Salesforce Applies More AI to Sales Management

    Salesforce has expanded the sales team management capabilities of its Sales Cloud platform by melding its Einstein artificial intelligence (AI) platform and Tableau analytics software to create a unified revenue management command center.

    At the same time, Salesforce has added a sales enablement module that makes it simpler to onboard and train sales staff by leveraging Einstein AI to enable sales leaders to identify issues based on metrics such as lead-to-opportunity conversion rates, sales cycle times, and the rate at which deals close.

    Finally, Salesforce has also added a Subscription Management for Revenue Cloud module that makes it easier to manage sales teams that are being incentivized to drive recurring revenues.

    Providing Actionable Intelligence

    Salesforce has been steadily increasing the amount of AI that can be brought to bear on sales management processes for several years now. The Einstein Deal updates are designed to make it easier for sales leaders to spend less time collecting metrics that can be more easily aggregated by the Einstein AI platform, says Taksino Eammano, senior vice president of product for Sales Cloud at Salesforce.

    The goal is to provide more actionable intelligence to identify not only what deals are likely to close, but also which ones based on key performance indicators (KPIs) surfaced using Tableau analytics software might close sooner if additional efforts were made, she adds. 

    The Sales Enablement module, meanwhile, can be employed to identify areas where additional training provided within the context of a specific deal could also accelerate sales, notes Eammano.

    At a time when many sales teams are operating out of their homes it’s become more challenging for sales leaders to identify issues members of their sales teams may be encountering. A command center provides a fact-based approach to managing sales teams that leverages AI and analytics reduces the need for sales leaders to rely on guesswork and intuition, says Eammano.

    That’s critical because as business models evolve the age of digital transformation there’s more uncertainty than ever, Eammano adds. “There’s a digital imperative.” 

    Also read: AI and Observability Platforms to Alter DevOps Economics

    Taking Advantage of AI Now

    Of course, no amount of software is ever going to close a deal. Most people still buy anything of any real consequence from someone they have engaged with despite the rise of e-commerce as a vehicle for processing the ultimate transaction. That’s even more true of business-to-business (B2B) transactions that typically require a lot of effort to first close and then support.

    There will come a time soon when every sales representative has their AI assistant that will identify potential opportunities as well as issues that might have a negative impact on customer satisfaction. In the meantime, sales leaders that can’t be everywhere may have no choice but to rely more on AI to help keep revenue flowing. After all, the finance department will most certainly also be applying AI to determine exactly why sales goals aren’t being met. As such, it’s always better to be the one bearing the news first, good or bad, than to be surprised by it when delivered by somebody else.

    Read next: Bad Bots & Online Retail: A Q&A With DataDome

    Mike Vizard
    Mike Vizard
    Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.

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