Salesforce Debuts Customer 360 Data Platform


Salesforce is upping its data game with the launch of its Customer 360 platform that unifies customer data and apps in one centralized view across the cloud Inc. is upping its data game with the launch of its Customer 360 platform that aims to unify customer data and apps in one centralized view across the cloud.

The San Francisco-based provider of customer relationship management products released the new platform this week at its annual Dreamforce gathering of Salesforce customers and partners.

See also: Salesforce aims to put IoT data to work

Customer 360 promises to connect Salesforce and third-party apps while providing a customer ID that reconciles all customer data across clouds so that businesses can access the latest information on each customer.

It also increases back-end functionality by enabling admins to build customized packages for different lines of businesses without having to involve development teams or system integrators.

“Customer-facing employees lack a unified customer record because critical pieces of that profile are spread across multiple systems, creating a fragmented view of each customer,” the company said in a news release. “Traditional master data management methods used to unify customer data and plug it back into engagement applications require extensive IT resources, and are difficult to change when organizations need to deliver new personalized customer experiences quickly.”

While the idea of offering a unified customer view is not revolutionary, Salesforce says the delivery method of the data is cutting edge. Specifically, Customer 360 aims to circumvent the more cumbersome practice of creating sizeable centralized lakes of duplicate data. It achieves this by allowing data to reside in the systems that manage it, only calling upon the information when necessary.

For the 2018 fiscal year, Salesforce reported revenues of $10.5 billion from its many products including its artificial intelligence platform (AI) Einstein. The Einstein automated machine learning framework generates personalized AI predictions and models and for individual customers.


About Donal Power

Donal Power has over 20 years experience as a technical writer, reporter and editor for the Economist in Europe, on Wall Street, on Bay Street and in Asia. Subject expertise includes: AI, Smart Cities, IoT, Real Time Analytics, Fintech, Economics, Cannabis Legalization, Blockchain, Open Data, Health Technology and GovTech.

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