This data product provides a consolidated view of businesses at the granularity of individual sites (headquarters versus satellite offices, for example) that is enriched with corporate hierarchy and other referential data from several data providers. See Tamr Firmographic Enrichment for more information about supported data providers.

This data product provides:

An industry-standard schema for company data.
A machine learning model that deduplicates entities within, and across, your data sources.
Data quality services for company name, phone number, url, and address data.
Firmographic enrichment services that supplement your data with company hierarchy and other referential data.

These data products provide a view of companies that identifies, and differentiates, various business locations. In your data, companies might mean customers, suppliers, prospects, health care organizations, portfolio companies, or another type of organization.

B2B Customers Data Processing

The following diagram explains how your source records are prepared for clustering, and how Tamr creates and enriches the golden record for each B2B customer.

Source record preparation includes:

Aligning source columns to data product attributes.
Cleaning, validating, and enriching source record values.
Assigning each record a unique primary key, the tamr_record_id. This ID is a 128-bit hash value of the source dataset name and the source primary key.
Matching each source record to a Tamr Enrich ID (tamr_enrich_id). This ID is a unique, proprietary organizational identifier owned and managed by Tamr, which is used to match your source company data to referential data provided by the Tamr Enrich service and other data providers (Enigma, Pitchbook, and so on).

Source record clustering includes:

Applying the clustering model and any clustering rules to group source records that refer to the same company. (This model is described in the section below.) Each record in a given cluster is assigned the same Tamr ID. This is ID is a unique, persistent identifier that links records in a cluster with each other and with the generated golden record for that cluster.
Applying any previous cluster overrides and verifications.

Golden record creation includes:

Applying logic to select the best value for each golden record attribute, and associating a Tamr ID with the golden record.
Enriching golden records with firmographic data from selected data providers.

B2B Customers Clustering Model

By default, the B2B customers model groups records as follows. Additionally, Tamr applies any custom clustering rules you have added to for the data product when clustering source records.

First, by tamr_enrich_id, when matched based on company name and full address.

Depending on the available source data, Tamr matches companies in your source datasets to Tamr Enrich IDs based on one of the following:

Company name and full address. For this match level, address information must be available and mapped to input fields used by the enricher.
Company name and city. Tamr identied a match based on the company name, city, country, and either region or postal code.
Company name, domestic ultimate parent company, and country code. Tamr identified a match based on the company name, domestic parent company, and country code.
Registration number. Tamr identified a match based on the company's registration number.
Company name and country code. Tamr identified a match based on the company name and country code. For companies with US addresses, state is used in case of a tie. Postal code and city are further used to break ties, for all countries.
Phone number. Tamr identified a match based on the cleaned phone number.
Website. Tamr identified a match based on the cleaned website.

If a tamr_enrich_id is assigned to a source record based on the company name and full address (tamr_firmographic_match_status is MATCH_NAME_ADDRESS), then records with matching tamr_enrich_id values are clustered together and records with different tamr_enrich_id values are not clustered together.

Then, by similarity.

Records with tamr_enrich_ids in which the tamr_firmographic_match_status is MATCH_NAME_CITY, MATCH_NAME_COUNTRY, MATCH_PHONE, or MATCH_WEBSITE may be clustered with records that have a different (or null) tamr_enrich_id based on similarities between these attribute fields:

Company name
Alternate company names
Full address and address components
Phone number
Website

The model considers similarities in these values, not exact matches. For example, two addresses on the same street may correspond to the same company site.

Data Quality Services

This data product includes data quality services for the following values:

These services supplement your source data with standardized, validated values for these essential attributes. They examine values for these attributes, and add any resulting validated, standardized values to each record in new enrichment-specific attributes. The original values mapped from your source datasets remain present and unchanged. They also help identify additional communication channels, including which phone numbers can receive text messages. With reliable, up-to-date information, your organization’s representatives can more efficiently and effectively work on their accounts.

See the topics linked above for processing details and added attributes.

Firmographic Enrichment

The B2B customers data product includes Tamr firmographic enrichment services that enrich your data with corporate hierarchy and other referential data providers. These providers include Public Sources, Pitchbook, Companies House, and so on. To help you validate the accuracy of firmographic enrichment, Tamr provides similarity scores between key attribute values in the mastered entity and the corresponding values returned by your selected data provider. For example, Tamr calculates the similarity between the company name in the mastered entity and the company name returned by the data provider. See Tamr Firmographic Enrichment for more information about supported data providers. Firmographic enrichment can help solve problems such as:

Missing corporate hierarchy information.
Out-of-date information, such as company names that have changed due to acquisition.
Missing details about an organization, such as number of employees, revenue, SIC codes, national identifier, and so on.
Misidentifying different companies that reside in the same building as the same company.

Using this Data Product

To learn more about this data product's requirements, configuration, and resulting mastered entities, see: