More organizations putting focus on customer data integration
Of all the data management tasks organizations face today, ensuring effective customer data integration is among the most important.
“Customer experience is a growing area of focus for many organizations,” said Stewart Bond, research director, data integration software, at International Data Corp. (IDC). “Data about customers is at the heart of providing better experiences in every engagement with the customer, regardless of how, where, and when the engagement occurs.”
Increasingly, organizations are using graph database technology to provide the necessary relationship mapping, combined with master data management, data federation, and artificial intelligence to automate the customer data discovery process, Bond said.
Companies that don’t have the most recent “version of truth” for customer master data, transactions, relationships and interactions will fail in customer experience and engagement, Bond said. A bad customer experience might not only result in losing that customer, but losing additional customers who hear about the experience on social media.
Customer data isn’t just about what’s in a customer relationship management (CRM) or enterprise resource planning (ERP) system, or even what’s in a master data management system, Bond said. Getting a 360-degree view of customers also involves data from transactions, engagement with call centers, Web inquiry logs, chatbot sessions, and other sources.
“Capturing all of this data and information requires integration capabilities across multiple disparate data sources, big data repositories, streaming data sources—and ultimately the capability to make sense of all of it as it relates to customers,” Bond said.
With security and privacy being such big concerns today, companies need to make sure customer data is protected at all times.
“Knowledge about where customer data is, what is in it, who has access to it, how and why it is being used—informed by data intelligence—is critical not only for integrating data but also for protecting it,” Bond said. “Data intelligence software such as data discovery, cataloging, profiling, mastering, and lineage management is being used to inform data governance processes and implementation of policies to help mitigate security and privacy risks.”