Best B2B Identity Graph Datasets, Databases & APIs

What is B2B Identity Graph Data?

B2B identity graph data is information about key officials at a prospective client business. This information includes email address, geographical location, contact details, device IDs, business IDs, and account username. This data is used to identify the contact details and personal information of the key players at target businesses.   

How is B2B Identity Graph Data collected?

B2B identity graph data is collected through different sources. These sources include company websites, social media platforms, and business registration authorities. Data providers collect, organize, and analyze this information and create accurate graphs and datasets by cleaning and removing duplicates and unnecessary information, such as outdated email addresses and ex-directory numbers.

What are the typical attributes of B2B Identity Graph Data?

B2B identity graph data consists of these typical attributes:

• Business name and location: this refers to the business’s physical geographical location and its registered name. This also includes the employees and key officials of the business.
• Contact details: this refers to the personal and professional contact details of the business and employees.
• Type of business: this refers to the type of business, what they offer, the nature of the business, financial records, and other related information about the business.

What is B2B Identity Graph Data used for?

B2B identity graph data is used by B2B marketers and sales teams at businesses. This data is used to identify new prospect businesses. For a business to thrive in the market, B2B identity graph can be used as a tool to contact and build rapport among businesses. B2B identity graph data also helps eliminate wasted time and resources in gathering this data independently. B2B identity graph data also helps verify and validate the business’ identity and credibility.

How can a user assess the quality of B2B Identity Graph Data?

In assessing the quality of B2B identity graph data, users should consider the following quality aspects:

• Credible: this refers to how the gathered information performs when it’s verified and validated against other sources.
• Accurate: for B2B identity graph data to be considered high-quality, data must be free from error and updated regularly. Users must identify how the data was processed and cleaned.
• Accessible: the data must be accessible at all times without compromising PII.
• Complete: all the data included in the B2B identity graph data must be complete and consistent. The data must be organized according to categories and types.

Where can I buy B2B Identity Graph Data?

Data providers and vendors listed on Datarade sell B2B Identity Graph Data products and samples. Popular B2B Identity Graph Data products and datasets available on our platform are OMI’s USA B2B Targeted Audiences with Digital ID for Display Advertising by Outwardmedia, Anteriad - B2B Onboarding Graph USA - Company Professionals matched to MAID by Anteriad, and True Influence Marketing Cloud | B2B Intent & Contact Data USA (7M Contacts with Intent, 30M Companies) by True Influence.

How can I get B2B Identity Graph Data?

You can get B2B Identity Graph Data via a range of delivery methods - the right one for you depends on your use case. For example, historical B2B Identity Graph Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time B2B Identity Graph Data APIs, feeds and streams to download the most up-to-date intelligence.

What are similar data types to B2B Identity Graph Data?

B2B Identity Graph Data is similar to Device Graph Data and Consumer Identity Graph Data. These data categories are commonly used for Account-Based Marketing (ABM) and Identity Resolution.

What are the most common use cases for B2B Identity Graph Data?

The top use cases for B2B Identity Graph Data are Account-Based Marketing (ABM), Identity Resolution, and Data Onboarding.