3 Ways AI Is Upending the B2B Sales Experience
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 pieces of content -- and even what order of slides -- will work best for the particular combination of buyers in the room during a presentation.
Which brings me to my next point …
Eighty percent of B2B sales organizations find personalized interactions to be most effective with buyers. Unfortunately, Forrester has found that 78 percent of buyers say salespeople come to meetings with irrelevant or incorrect materials.
AI opens up a new world of personalization in sales conversations. One important instance will be in lead scoring. Right now, lead scoring essentially involves qualifying leads by fairly large, non-specific buckets based on previous interactions and subjective human input. 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.
From there, AI will also usher in dramatic changes to the content used by sales reps. Integrating data coming from the Internet of Things opens up particularly intriguing cases. Today this data primarily assists product monitoring, but it’s not hard to see a situation in which, say, Boeing, through the digital monitoring of their own commercial machine parts, reaches out to American Airlines with a personalized product brochure -- automatically personalized with the right logos and pertinent case studies for the individual buyer -- on new turbines the moment there are indications that it may be time for a new one within their fleet.
3. The elimination of mundane sales tasks.
Popular calendar and scheduling tools are, frankly, a giant pain for everyone involved. 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. We’re already seeing a crop of new tools that leverage AI to help with scheduling meetings. X.ai, for example, automates the email back and forth for the sales rep.
Another manually intensive area of sales is note taking. Required for proper follow-up, note taking can also distract the rep from giving his or her full attention to the buyer. Clarke.ai is claiming to solve this problem via NLP. By dialing into the service before a call, Clarke.ai will record the context of the meeting and provide it back to the seller automatically.
Bringing it all together
While the tactical changes promised by AI will no doubt change the day-to-day of sales reps, its true benefit lies in the feedback loop. 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. AI will be able to pinpoint and predict areas of strength and weaknesses in the experience of each new lead that comes through, improving the entire sales and marketing process intelligently and automatically.
The main problem with AI and sales is how companies position these new technologies to the sales floor. AI can induce anxiety and anger when introduced improperly. It should be made clear that, when it comes to maximizing their time spent selling, AI promises to be a boon for reps, resulting in higher compensation, meaningful relationships with buyers and bottom-line company success. According to SiriusDecisions, these also happen to be the top reasons why sales reps stay with a company, resulting in long-term and enjoyable work in which the rep can find meaning and success.