We take all these technological innovations for granted. And eagerly await the next ones. Well, at least one group – artificial intelligence – is already here. While sales reps and managers have gotten used to the ex- plosion of digital tools designed to help them track and close deals, there’s no doubt these programs and devices make selling more efficient – or, at least, they make it easier to con- tact and track more prospects and customers. But sometimes the tools themselves can become, not technological marvels, but annoying distractions from the sales effort.


Is It Intelligent?


The latest family of tools travels under the name of ar- tificial intelligence (AI). So what exactly is AI? And will it help or burden salespeople? Some wary sales consultants think AI has become just a marketing buzzword software vendors use to sell solutions. But others look to reps’ and managers’ increasing ability to deal with closing deals and serving customers while technology handles the ho-hum administrative tasks instead. But wait: While sales is (and has always been) a people business, AI even promises to help with that.


AI certainly includes specific techniques, like natural language processing – hey, Siri does that! It also includes machine learning – and Siri does a bit of that too. Basically, though, AI is any software that “thinks” at least a bit like a human does, at least for a very specific and well-defined problem. And, if the problem happens to involve massive numbers or data, AI may actually think faster and better than humans.


This makes AI sound a bit like data analytics (and there is a fuzzy line between analytics and some AI tools). But, for sales leaders, AI’s true definition doesn’t really matter. What matters? What a specific tool can do, how well and accurately it can do it, and how much that will benefit sales performance. Some very respected neutral observers say certain AI tools already (or soon will) pass these tests. For example, AI-assisted automation of many sales administrative processes and mundane communication tasks is already spreading. Smarter training recommenda- tions enabled by AI are near. AI to remove at least some of the burdens of forecasting is coming. AI tools for territory decisions and helping set incentives could arrive in a few years. AI to feed pipelines, set priorities, and clear out the dead wood is on the near horizon.


Robots to the Rescue? Tad Travis, research vice president at Gartner, thinks of AI


as a natural outgrowth of the advanced analytics and ro- botic process automation (RPA) that has been adopted by B2C sellers and is now spreading through B2B. He argues AI will start with predictive analytics – essentially, scoring opportunities based on smart analysis of all the available data on them. Then Travis sees AI moving into prescriptive analytics. “That will mean guided selling,” he explains. “All reps need help on what to do next with a prospect, deal, or account.” For companies willing to report to Gartner, a


significant share are at least attempting to use prescriptive AI, and Travis thinks, “Generally, companies are very early on the path of adopting prescriptive analytics.” One sign that all this is getting more real is that major CRM providers such as Salesforce.com, Microsoft, Oracle, and SAP are adding predictive analytics to their offers – scoring leads as a first step to prescribing the right moves for reps. And the same major software companies are developing RPA tools that can work with certain very stan- dard data sets and processes common in sales. For example, RPA is already automatically generating outbound emails tailored to the stage of the sales process, the prospect, past actions, and other data. “The app de- cides what message to send on what day,” Travis explains. “The recipient can click to schedule an appointment, and the message is very difficult to tell from one sent by a hu- man.” Even after initial deployment, this AI approach gets better. Machine learning runs in the background tests and tweaks the automated emails according to phrasings that have been shown to achieve better results.


Message Me Travis cites another AI tool that decides which of hundreds


of inbound contacts need immediate qualifying contacts from reps or marketers, which message should be sent, and which channels should be used to send them. Gart- ner calls this kind of assistance “sales acceleration,” as it removes the manual analysis of leads that, in addition to requiring man-hours of effort, slow sales down. Another near-term AI tool uses natural language pro- cessing to analyze reps’ conversations with prospects. These conversational analytic tools record conversations, convert them to text, and then analyze their effectiveness in advancing the opportunity. Travis predicts major CRM providers will offer all these AI tools and more in the next three years. Forrester Principal Analyst Mary Shea agrees with Travis that AI will soon enable better and faster sales decisions, suggest the best next actions, and automate manual tasks. She argues AI will thus help close the current gap between how prospects want to buy and how they are served. AI will enable reps to deliver a better customer experience. And it will do all this while slashing the 40 to 50 percent of rep time now devoted to low-value administrative tasks. Predictive analytics will prioritize opportunities and


recommend the right content to share with prospects. And AI can also be used to help train reps. Smart tools can suggest mini training lessons delivered in real time based on prospect characteristics, contacts to date, and where the prospect is in the sales process. Shea calls this “sales readiness AI.” The Forrester analyst sees AI helping sales managers design their territories more fairly and effectively, set quo- tas and payouts for better performance, align reps with the right territories, and recommend regions and products on which lagging reps should focus. For sales leaders, Shea says, AI can even recommend the best spiffs to improve performance.


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