Genie is a step beyond the Salesforce CDP

Genie represents a rethinking of Salesforce’s approach to customer data.



Salesforce’s key announcement at this year’s Dreamforce was a new data platform solution, Genie.


Genie is the latest stage in Salesforce’s multi-year customer data journey. It launched a CDP, to be known as 360 Audiences in 2020. In early 2021, the name was withdrawn in favor of the simple Salesforce CDP. Now Salesforce is dreaming of Genie.


Getting clearer on Genie. When we reported this news last month, we did say:



In terms of what is announced here, the distinction between Salesforce CDP and Genie is not immediately clear, although Genie is implied to be larger in scale and faster.

“At Dreamforce, a new data platform and enhancements to Slack” September 21, 2022

Since then we’ve learnt more about the offering, in part through a conversation with Rahul Auradkar, EVP and GM, Unified Data Services and Einstein at Salesforce.


One thing Auradkar made clear is that Genie is neither separate from nor a simple addition to Salesforce CDP. It is, rather, a rethinking of the CDP and its capabilities.


Back in 2020, Chris O’Hara, then Salesforce’s VP of product marketing, spoke of integrating Salesforce CDP with the sales and service clouds as well as the marketing cloud. It now seems this never really happened; the aim is that Genie will finally bring this about.


Structural change. What Genie represents might be described as a structural change to the way customer data is handled within Salesforce. As is well known, the Salesforce platform was constructed in large part through acquisitions, leading to customer data being siloed in various applications. Genie now constitutes an active common layer supporting (at least) the main applications — CRM, marketing and service — and making consistent customer data available to all of them (at great scale and speed, Salesforce says).


In simple terms, Genie supports engagement and experience at the app level by providing:



  • Real-time decisioning.
  • Event processing.
  • Machine learning.
  • Analytics.

(This according to a demonstration by Auradkar.) Through identity resolution, a single view of the customer, across applications, will be available for decisioning, processing, ML and analytics.


Why we care. The CDP race between Adobe’s Real-Time CDP, Oracle Unity and Salesforce’s offering under various names and guises, is not over. It’s important to get as clear as possible on what these major CX platforms are offering when it comes to wrangling customer data consistently across what have been essentially disparate systems.


It’s even more important as we watch the CDP space itself grow more disparate, now encompassing independent enterprise CDPs, CDPs that execute on data held outside the CDP (e.g. in a data lake), and CDPs that are packaged with broader e-commerce, CMS and digital experience offerings. And all shades in between.






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About The Author










Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space. He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020. Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.

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