I recently had an opportunity to witness the latest online webinar on “Mastering Salesforce Data Cloud” hosted by London Research in partnership with EPAM & Salesforce. Keynote speakers of the session were: Raz Embleton, Director @EPAM Systems; James Bishop, VP Data Cloud @Salesforce and Linus Gregoriardis, Director and Co-Founder @London Research.

This webinar provides us with a glimpse of the AI foundational aspect of the Salesforce Data Cloud. Salesforce Data Cloud is a hyperscale data platform that enables users to unify customer data from multiple channels into a single location. The data cloud has evolved from a customer data platform into an activation software with advanced AI-based capabilities enhancing cross-functional journeys across sales, service, marketing, and commerce. The Data Cloud is designed to solve the contingencies in the proliferation of data which is in bulk amounts possibly in terabytes. Its processing power is expected to double in the coming years. The management of these doubling number of sets would be rather complex because these data sets are trapped inside siloed systems leading to customer data being scattered. These data sets are primarily found in mainframes, financial systems, website applications, and more. These sets are in various formats and could be structured like CRM or transactional data and unstructured like text files, emails, or social media. However, 90% of these are in unstructured formats and this poses a significant challenge which is attributed to poor data targeting and segmentation approach, most of it being around AI. So, the AI is only as good as the data that is fed and as a consequence, organizations are starting to build complex ecosystems for centralizing and harmonizing these data types. The Data Cloud assorts these types in real time by enabling batch and streaming ingestion from customer-facing and backend systems. The platform then uses matching and reconciliation to look for relevant accounts or individuals using identifiers that can be connected to create unified profiles.

The webinar further talks about customers planning to move their contact centres from cost to revenue centres by reducing call handling times and turning inquiries into sales opportunities with AI-generated next-best-action offers. The platform corroborates the proactive service to telemetry use case and identifies when a problem may occur by triggering a communication to a customer regarding a call or service. On moving ahead, the representative from EPAM Systems cited an example on “Lookers Group”, United Kingdom’s largest car dealership, and how the company moved towards a multi-cloud system comprising of commerce cloud, service cloud, marketing cloud, and data cloud. Particularly using the data cloud, the company was able to gain a connected 360-degree view of customers across multiple dealerships. The company presumed it had about 7 million customers across its dealership network but when the identity resolution rule was set using the data cloud platform, the customer count came out to be 1.7 million which shows how accurate the data cloud’s identity resolution capability is.

Finally, the speakers of the webinar mentioned their latest release called Hyperforce which is Salesforce’s public cloud infrastructure capable of delivering any applications developed worldwide. They talked about their new di Digital Wallet which assists consumers in tracking consumption and making revenue decisions. They spoke of their new Zero Copy ETL Data Net which has been developed after working with major players like AWS Databricks, Microsoft Azure, Google Big Query, and Snowflake such that their data could be uploaded into Salesforce Data Cloud seamlessly.

According to Manakh Phukon analyst at QKS Group, “Salesforce Data Cloud represents a significant advancement in how organizations manage and utilize customer data across multiple functions and channels. The platform’s ability to unify structured and unstructured data in real-time addresses one of the most critical challenges businesses face today: fragmented customer insights due to siloed data systems. By enabling AI-driven capabilities, Data Cloud facilitates more personalized customer engagement and operational efficiency, especially in sectors like sales, service, and marketing.”

Author: Manakh Phukon, Analyst, Analytics and Artificial Intelligence at QKS Group