The Unstoppable [Selling] Force

The Technology That Turns Sellers Into Superheroes

“We were able to change the way our sales team thinks and show them that the use of data and analytics can help them do their job smarter and more productively,” Woll tells The Modern Sale. Now AXA’s sales team is harnessing data through artificial intelligence via applications like Collective[i] to provide analytics solutions to drive productivity, with quantifiable results.

“In the financial services industry, there are many sales roles that still rely on good old phones calls and face-to-face meetings, and the switching costs from legacy sales systems is quite high,” Woll admits. “The digitization of the sales process is only just beginning, and we expect it to have a big impact going forward.”

In other words, watch this space.

“The digitization of the sales process is only just beginning, and we expect it to have a big impact going forward.”

Although everyone from manufacturers to marketers have adopted new technologies to improve productivity and eliminate pain points, sales is somehow the last sector of the enterprise to modernize. Woll, however, is an outlier. For nearly every other chief operating officer, chief revenue officer or head of sales, Customer Relationship Management (CRM) systems have been and remain the holy grail. Which is crazy. In what other area of consumer or business life are people still using 50-year-old technology? And as sales organizations morph to almost entirely comprise millennials and digital natives, “we need to prepare for a future where a salesperson will need to have insights and intelligence at their fingertips,” says Toby Carrington, senior vice president and head of global sales operations at Siemens Healthineers, a med-tech services company. “This is a generational shift coupled with the AI and machine-learning revolution.” Doing nothing, in other words, is the silent killer. Just look at Toys ‘R’ Us (RIP), which kept its merchandise in pricey brick-and-mortar stores, versus Amazon’s many online advancements and perks, which just got you to buy something you didn’t even know you wanted. It’s arriving this afternoon.

Hiring agile, expert sellers with great interpersonal skills is critical, but enhancing and upgrading the sales stack, top sales leaders argue, is equally as important. “If I were a Nascar driver, I’d know that my competitors all have basically the same car, which means performance comes down to each driver’s execution,” says Shawn Schwegman, co-founder and chief strategic officer of customer-acquisition platform DemandJump. But in today’s sales-driven companies, no car is the same, which provides for an unfair advantage. “The only way to maintain that edge over a competitor, beyond hiring the right team, is to build a better car for the salesperson to drive. And that is not going to happen starting with CRM as the core platform. Therefore, building the right sales and marketing tech stack coupled with the right training and internal adoption is essential to outmaneuvering one’s competition and winning in the marketplace.”

Likewise, training an entire team to sell the same way your top salesperson does is impractical and old-fashioned, especially in a world where everything we touch in our consumer lives is personalized. The most basic first step in harnessing a sales team’s skills is to implement a lead-generating platform such as HubSpot or Oracle Eloqua. These technologies optimize time spent on actual dealmaking, which is essential considering that between 63 and 80 percent of a buying decision has already been made before a seller even reaches out to a prospect. But integrating a dynamic tool into the sales stack doesn’t mean anything if CROs don’t also take a cold, hard look at their legacy CRM systems. Even with add-ons like Salesforce Einstein, IBM Watson and other forms of predictive analytics, CRM is limited to analyzing a one-dimensional process—one seller with one buyer. The reality is that modern buying processes have become increasingly more complex involving multiple internal functions (legal, finance, marketing as examples) and larger buying teams. Adapting to that reality requires a sophisticated technology stack that not only removes tasks from the sales professional but also provides robust tools for internal collaboration with both human and machine-generated insights to enable true and real-time personalization of the selling process. As anyone who works with legacy CRM systems knows, manual logging is rarely done by sales people and never by the other people in the process who do not even have a license — which means so much intelligence is lost. And perhaps most devastating is the internal time spent trying to gather this intelligence resulting in less and less time spent improving the buying experience and outcomes.

“How do you not take into account all of the people in the deal or use technology to find people you know who can help you?” asks Stephen Messer, co-founder and vice chairman of the leading AI sales technology company Collective[i], whose application and rapidly-growing network provides sales teams with artificial and machine-generated intelligence and hosts the social network for sales professionals, “If the security guy gave the wrong answer or the lawyer took three weeks to get back to the buyer, and either one of those is what killed an opportunity, no one would ever know. Everyone who interacts with the buyer should be automatically logged at every point. No sales professional should have to talk to 10 people and then log every interaction. There is no sales skill in spending time getting other people up to speed or trying to forecast when a deal will close. The reality is that many sales professionals don’t enter data because it takes away from time spent selling.”

Which is where an automated network-driven platform comes into the sales stack. In the same way a company tracks activity of users to its website, CRMs need to effortlessly track not just the sellers but everyone on the deal. Messer’s Collective[i], for example, pulls from email, phone logs, calendars, document-management applications like Box and DocuSign, price-quoting technology and any other programs that collect data related to how buyers and sellers interact for the purpose of predicting outcomes. This enables internal buyer-centric coordination and the ability to identify real or perceived problems specific to each deal. By tying all that company-specific data to a network of other sales forces, the machine learns and the application (along with its users) not only becomes supersmart and highly accurate but also constantly adjusts to changing buyer behavior. As does Waze for drivers, Collective[i] anonymizes sellers’ information so companies aren’t giving away any secrets. And let’s face it — if your competitor is using the network but you’re not, “it’s like pretending the internet doesn’t exist,” says Messer. “If B2B sales can learn anything from recent history, it’s that the most networked companies and people win.”

“If B2B sales can learn anything from recent history, it’s that the most networked companies and people win.”

For a real-world comparison, walk into any Apple store, and you’ll walk out with a phone that already works, plus a bunch of accessories handpicked by a smiling professional. Or look at how online mattress retailer Casper has set up physical stores populated by sleep experts who show consumers why foam is better than springs. You could buy your Tesla car online, but if you go to the showroom, an electrical engineer will talk you through your fears of the expensive purchase and take you for a test drive at no additional cost. The way consumers engage with retail purchases is also dramatically affecting the way companies expect to be sold to as well as how they make decisions, and sales teams are only just starting to respond. “In sales, it feels like people are still focused on quotas rather than focusing on the buyer’s experience,” says Messer. “But when you have GE opening an online store selling nuclear parts, you get the sense that if sales doesn’t advance, then sales will die.” He says the leaders who will make it in an AI augmented world will constantly be thinking:  “If  I’m  still  selling  the  way  I  was  five  years  ago,  I’m  probably  doing  something  wrong.”

This generational transformation of how sales gets done doesn’t mean human sellers will become obsolete. In fact, a recent study by Boston College, Harvard University and the University of Michigan found that training in “soft skills,” like communication and problem-solving, boosts productivity and retention by 12 percent and delivers a 250 percent return on investment. Ironically, through recent innovations, a sales professional can return to being a people person rather than a data-entry person. “Technology will make salespeople more efficient, intelligent in terms of insights, and connected internally and externally,” says Siemens’ Carrington. “But humans still have to provide value to our customers by explaining our relevance to a particular strategy and by building trust through strong relationships.” Let technology do the grunt work — then allow your sales team to take the deal over the finish line.

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