The Structured Data Joiner ensures that any structured data, which typically includes important identifying and transactional information, is correlated with the feedback written by the customer. An email address from a web form, for example, may identify the individual providing feedback as a gold-level customer. Transactional data from data warehouses, which are typically analyzed in isolation, provide a partial glimpse of customer needs and requirements. When this data is understood and analyzed alongside customer feedback data it provides business insights that enables organizations to better serve customers, control cost and risk, and identify opportunities for increased efficiency. Clarabridge integrates structured data throughout the customer intelligence transformation process to ensure businesses get a universal view of their customer. The platform then automatically creates and maintains dimensional lookup and cross-reference tables for structured data elements.
Automatically Integrate Structured Attributes for Better Reporting
The binding of unstructured + structured data enables the slicing and dicing of data, definition of categories and other analysis in the context of attributes such as age, gender, location, etc. Clarabridge offers multiple wizard-based options for business users to control how structured attributes is correlated with unstructured data - create attributes, enable/disable attributes for reporting, define attribute types and perform attribute mapping. These structured attributes are then made available for downstream reporting with multiple options to analyze customer insights using structured data dimensions.
