Table of Contents

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  1. Preface
  2. Introduction to Informatica Cloud Customer 360
  3. Configuring the Data Cleansing Settings
  4. Managing Batch Jobs
  5. Verifying Addresses, Email Addresses, and Phone Numbers
  6. Synchronizing Salesforce Records with CC360
  7. Managing Duplicate Records
  8. Consolidating Records
  9. Converting External Records to Salesforce Records
  10. Managing Hierarchies
  11. Integrating Cloud Customer 360 with MDM Multidomain Edition
  12. Managing Multi-Org
  13. Custom Settings
  14. Glossary

Legal Form Normalization

Legal form normalization is the process of extracting the legal form from the company norm and populating the legal form field with normalized data.
Extract the legal form from the company name to improve matching performance. When you enable legal form normalization,
CC360
identifies the legal form in a company name and then populates a normalized legal form in a separate field from the company norm field. By default,
CC360
combines the country ISO code and the country norm to create a fuzzy matching segment in the master bean. To optimize matching results, eliminate the legal form from the fuzzy matching segment.
For example, a user might enter company name information in any of the following ways:
  • Acme Limited
  • Acme Ltd.
  • Acme L.T.D.
If a user enters any of these names in the company name field,
CC360
can populate the company norm field with Acme and populate the legal form field with LTD.
CC360
uses the company norm field when it creates the fuzzy matching segment.
When you extract the legal form from the company norm field,
CC360
eliminates nonunique character strings from the fuzzy matching segment, which improves match performance.
For example, if an organization has many customers with frequently occurring elements in the company names such as ABC Plumbing and Acme Plumbing. If you do not specify a legal form,
CC360
creates the fuzzy matching segments as USABCPLUMBING and USACMEPLUMBING. If you add Plumbing to the legal form settings,
CC360
creates the fuzzy matching segments as USABC and USACME. Fuzzy matching performance improves because the character strings in the fuzzy matching segments are more unique and distinct.

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