The question has changed from “how do we get data?” to “what do we do with it?” Forrester found that enterprises plan on increasing investment in artificial intelligence (AI) by 300 percent in 2017. One area of major AI investments will be sales. Content and meeting preparation processes are also primed for AI, particularly through natural language processing (NLP). NLP will also improve how sales reps prepare for meetings by bringing context front-and-center. By leveraging data accrued from past meetings across the sales organizations, sales reps will know what pieces of content -- and even what order of slides -- will work best for the particular combination of buyers in the room during a presentation. Eighty percent of B2B sales organizations find personalized interactions to be most effective with buyers. With AI processing data from the entire marketing, sales and UX technology stacks, lead scoring will become exponentially more granular, where sales reps are handed personalized blueprints on how to approach each lead as an individual. Our sales team of 60 schedules about 3,600 meetings per month. If each meeting takes 10 minutes of sending calendar invites back and forth and including new attendees, the result is 600 hours per month wasted scheduling meetings. Big data investments have allowed data to be collected from all areas of the customer experience, from first touch to the monitoring of products they end up using.
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This year will be known as the year enterprises became artificially intelligent. Research by Gartner suggests that interest in new big data investments has peaked. The question has changed from “how do we get data?” to “what do we do with it?” Forrester found that enterprises plan on increasing investment in artificial intelligence (AI) by 300 percent in 2017.
One area of major AI investments will be sales. Customer analytics are one of the largest data sources for enterprises, and Salesforce already made a big splash earlier this month by releasing Einstein, their AI assistant designed to help sales teams uncover insights that will help close deals and identify upsell opportunities.
But how exactly will sales be upended by AI? I see three main areas:
1. Process optimization.
According to CSO Insights, 43 percent of enterprise sales reps miss quota. The main reason? Lack of efficient, organized sales processes.
AI will make huge inroads in regards to optimizing the sales process, beginning with the onboarding of new reps, which currently takes upwards of six to 10 months to reach full productivity.
Based on observing the actions of high-performing reps, AI will provide a blueprint to new reps, offering guidance in terms of how often reach out to a prospect and what collateral to send them to be most effective in closing deals. This “autocoach” functionality will mitigate the time in which new reps operate at a loss because they are acting in a statistically similar way as high-performing reps.
Content and meeting preparation processes are also primed for AI, particularly through natural language processing (NLP). For example, client-facing collateral in regulated industries, like financial services, is often required to include correct disclosures, a manual process usually delegated to reps. NLP can automate this process through keyword scanning, and as sales compliance remains a hot button issue in financial services, expect to see AI play a major role.
NLP will also improve how sales reps prepare for meetings by bringing context front-and-center. By leveraging data accrued from past meetings across the sales organizations, sales reps will know what…
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