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.

CTV Identity Graph Market Outlook

According to our latest research, the global CTV Identity Graph market size is valued at USD 1.9 billion in 2024, with a robust compound annual growth rate (CAGR) of 18.7% expected from 2025 to 2033. By the end of 2033, the market is forecasted to reach approximately USD 10.6 billion. This significant growth is primarily driven by the escalating demand for precise audience targeting and cross-device measurement in the rapidly expanding connected TV (CTV) ecosystem, as brands and agencies strive for better personalization and attribution across digital advertising channels.

One of the primary growth factors for the CTV Identity Graph market is the exponential rise in CTV viewership globally, which has fundamentally transformed the digital advertising landscape. As more consumers migrate from traditional linear television to streaming platforms, advertisers are increasingly challenged to accurately identify and target fragmented audiences across multiple devices. CTV identity graphs have emerged as a critical solution, enabling advertisers to unify disparate data points and establish persistent, privacy-compliant user identities. This empowers brands to deliver personalized ad experiences, optimize campaign performance, and maximize return on ad spend (ROAS) in an environment where third-party cookies are rapidly being deprecated. The proliferation of smart TVs, OTT devices, and streaming services is fueling the integration of identity graphs, making them indispensable for any data-driven advertising strategy.

Furthermore, the growing complexity of the programmatic advertising ecosystem is propelling the adoption of CTV identity graphs. With the convergence of linear TV, digital video, and mobile platforms, advertisers face the challenge of measuring reach and frequency across devices and platforms. CTV identity graphs enable advanced measurement and analytics by resolving user identities in real-time, providing advertisers and publishers with holistic insights into audience behavior. This capability is particularly crucial for accurate attribution, as brands demand transparency and granularity in understanding which touchpoints drive conversions. The increasing emphasis on measurable outcomes and data-driven decision-making in the advertising industry is expected to sustain the high growth trajectory of the CTV identity graph market.

Another key driver is the heightened focus on privacy and data security in the digital advertising ecosystem. With stringent regulations such as GDPR and CCPA, along with growing consumer awareness about data usage, advertisers and publishers are under pressure to adopt privacy-centric solutions. CTV identity graphs are evolving to incorporate privacy-by-design principles, leveraging anonymized and consented data to build accurate audience profiles without compromising user privacy. Innovations in data encryption, differential privacy, and secure data collaboration are enhancing trust among consumers, regulators, and industry stakeholders. This alignment with regulatory requirements is not only facilitating market growth but also fostering long-term sustainability and acceptance of identity graph solutions in the CTV landscape.

From a regional perspective, North America continues to dominate the CTV Identity Graph market, accounting for over 42% of global revenue in 2024. The region’s leadership is attributed to the high penetration of connected TV devices, mature digital advertising infrastructure, and early adoption of advanced identity resolution technologies. Europe is witnessing accelerated growth, driven by expanding OTT consumption and increasing regulatory compliance. Meanwhile, Asia Pacific is emerging as a lucrative market, supported by rapid digitalization, rising disposable incomes, and growing investments in programmatic advertising. Latin America and the Middle East & Africa are expected to witness steady growth, albeit from a smaller base, as internet connectivity and streaming adoption continue to rise. The global outlook remains highly promising, with technological advancements and evolving consumer behaviors shaping the future trajectory of the CTV identity graph market.

Component Analysis

The CTV Identity Graph market is segmented by component into software and services, each playing a pivotal role in the ecosystem’s growth and adoption. The software segment, which comprises identity resolution plat

Thank you for checking the code, data, and the execution history.

This Zenodo repository corresponds to our publication at the ESWC'23 conference.

1) There are three kinds of sources in the directory ./sources

2) The scripts corresponding to the algorithm are in the ./algorithm directory

3) The gold standard is in the directory ./gold_standard together with additional information of each connected component (as a file on its own) including error degree of the edges. The annotation of volunteers is in the *.tsv file.

4) Some scripts for analysis, for extraction/processing of data, and plotting are included in the ./other_scripts directory.

5) The ./execution_history directory consists of all the log files during evaluation. The summaries are in *.log.

Please see each directory for detailed description in PDF or txt.

The latest version of the code is online at https://github.com/shuaiwangvu/sameAs-iUNA

In case of any mistake to report, please contact Shuai Wang at shuai.wang@vu.nl.

Andrew Wharton's US Consumer Email Databases provide over 650 million current and active email address records in our 36-month Production Email Database, and additionally, over 1.4 billion historical records in our Legacy Email Database. These databases offer a comprehensive look-back at the digital and terrestrial identity information associated with a consumer. This Identity Graph Data has been collected from website registrations and is 100% opted-in for Third Party Uses.

The Email Address Data is fully populated with email addresses, HEMS (MD5, Sha1, Sha256), first name, last name, postal address (primary and secondary), IP Address, and Time Stamps for Last Registration, Verification, and First Seen. Additionally, our email address information assets can be linked with our Date-of-Birth and Phone Number databases to provide a powerful solution for consumer identity recognition and verification platforms through Identity Linkage Data.

As an add-on to our current and historical information, we also offer a database of hard-bounce email addresses. These are email addresses that have hard-bounced during our large-scale email campaign deployments or were identified as hard-bounces during our email verification processes. This database provides over 400 million unproductive email addresses useable as a part of suppression or fraud identification applications.

Our Email Information Assets are utilized by major Identity Graph Data and Identity Linkage platforms due to our comprehensive information that links the email address to consumer identity and IP Address information. This Identity Graph Data provides a robust alternative approach when faced with third-party cookie deprecation in the digital ecosystem.

Our digital advertising partners leverage this information to understand where their clients' customers and prospects are online and align media and content with consumer behavior. The additional Email Address Data, mobile phone numbers, and IP Addresses also work to increase the reach of your Digital Audience Data.

This Identity Graph Data has the scale and depth to help drive the creation of new platforms and products and provide significant enhancements to existing platforms. By utilizing our extensive Email Address Data and Identity Linkage Data, you can ensure precise consumer identity recognition and verification, making your marketing campaigns more effective and far-reaching.

Contact us at successdelivered@andrewswharton.com or visit us at www.andrewswharton.com to learn more about how our Identity Graph Data, Email Address Data, Identity Linkage Data, and Digital Audience Data can meet your marketing needs.

CTV Identity Graph Market Outlook

According to our latest research, the global CTV Identity Graph market size reached USD 1.47 billion in 2024 and is anticipated to grow at a robust CAGR of 17.6% from 2025 to 2033, reaching a projected market size of USD 6.01 billion by 2033. This impressive growth trajectory is largely fueled by the surging adoption of connected TV (CTV) platforms, the imperative for cross-device audience targeting, and the escalating demand for advanced measurement and attribution capabilities. The proliferation of digital advertising and the shift toward data-driven marketing strategies are further amplifying the necessity for sophisticated identity graph solutions in the CTV ecosystem.

A key growth factor for the CTV Identity Graph market is the exponential rise in digital content consumption via connected TV devices, which has fundamentally transformed the advertising landscape. As consumers increasingly migrate from traditional linear television to streaming platforms, advertisers are compelled to adopt identity graph technologies to maintain accurate user profiles across multiple devices and channels. This shift not only enhances audience targeting precision but also enables advertisers to deliver personalized content, substantially improving campaign effectiveness and return on investment. Moreover, the fragmentation of media consumption habits necessitates a unified approach to identity resolution, driving widespread adoption of CTV identity graph solutions among brands and agencies.

In addition, the growing complexity of the digital advertising ecosystem has underscored the need for transparent and reliable measurement frameworks. CTV identity graphs play a pivotal role in bridging data silos and enabling comprehensive analytics across disparate platforms. By integrating first-party, second-party, and third-party data sources, these solutions empower advertisers and publishers to attain a holistic view of audience behavior, facilitating more accurate measurement, robust attribution models, and granular reporting. This capability is particularly crucial in a privacy-conscious era, where regulatory compliance and consumer trust are paramount. As such, the demand for CTV identity graph platforms is expected to accelerate, driven by the dual imperatives of data-driven marketing and regulatory adherence.

Furthermore, advancements in artificial intelligence and machine learning are propelling the sophistication of CTV identity graph solutions, enabling real-time data processing and enhanced fraud detection. The integration of AI-driven algorithms allows for dynamic audience segmentation, predictive analytics, and automated anomaly detection, which collectively contribute to improved campaign performance and reduced ad fraud. As the industry continues to evolve, the convergence of AI and identity graph technology is set to unlock new opportunities for innovation, operational efficiency, and competitive differentiation. This technological evolution, coupled with the increasing availability of high-quality data, is expected to sustain the market's upward momentum over the forecast period.

From a regional perspective, North America remains the dominant force in the CTV Identity Graph market, accounting for the largest share of global revenue in 2024. This leadership position is underpinned by the region's advanced digital infrastructure, high penetration of connected TV devices, and a mature advertising ecosystem. Europe and Asia Pacific are also witnessing significant growth, driven by rising investments in digital advertising and the rapid expansion of OTT platforms. Latin America and the Middle East & Africa, while representing smaller market shares, are expected to exhibit strong growth rates owing to increasing internet penetration and the gradual adoption of CTV technologies. Overall, the global landscape is characterized by dynamic regional trends, with each market presenting unique opportunities and challenges for stakeholders.

Component Analysis

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Redmob's Identity Graph Data helps you bring fragmented user data into one unified view. Built in-house and refreshed weekly, the mobile identity graph connects online and offline identifiers.

Designed for adtech platforms, brands, CRM, and CDP owners, Redmob enables cross-device audience tracking, deterministic identity resolution, and more precise attribution modeling across digital touchpoints.

Use cases

The Redmob Identity Graph is a mobile-centric database of linked identifiers that enables:

• Cross-device matching to connect mobile, web, and offline behaviors
• Enrich your CRM and CDP with stable IDs to improve marketing automation
• Match mobile device IDs to emails, cookies, and offline data
• Create lasting user profiles by connecting data from different channels
• Enrich customer data for better segmentation and engagement

Key benefits:

• Connects users across devices with Redmob's in-house identity graph
• Weekly updates keep audience profiles fresh and accurate
• Links offline and online data to complete the user picture
• Built for adtech with reliable, high-accuracy matches

This is the dataset for our paper

What does it mean when your URIs are redirected? Examining identity and redirection in the LOD cloud

Redirection of URIs is widely used in the LOD cloud, and is even part of the best practice guidelines as an approach to the ``curation problem'' on the semantic web (i.e. how to repair imperfections). When dereferencing, one URI is redirected to another URI. Such a redirection could be the result of an update of the namespace, a different encoding scheme, or some other reasons. In this paper, we study the semantics of redirection and examine if redirection indicates how entities in the LOD cloud evolve. More specifically, we focus on entities in the identity graphs: subgraphs in the semantic web restricted to identity links. The entities we study are from sameAs.cc, an identity graph extracted from a crawl of the semantic web in 2015. Our analytical results include an examination of edges and chains of redirection as well as a statistical analysis of the redirection behavior of sampled entities. Additionally, we present properties of the graphs formed by redirection relations.

The dataset contains the redirect relations of four sets of sampled entities. These sampled files are:

• ite_uniform... the edges of redirection graph corresponding to uniform samplings
• cc_sample_2... the sampling regarding connected components of size 2, 3-10, 10+, respectively.

The Python scripts are open source online at:

https://github.com/shuaiwangvu/redirection

The paper is attached. In case of any questions, please contact Shuai Wang at shuai.wang@vu.nl.

Identity Resolution Market Outlook

The global identity resolution market size was valued at approximately USD 1.5 billion in 2023 and is projected to reach a valuation of around USD 5.8 billion by 2032, growing at a CAGR of 16.2% during the forecast period from 2024 to 2032. This remarkable growth is primarily driven by the increasing need for organizations to accurately identify and understand their customers, thereby enhancing marketing efficiency and reducing fraud.

One of the significant growth factors for the identity resolution market is the exponential increase in digital interactions. With the proliferation of digital channels such as social media, e-commerce platforms, and mobile applications, organizations face the challenge of integrating diverse data points to create a unified customer profile. Identity resolution technology enables businesses to overcome this challenge by linking disparate data sources, thereby providing a holistic view of the customer. This capability is particularly crucial in enhancing targeted marketing campaigns, improving customer engagement, and boosting overall business performance.

Another critical driver is the rising incidences of fraud and cyber threats. As digital transactions surge, the risk of identity theft and fraud also escalates. Businesses are increasingly adopting identity resolution solutions to detect and prevent fraudulent activities in real-time. These solutions employ advanced algorithms and machine learning techniques to analyze data patterns and identify anomalies. By doing so, businesses can protect themselves and their customers from potential fraud, thereby safeguarding their reputation and financial stability.

The push for regulatory compliance also fuels the demand for identity resolution solutions. Various regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), mandate organizations to manage and protect personal data effectively. Identity resolution tools help organizations comply with these regulations by ensuring data accuracy and consistency across different systems and applications. This not only mitigates the risk of non-compliance penalties but also enhances customer trust and loyalty.

Regionally, North America is expected to hold the largest market share in the identity resolution market during the forecast period. This dominance is attributed to the early adoption of advanced technologies, a high concentration of market players, and stringent data privacy regulations. Moreover, the growing focus on customer experience management and security concerns are driving the adoption of identity resolution solutions in the region. The Asia Pacific region is also anticipated to witness significant growth, driven by the rapid digital transformation, increasing internet penetration, and rising awareness about data privacy and security.

Component Analysis

The identity resolution market is segmented by component into software and services. The software segment encompasses various tools and platforms designed to integrate and reconcile different data points to form a unified customer identity. This segment is expected to hold a significant share of the market due to the increasing reliance on advanced analytics and machine learning algorithms to process large volumes of data. These software solutions are pivotal in ensuring data accuracy and consistency, thereby enabling businesses to derive actionable insights from their data.

Within the software segment, various types of solutions are available, including customer data platforms (CDPs), data management platforms (DMPs), and identity graph technologies. CDPs and DMPs are particularly popular due to their ability to aggregate data from multiple sources, allowing for real-time customer identity resolution. Identity graph technologies, on the other hand, focus on mapping relationships between different data points, thereby enhancing the accuracy of customer profiles. The continuous innovation in these software solutions is expected to drive the growth of the software segment.

The services segment includes consulting, implementation, and support services offered by various vendors to help organizations deploy and maintain identity resolution solutions. Consulting services are vital in assessing an organization's current data landscape and identifying the best strategies for implementing identity resolution technologies. Implementation services ensure the seamless integration of these solutions into existing systems, while support services provide ongoing m

DRAKO's Device Graph Data provides a comprehensive view of consumer identities across various devices, enabling businesses to gain deeper insights into audience behaviours. Leverage our extensive Device Graph, which includes: Identity Graph Data, Connected TV Data, and Mobile Attribution Data.

Over 3.3B MAID-MD5/SHA256 identity linkages. Over 200M monthly uniques.
Proprietary ID Check technology to maximize quality by eliminating invalid and inactive IDs. Real-Time API or Batch Processing available.

Our graph consists of contact information including names, postal addresses, Placekey IDs, raw and hashed email addresses, phone numbers, and Mobile Ad IDs (MAIDs). We connect data fragments of an individual to build a whole-person picture. This includes both personal and professional identities and hundreds of marketing attributes about a person which can be queried by the graph to identify the individual person from the billions of people in the Identity Graph.

Our identity dataset allows businesses to submit their customer IDs, which our platform matches to identities across various platforms and devices. This process opens up new communication channels by using multiple data points to determine or probabilistically match users to their corresponding identities.

Identity Data Reach

Our dataset links device data to hashed email data from first-party data owners. Leveraging our identity graph, we connect IP addresses, device IDs, and other platform identities, enabling more comprehensive communication channels.

• Record Count: 500 Million+
• Updated: Monthly
• Historical Data: Past 6 Months

Data Export Methodology

We dynamically collect and update data, providing the latest insights through Data Clean Rooms. This method ensures privacy compliance while enriching your data according to your specific requirements.

Use Cases

Our identity dataset is crucial for identity resolution and data enrichment, empowering businesses to enhance their customer data and expand their reach across multiple platforms and devices.

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

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

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

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

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

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

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

We release 280 synthetic IAM graphs generated using IAM graphs of commercial companies. Specifically, we vary the number of nodes, but keep graph density as is, i.e. in the range of 0.259 ± 0.198 (avg ± std). To generate a synthetic graph, we first sample the number of users and datastores from uniform distributions over the following intervals [10, 150] and [50, 300] respectively that cover variations of those parameters across real graphs. After fixing node counts we sample with replacement the actual nodes from a real world graph, which is chosen at random. Then we add Gaussian N(0, 0.01) noise to node embeddings and renormalize them. To match the graph density with the density of the underlying baseline we sample edges from a multinomial distribution, where each component is proportional to the cosine distance between a user and a datastore embeddings. Also we enforce the invariant that dynamic edges are always a subset of all permission edges. A synthetic graph generated in such a way is an ”upsampled” version of an underlying real world graph.

Redmob's Identity Graph Data helps you bring fragmented user data into one unified view. Built in-house and refreshed weekly, the mobile identity graph connects online and offline identifiers.

Designed for adtech platforms, brands, CRM, and CDP owners, Redmob enables cross-device audience tracking, deterministic identity resolution, and more precise attribution modeling across digital touchpoints.

Use cases

The Redmob Identity Graph is a mobile-centric database of linked identifiers that enables:

• Cross-device matching to connect mobile, web, and offline behaviors
• Enrich your CRM and CDP with stable IDs to improve marketing automation
• Match mobile device IDs to emails, cookies, and offline data
• Create lasting user profiles by connecting data from different channels
• Enrich customer data for better segmentation and engagement

Key benefits:

• Connects users across devices with Redmob's in-house identity graph
• Weekly updates keep audience profiles fresh and accurate
• Links offline and online data to complete the user picture
• Built for adtech with reliable, high-accuracy matches

Unacast’s Identity Data Linkages is a privacy-compliant identity resolution solution that helps companies bridge fragmented user identities across mobile, desktop, and connected TV (CTV) environments.

Identity Data Linkages includes: -MAID to HEM linkage: maps MAIDs to associated hashed email addresses - MAID to FLIP linkage: maps MAIDs to the IPs associated with the Frequented Locations of that MAID

These deterministic linkages provide the foundation for accurate cross-device tracking, allowing advertisers and platforms to unify consumer behavior across channels and create more coherent audience profiles for either an identity graph or device graph.

Data Linkages supports key use cases like identity graph enrichment, device graph enrichment, cross-device targeting, audience personalization, measurement, and fraud prevention.

Unacast's data products are GDPR and CCPA compliant.

Delivery: S3, Azure, or Google Cloud Bucket Format: CSV, PSV, Parquet Frequency: Bi-weekly or monthly / historical

Different variables can impact pricing. Please reach out to further discuss your use case and pricing.

Our groundbreaking real-time, cookieless Identity Graph is constructed using identity linkage data, consumer marketing data, demographic data, audience data, prospect data, and more.

From connecting CTV viewership data across devices to knowing where and how to communicate your message best, OMNA provides everything you could ever want to know about your audiences for consumer marketing.

How clients benefit from our identity linkage data, consumer marketing data, demographic data, audience data, and prospect data:

1. Instantaneous Campaign Feedback: Fast turnaround and operational cost savings due to no attrition moving from vendor to vendor.

2. Verifiable Results: Increase Conversions, Return on ad spend (ROAS), and Return on Investment (ROI) via closed-loop campaign.

3. Expansive Data Insights: Stirista’s data assets including identity linkage data, consumer marketing data, demographic data, audience data, prospect data,
   interests, etc. - are fueled by our in-house Email Sending Platform (ESP) and Demand Side Platform (DSP). This enables unlimited segmentation.

Keep up with your audiences as they move across devices throughout the day and improve your campaign performances with quality identity linkage data, consumer marketing data, demographic data, audience data, and prospect data.

Observed linkages between emails and mobile advertising identifiers (MAIDs) from website and device activity.

Business-to-Business marketers are looking to simplify data work-flows and increase data portability across their technology stacks. Developed off 180byTwo’s AccountLink™ B2B graph, AI, and DAAS solutions; Unifi enables B2B and Account-Based Marketers to seamlessly execute and measure marketing programs.

Create a new audience that mirrors your ideal customers for sales and marketing initiatives. With Versium REACH, you have access to 80+ demographic data filters which allow you to create highly targeted audiences for direct mail, email, phone, digital or multichannel marketing campaigns. With Versium REACH you are connected to our proprietary database of over 300+ million consumers, 1 Billion emails, and over 150 million households in the United States.