk data feeds Data hygiene, standardisation, cleansing and enrichment Know Your Business (KYB)

Keywords:

B2B,Prospect Data,Validated Work Emails,Personal Emails,Email Enrichment,Company Data,Lead Enrichment,Data Enhancement,Account Based Marketing (ABM),Customer Data,Phone Enrichment,LinkedIn URL,Market Intelligence,Business Intelligence,Data Append,Contact Data,Lead Generation,360-Degree Customer View,Data Cleansing,Lead Data,Email and Phone Validation,Data Augmentation,Segmentation,Data Enrichment,Email Marketing,Data Intelligence,Direct Marketing,Customer Insights,Audience Targeting,Audience Generation,Mobile Phone,B2B Data Enrichment,Social Advertising,Due Diligence,B2B Advertising,Audience Insights,B2B Lead Retargeting,Contact Information,Demographic Data,Consumer Data Enrichment,People-Based Marketing,Contact Data Enrichment,Customer Data Insights,Prospecting,Sales Intelligence,Predictive Analytics,Email Address Validation,Company Data Enrichment,Audience Intelligence,Cold Outreach,Analytics,Marketing Data Enrichment,Customer Acquisition,Data Cleansing,B2C Data,People Data,Professional Information,Recruiting and HR,KYC,B2B List Validation,Lead Information,Sales Prospecting,B2B Sales,B2B Data,Lead Lists,Contact Validation,Competitive Intelligence,Customer Data Enrichment,Identity Resolution,Identity Validation,Data Science,B2C Data Enrichment,B2C,Lead Data Enrichment,Social Media Data.

Factori's Person API empowers businesses to enhance their contact database of Shopify and Klaviyo by enriching data. Simply input phone numbers, email addresses, hashed values, or name/company details, and receive comprehensive contact details in a standardized format. Fuel your marketing, sales, and customer relationship management activities with enriched contact information, including names, company details, job titles, contact information, social media profiles, and more. With optimized performance, robust error handling, and data security measures, Factori's Person API provides a seamless experience. Unlock valuable insights, personalize your outreach, and drive business growth effortlessly with Factori's Person API. Use Cases: Personalized Marketing: Enrich existing contact data with additional details such as social media profiles, educational background, or job titles. Tailor your marketing messages and campaigns to specific customer segments, improving personalization and engagement. Account-Based Marketing (ABM): Enhance your ABM strategy by enriching contact data of target accounts. Gain a comprehensive understanding of key stakeholders, their roles, and their preferences to deliver highly targeted and personalized campaigns. Sales Intelligence: Arm your sales team with enriched contact information to improve prospecting and sales conversations. Access valuable insights such as past experiences, interests, or industry expertise to establish meaningful connections and drive conversions. Data Cleansing and Validation: Ensure the accuracy and completeness of your contact database by enriching existing data with verified information. Update outdated or missing contact details, improving data quality and integrity. Market Research and Analysis: Enrich contact data to gain deeper insights into industry trends, job movements, or market dynamics. Analyze enriched data to identify patterns, opportunities, and market gaps for informed decision-making.

Solution Publishing by Allforce Data Enrichment - Transform Your Database into Your Strategic Advantage

Our data enrichment solution is built on a powerful identity foundation that delivers comprehensive insights beyond basic contact information:

Unmatched Identity Resolution Our proprietary ASID (Allforce Source ID) system cross-references hundreds of data sources Advanced matching algorithms create accurate, unified contact profiles Seamlessly links professional and personal identities for a complete 360-degree view

Comprehensive Profile Development

Personal Dimensions Complete demographics (name, gender, age range) Lifestyle indicators (marital status, children, homeownership) Financial insights (income range, net worth)

Professional Context Detailed company information (name, domain, revenue, size, industry) Career positioning (job title, seniority, department) Verified business contact details

Contact Verification Phone number validation with type classification (direct, personal, mobile) Address verification with USPS DPV code validation Email validation and deliverability scoring

Digital Footprint Social media profile correlation (LinkedIn) Digital engagement indicators

Strategic Impact

Our enrichment process doesn't simply fill data gaps—it reveals valuable connections between professional and personal identities, helping you understand and engage your contacts across both business and consumer contexts.

Contact us today for a complimentary data assessment and discover how our identity resolution can transform your fragmented database into your most valuable business asset.

We describe a bibliometric network characterizing co-authorship collaborations in the entire Italian academic community. The network, consisting of 38,220 nodes and 507,050 edges, is built upon two distinct data sources: faculty information provided by the Italian Ministry of University and Research and publications available in Semantic Scholar. Both nodes and edges are associated with a large variety of semantic data, including gender, bibliometric indexes, authors' and publications' research fields, and temporal information. While linking data between the two original sources posed many challenges, the network has been carefully validated to assess its reliability and to understand its graph-theoretic characteristics. By resembling several features of social networks, our dataset can be profitably leveraged in experimental studies in the wide social network analytics domain as well as in more specific bibliometric contexts. , The proposed network is built starting from two distinct data sources:

the entire dataset dump from Semantic Scholar (with particular emphasis on the authors and papers datasets) the entire list of Italian faculty members as maintained by Cineca (under appointment by the Italian Ministry of University and Research).

By means of a custom name-identity recognition algorithm (details are available in the accompanying paper published in Scientific Data), the names of the authors in the Semantic Scholar dataset have been mapped against the names contained in the Cineca dataset and authors with no match (e.g., because of not being part of an Italian university) have been discarded. The remaining authors will compose the nodes of the network, which have been enriched with node-related (i.e., author-related) attributes. In order to build the network edges, we leveraged the papers dataset from Semantic Scholar: specifically, any two authors are said to be connected if there is at least one pap..., , # Data cleaning and enrichment through data integration: networking the Italian academia

https://doi.org/10.5061/dryad.wpzgmsbwj

Manuscript published in Scientific Data with DOI .

Description of the data and file structure

This repository contains two main data files:

• edge_data_AGG.csv, the full network in comma-separated edge list format (this file contains mainly temporal co-authorship information);
• Coauthorship_Network_AGG.graphml, the full network in GraphML format.Â

along with several supplementary data, listed below, useful only to build the network (i.e., for reproducibility only):

• University-City-match.xlsx, an Excel file that maps the name of a university against the city where its respective headquarter is located;
• Areas-SS-CINECA-match.xlsx, an Excel file that maps the research areas in Cineca against the research areas in Semantic Scholar.

Description of the main data files

The `Coauthorship_Networ...

This table contains names, positions, and references for the samples contained in the sequence dataset and whether Prokaryotes and/or Eukaryotes were analyzed from the sample in this study. (CSV 3 kb)

Sex-dependent Effects of Social Enrichment on Goal-Directed Behavior

Find any Shopify store in North America's detailed info. The data includes: - Store Name - Store URL - Product Distribution and Categories - Alexa Ranks - Number Of Products in Store - Country (Please look into other products for the global lists) - Email and Contact Info - Social Media Outlets With URLs

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Alternative Data Market Size 2025-2029

The alternative data market size is forecast to increase by USD 60.32 billion, at a CAGR of 52.5% between 2024 and 2029.

The market is experiencing significant growth, driven by the increased availability and diversity of data sources. This expanding data landscape is fueling the rise of alternative data-driven investment strategies across various industries. However, the market faces challenges related to data quality and standardization. As companies increasingly rely on alternative data to inform business decisions, ensuring data accuracy and consistency becomes paramount. Addressing these challenges requires robust data management systems and collaboration between data providers and consumers to establish industry-wide standards. Companies that effectively navigate these dynamics can capitalize on the wealth of opportunities presented by alternative data, driving innovation and competitive advantage.

What will be the Size of the Alternative Data Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market continues to evolve, with new applications and technologies shaping its dynamics. Predictive analytics and deep learning are increasingly being integrated into business intelligence systems, enabling more accurate risk management and sales forecasting. Data aggregation from various sources, including social media and web scraping, enriches datasets for more comprehensive quantitative analysis. Data governance and metadata management are crucial for maintaining data accuracy and ensuring data security. Real-time analytics and cloud computing facilitate decision support systems, while data lineage and data timeliness are essential for effective portfolio management. Unstructured data, such as sentiment analysis and natural language processing, provide valuable insights for various sectors. Machine learning algorithms and execution algorithms are revolutionizing trading strategies, from proprietary trading to high-frequency trading. Data cleansing and data validation are essential for maintaining data quality and relevance. Standard deviation and regression analysis are essential tools for financial modeling and risk management. Data enrichment and data warehousing are crucial for data consistency and completeness, allowing for more effective customer segmentation and sales forecasting. Data security and fraud detection are ongoing concerns, with advancements in technology continually addressing new threats. The market's continuous dynamism is reflected in its integration of various technologies and applications. From data mining and data visualization to supply chain optimization and pricing optimization, the market's evolution is driven by the ongoing unfolding of market activities and evolving patterns.

How is this Alternative Data Industry segmented?

The alternative data industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. TypeCredit and debit card transactionsSocial mediaMobile application usageWeb scrapped dataOthersEnd-userBFSIIT and telecommunicationRetailOthersGeographyNorth AmericaUSCanadaMexicoEuropeFranceGermanyItalyUKAPACChinaIndiaJapanRest of World (ROW)

By Type Insights

The credit and debit card transactions segment is estimated to witness significant growth during the forecast period.Alternative data derived from card and debit card transactions plays a pivotal role in business intelligence, offering valuable insights into consumer spending behaviors. This data is essential for market analysts, financial institutions, and businesses aiming to optimize strategies and enhance customer experiences. Two primary categories exist within this data segment: credit card transactions and debit card transactions. Credit card transactions reveal consumers' discretionary spending patterns, luxury purchases, and credit management abilities. By analyzing this data through quantitative methods, such as regression analysis and time series analysis, businesses can gain a deeper understanding of consumer preferences and trends. Debit card transactions, on the other hand, provide insights into essential spending habits, budgeting strategies, and daily expenses. This data is crucial for understanding consumers' practical needs and lifestyle choices. Machine learning algorithms, such as deep learning and predictive analytics, can be employed to uncover patterns and trends in debit card transactions, enabling businesses to tailor their offerings and services accordingly. Data governance, data security, and data accuracy are critical considerations when dealing with sensitive financial d

Soleadify is a modern data technology company. Every week, we use AI and NLP to capture and refresh web and social media content on over 70 million active SMBs and private companies in 200 countries and 20 languages.

Our technology enables us to convert unstructured content into accessible, actionable data that defines what a company does, what products it produces, what technology it uses and what its ESG profile is. In total, we capture more than 100 attributes of each company. We do all of this at high velocity, capturing new businesses and validating all attributes of existing business every week. The speed of our data collection and the frequency of our refresh cycles enable us to monitor material changes to millions of companies.

We deliver our solution through APIs that support two broad uses: searching and data enrichment. Our APIs are easy and quick to implement, increasing the speed to value creation for our partner and end clients.

Our high quality data supports a number of use cases including procurement, SMB lending, SMB underwriting and private company market intelligence. We work with a variety of fintech, insuretech, procuretech and large-scale data aggregators in order to reach end clients.

To date, we have helped many Tier 1 enterprises including one of Canada's largest banks, a top 10 insurance company that is part of a $15B global organization, and the largest global consulting firm.

Environmental enrichment (EE) protocolDuring the EE in the brood boxes (8-28 days old), 3 different sets of enrichments were rotated between boxes every 7 days. After reallocation in home cages at 28 days of age, EE was applied in 3 periods with different enrichment sets. Within each period, EE home cages received weekly one of the three enrichment sets in a random order in such a manner that all EE animals were exposed to the 3 enrichment sets. The replacement of the enrichment items was done on a fixed day and time every week, and during this procedure all the animals were removed from the box and placed in a basket. Control animals underwent the same manipulation procedure.Social Interaction Test was performed between 118 and 130 days of age. This test is described in detail in Caliva et al (2017, Pout. Sci) including a figure with the schematic representation of the test procedure. Briefly, the SI test consists in encounters between an unfamiliar test adult male and a PC stimulus adult male, in the presence of the test bird’s female cagemate (audience). First, the test male and it’s female cagemate were placed in a central compartment separated by an opaque partition from a PC stimulus male. After 2 min, the test male and the PC stimulus male, remained in the same compartment, while the female cagemate was placed in a nearby compartment at one side of the apparatus, and used as a social audience. Immediately after, the central opaque partition was removed and the test and PC stimulus birds were allowed to interact. Direct interaction lasted a maximum of 10 min. However, if during the interaction a quail received more than 5 consecutive aggressive pecks, showed a clear and continued escaping (retrieval) behavior, and/or showed any sign of physical damage, the interaction was immediately interrupted. A video-camera was positioned 1 m above the apparatus and connected to a computer that allowed constant monitoring and recording during the test while out of the sight of the birds. Using ANY-maze the following aggressive behaviors were recorded: pecks, grabs, mounts, cloacal contacts, threats, chase, and attack with claws. Herein, when grabs, mounts or cloacal contacts were performed by one male towards another male, they were considered as aggressive behaviors. Males that performed more than 5 aggressiveness behaviors were considered aggressive (Ag), and males that did not perform any aggressive behavior towards PC opponent were considered non-aggressive (nonAg).Males exposed to the experimental apparatus without the presence of an opponent (testCON) and non-manipulated males that always remained in the home cage (Naive) with their cagemate were used as control groups.

These data contain aggregated survey responses assessing the quality and completeness of metadata for datasets deposited in public repositories and for the same datasets after professional curation.Responses were provided by 10 professional editors representing life, social and physical sciences. Each were randomly assigned four datasets to assess, half (20) of which had been curated according to the standards of Springer Nature's Research Data Support service and half (20) which had not.Curated datasets were shared privately with research participants. The versions that did not receive curation via Springer Nature's Research Data Support are openly accessible.Single-blind testing was employed; the researchers were not made aware which datasets had been curated and which had not, and it was ensured that no participant assessed the same dataset before and after curation. Responses were collected via an online survey. The relevant question and scoring is provided below:Rate the overall quality and completeness of the metadata for the dataset (with regards to finding and accessing and citing the data, not reusing the data)1 = not complete, 5 = very complete

Data to accompany paper "An exploration of the postural, location- and social contact- related sub-characteristics of inactive but awake behaviour as a depression-like indicator in mice" DOI: https://doi.org/10.1016/j.applanim.2024.106431.Data are from two experiments

The datasets contains all raw data (mother_data) and corresponding sum scores (edited_data) used for analyses in the research described in the JEG-paper by Gubbels and Colleagues. The paper addresses the cognitive, socio-emotional, and attitudinal development of gifted children participating in a pull-out program. Children spent all of their time in the regular classroom, except for the morning of the week during which they participated in the pull-out program provided by a secondary school. The program comprised three successive 1-hr classes each week: robotics, mathematics, and research and design. Three qualified secondary schoolteachers with experience in teaching gifted children taught the successive classes. A full description of the program as well as all measures is given in the Methodology file. Data are collected in a pretest-posttest control group design via group administered tests and questionnaires. The codebook describes the process of data collection. The syntax file contains syntax to recode raw data into item scores and subsequently into sum scores. In addition, all steps of data analysis that are performed in order to get to the results as described in the paper are included.

Environmental enrichment is used to increase social and physical stimulation for animals in captivity which can lead to enhanced cognition. Fundamental to the positive effect enrichment has on the brain is that it provides opportunities for captive animals to recognize and discriminate between different stimuli in the environment. In the wild, being able to discriminate between novel or familiar stimuli has implications for survival, for example finding food, hiding from predators, or even choosing a mate. The novel object recognition (NOR) test is a cognitive task that is used extensively in the rodent literature to assess object recognition and memory, where the amount of time an animal spends exploring a novel vs. familiar object is quantified. Enrichment has been shown to enhance object recognition in rodents. More recently, the use of the NOR test has been applied to another animal model, zebrafish (Danio rerio), however, the effects of enrichment have not yet been explored. In the...