Salesforce Honors Customers, Boosts Sales Productivity: Gleanings from an Industry Analyst Observer

Oct 9, 2018 12:44:15 PM

marcbenioffI could spend pages and days talking all about the new technology that was released at Dreamforce 2018, but I am going to take the higher road and discuss what Dreamforce 2018 means to customer organizations. Salesforce demonstrated that it cares about its customers and is committed to increasing the productivity of customer-facing teams around the world. Of course, if customer-facing teams are more productive, that will mean increased revenue, higher customer satisfaction, and a palpable competitive advantage.

The C-Suite Should see Gains in Productivity and Profitability

Many sales leaders complain about the challenge of getting sales representatives to enter information into their sales automation systems. The results are incomplete information and the inability to properly forecast and manage sales teams for success. The introduction of Einstein Voice allows sales teams to interact with Salesforce products over their morning coffee or handsfree on their drive home, freeing them to do more of what they are paid to do: sell.

Einstein Voice is more than voice recognition; it is intelligent voice interaction. Einstein artificial intelligence (AI) runs in the background, interpreting voice commands and connecting them to specific actions and information already in the system. For example, a sales representative can talk to Salesforce to enter notes, set actions, and make changes to an account. This first activity is simple voice recognition. When Einstein joins the party, it makes recommendations using natural language processing. It finds the right account record and opportunity, and it exposes the links immediately. When the sales rep selects the opportunity, Einstein recognizes that it was correct and learns from the experience. Einstein also takes the action items from the note and offers to make the changes. The sales representative says, “Save to Salesforce,” and Einstein does it. Done.

Pervasive Automated Insight will Yield Previously Undiscovered Customer Insight

Customer analytics continues to be the number-one investment area in information technology, just as it has for the last 25 years. Today’s challenge is that we have too much data, too many dashboards, and too much noise. Digital transformation and the proliferation of sales, marketing, and customer service automation provide valuable customer insight, but finding the most valuable insight remains obscure.

Salesforce demonstrated both Einstein AI and Voice running with their Sales Cloud, Marketing Cloud, and Customer Service Cloud. The obvious value to customers will be insight-driven decisions for anyone who touches a customer without the intervention of a data analyst. The not-so-obvious value will come from looking at correlations across the three business areas. While the former business impact will be immediate, the latter will likely come down the road as the separate systems are more integrated.

The Use of AI in Business Intelligence Makes the Insight-Driven Enterprise Feasible

Most organizations face two major barriers in their journey to become driven by insight. One, they lack the data analyst resources necessary to serve the entire business community. Two, they have not successfully embedded analytics in their business processes. The use of AI within business intelligence and analytic platforms has been spreading over the last year, with similar announcements for IBM Cognos, Domo, SiSense, ThoughtSpot, Tibco Spotfire, and Yellowfin.

With the application of Einstein AI to Salesforce Analytics, customers can expect to increase the flow of information to both executives and frontline workers. Salesforce users can launch Einstein from within their typical dashboard views, or receive recommendations from Einstein as they are working their operational workflows. To assist in finding immediately useful information, users can also “talk to their analytics” using Einstein voice.

To demonstrate the ease of use, the demo was done by Salesforce customer, Mirko Gropp of Telstra.

To demonstrate the ease of use, the demo was done by Salesforce customer, Mirko Gropp of Telstra.

The API Economy is Upon Us

In the last several years, Salesforce clearly moved from its early days as a customer relationship management (CRM) platform to become an enterprise application ecosystem. Via acquisitions and a substantial partner ecosystem, there are now hundreds of enterprise applications that can be plugged into or run on the Salesforce platform. Since most of global digital transformation takes place in the areas of sales and marketing, this puts Salesforce right at the center of every digital project. However, this diverse ecosystem creates a major data challenge and a big opportunity for enterprise analytics.

One of the main Dreamforce 2018 highlights was the Salesforce acquisition of Mulesoft. Based on the challenge described above, the acquisition makes perfect sense. The agility through APIs and the ability to connect data from across an enterprise application ecosystem is vital to any organization. A Mulesoft demo showed the ease of being able to make connections from within the Salesforce system. Customers can expect easier access to information from across their entire organization.

Customers Matter Most, Customer Insight Matters More

What is the bottom line? Customers matter most and customer insight may matter more because of the way it transforms the customer relationship. My sense is that many of those in attendance at Dreamforce understand that customers matter most. I am not convinced the audience understood the full impact and value of customer insight. However, adding an intelligent voice interface for end users should go a long way toward the penetration of both of these messages into organizations. In addition, by embedding analytics and AI everywhere in their applications, Salesforce is well on the way to evangelizing some of their biggest investments.

John Santaferraro

Written by John Santaferraro

John is the research director for analytics, business intelligence, and data management at EMA. His 23 years of experience in the data and analytics market span everything from startups to executive positions at Fortune 50 companies. His deep understanding of the industry comes from years of leadership in product and marketing organizations, along with multiple big data imagineering efforts for finance, communications, retail, manufacturing, healthcare, events, oil and gas, and utilities. John's coverage area also includes data integration, data discovery, metadata management, artificial intelligence, machine learning, data science, digital marketing, and innovation.

    Lists by Topic

    see all

    Posts by Topic

    see all

    Recent Posts