Salesforce Positions Customer Data as a Center of Digital Gravity

January 24, 2020

Joining Salesforce in San Francisco for its giant (some 170,000 registrants) annual user event, Dreamforce, afforded the opportunity to learn about and discuss the vendor’s latest product announcements, customer stories, and plans for the future. 

As an industry, we talk often and voraciously about digital transformation—a journey that for many enterprises is underway, with the transition to the cloud a major component. (I argue this journey is a never-ending one.)

Salesforce’s position as a major player in enabling this journey was the key focus and takeaway from Dreamforce 2019, with product announcements that help organizations connect their substantial technology investments and create a more integrated digital experience. An experience whose center of gravity is found in the customer dataconnected by Salesforce and its Mulesoft acquisition, and supported with a growing array of AI and analytical insights, bolstered by the recent acquisition of Tableau.

The journey from systems of record to intelligence and truth

The evolution of enterprise IT was given more than a brief nod during the opening keynote at Dreamforce; as Salesforce put it, “the fourth wave of computing.” 

And the journey is a long and impressive one: from the early days of systems of records, through systems of engagement, to today and what Salesforce called systems of intelligence—and onward to truth (more on that later). 

This description is key to many of the strategic moves that Salesforce has made and is continuing to make. Two in particular stand out: the 2018 acquisition of MuleSoft and the recent 2019 acquisition of Tableau. MuleSoft and Tableau are being handled carefully by Salesforce, and with good reason: They derive considerable value from being independent, allowing them to work with the broadest range of software and data sources.

Connecting data and applications with MuleSoft, and analyzing and visualizing it with Tableau, are two of the keys to Salesforce’s Customer 360 announcements made at Dreamforce. (That is not to ignore the integrations and analysis capabilities that Salesforce has developed in house.) Yes, Customer 360 is a term that has been around as long as I have been writing about data, but something has changed. The growth in data about customers (volume of interactions, social, channels, and so on) has exploded, and the ability to connect and use it from a technical perspective has become easier and more accessible.

Connect the dots to see the full picture

The effort and investments made in digital transformation have most frequently focused on the front end; that is, the web presence, apps, and other channels through which a business interacts with its customers. But as the name suggests, a transformation must extend throughout the organization’s (often vast) landscape of systems that help create, transact, and deliver the products and services those channels promise. 

A key piece of information that can help connect these systems (and the processes that run across them) is a single customer identifier. Enter Salesforce Customer 360 Truth.

Announced at Dreamforce, Customer 360 Truth connects data across sales, service, marketing, commerce, and beyond to deliver a universal Salesforce Customer ID. While it may sound like the kind of information a business should have already, the complexity of creating—and maintaining—a single customer ID has proven a significant challenge. At the same time, its benefits are obvious and can rapidly return value.

For example, a salesperson may have a customer whose contract is up for renewal; that same customer may also be frustrated by an outstanding service request, potentially impacting that renewal. Without a single ID to unify the sales and service data, the salesperson will not be aware of the service matter (and cannot help resolve the issue), and the renewal may be lost.

Salesforce leverages the open-source Cloud Information Model (CIM), which, in this context, is enabled by MuleSoft technology. Unifying customer data is not just about bringing greater order and manageability to data; it enables the connection of customer-serving processes and applications across the enterprise. Greater visibility and connectivity across that enterprise IT landscape is a key success feature, helping enable digital transformation end to end, not just at the front end.

graphic explaining how unifying customer data enables the connection of customer-serving processes and applications across an enterprise

Digital gravity is defined by data

Digital transformation is clearly a prime driver for this work but it also usefully flags a shift in the center of gravity for many enterprises. From the early days of enterprise IT where specialist hardware manufacturers “owned” the enterprise IT relationship, through the rise of applications vendors, the next big shift will be digital gravity of data. In a world where technology solutions may be on-premises, in the cloud, across hybrid environments, owned, rented, or shared, the lines between hardware and software have blurred. The constant in all this change is data, which is enjoying a long, long overdue focus as being the connective tissue that holds together the enterprise.

From providing the definitive reference point for customer information, the source material for analytics and artificial intelligence (AI) and the currency of trust, whomever is seen as the source of truth in this field is likely the key technology relationship in the enterprise. Salesforce has set its stall out with Customer 360 Truth, supported by the connectivity of MuleSoft and insights of Tableau. 

Voice of the customer, yes, and now the voice of the employee

It is well known that many employees waste time and effort trying to get technology to do what they want. The means having to interact with enterprise technology that has been stuck in a rut, scattered with keyboards, mice, and discarded technical manuals. The ability to simply ask a question and get an answer has been developing at a clip in the consumer world (with devices like Alexa and Google Assistant proving the point).

During the first keynote at Dreamforce 2019, cofounders Marc Benioff and Parker Harris demonstrated  a smart speaker device asking it natural language questions about relevant business topics, such as sales performance. The Einstein platform is a key part of Salesforce’s development, bringing together analytics and AI to deliver actionable insights from data. While the underlying technology may be complex, the question and answer functionality of this capability enables users to get to the answers quickly—without having to learn a new technology.

Einstein Voice Assistant was introduced at Dreamforce in 2018; this year we were introduced to Einstein Voice Skills, expanding the voice capabilities of Einstein to admins and developers who will be able to build voice-powered apps with clicks rather than code.

See and understand your data—by talking to it

It is not just CRM benefiting from natural language. Last year, self-service analytics platform vendor Tableau was acquired by Salesforce, and took to the main stage at Dreamforce for an overview of its latest features and functionality. 

Following the same principles, Salesforce demonstrated how, by simply typing natural language questions into the interface, the Tableau solution understood the requirements, and built new visualizations and answered questions about the data. This capability is absolutely critical for expanding and simplifying the ongoing growth of data-driven decision-making in businesses; users should be able to interact with the data by simply asking questions of it, not spending time and effort trying to learn and understand the technology.

Tableau’s position in the Salesforce portfolio is similar to that of MuleSoft. A substantial part of its value is found in its independence, the ability to work with just about any application or data source to facilitate the myriad multi-vendor use cases found in enterprises. Salesforce already has some analytics capabilities in its portfolio, and the messaging at Dreamforce was that Tableau fits into the portfolio as the platform for enterprise-wide analytics. There is certainly serious potential among existing Salesforce customers as prospective adopters of Tableau—in our view, many of them will likely have Tableau deployed, at least as a departmental level solution. As Salesforce continues to expand on its platform story, the opportunity for offering Tableau for its customers to standardize on is likely one of the more compelling rationales behind the acquisition.

Ethics requires more than just good words

No good discussion about technology is complete without some time given to the subject of that technology’s ethical use. However, we often encounter the problem where these well-intentioned conversations do not translate into actions. 

Salesforce’s approach is different. In 2018, the vendor appointed a chief ethical and humane use officer, Paula Goldman, who, during one of the analyst sessions, set out some of Salesforce’s approach to not just considering these important issues, but how the company is budgeting time and resources to build ethical considerations into the creation and use of Salesforce's products. With AI-powered automation delivering what is often referred to as the fourth industrial revolution, the positioning and timing of Salesforce’s focus and contributions to ethical use could not be more prescient. 

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Salesforce Positions Customer Data as a Center of Digital Gravity Digital transformation was key at Dreamforce 2019, where Salesforce debuted new products and initiatives aimed at creating a more integrated and effective digital experience for customers.
Tom Pringle Tom is Vice President of Market Research at G2, and leads our analyst team. Tom's entire professional experience has been in information technology where he has worked in both consulting and research roles. His personal research has focused on data and analytics technologies; more recently, this has led to a practical and philosophical interest in artificial intelligence and automation. Prior to G2, Tom held research, consulting, and management roles at Datamonitor, Deloitte, BCG, and Ovum. Tom received a BSc. from the London School of Economics.