Artificial intelligence has evolved to the point where any sales organization that leverages AI will see measurable improvements in customer engagement, LTV, and overall sales. Join speakers from Capital One, Yelp, SurveyMonkey, and TopBots to learn how to use AI to sell B2B smarter and harder at this VB Live event.
[aditude-amp id="flyingcarpet" targeting='{"env":"staging","page_type":"article","post_id":2358918,"post_type":"vblive","post_chan":"none","tags":"category-business-industrial-business-services","ai":false,"category":"none","all_categories":"commerce,","session":"C"}']“When we think about applying AI, we try to take a human-centered lens to it,” says Rick Winslow, VP and head of digital innovation and transformation at Capital One Commercial Banking. “We want to start by asking what problems and opportunities do our customers and associates have day to day?”
It just comes down to efficiency, Winslow says: Saving sales people time in finding customers, helping them increase their hit rate, enriching the data they have in order to go after the most qualified customers, and helping enrich that customer conversation.
“Part of what we do is provide data to salespeople to help them with prospecting and targeting,” he says. “But part of it is also arming our salespeople with insights, so it will add value to our customers and help uncover customer needs more effectively and deliver solutions.”
AI plays a huge role in just making sense of all the data that’s out there, he adds. Salespeople are often working with disparate, incomplete data sources on private companies. And if you look at the job of that salesperson, or relationship manager or others who are in customer-facing roles, it can be a challenge to reach business customers, find the right decision-maker, or even find their contact information. It’s hard to pre-qualify private companies.
“For us, timing is everything,” Winslow says. “Revenue in commercial banking is really tied to customers’ lending needs, and it’s at that moment that we have an opportunity to go in and help solve their needs. AI does 90 percent of the work that gets you to the right prospect at the right time.”
But data is also part of the challenge in implementing an AI solution, he says, and your company’s ability to implement artificial intelligence depends on what the data ecosystem in your industry or area looks like. Regulatory oversight of each industry means there’s quite a difference in the availability of public and private data.
The second challenge is whether you have scale in your sales organization. The maximum benefit in B2B sales is just in getting more leverage out of your salespeople’s time, saving them time so they can prospect faster and more efficiently. The multiplier effect — the benefit you get out of AI in the sales process — really just depends on the scale of the sales organization, he explains.
“In B2B, that scale is always much smaller than in a B2C context,” Winslow says. “But even then, if you make 10 sales people twice as effective, versus 100 salespeople who are twice as effective, you can just do the math.”
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The last challenge is the degree of difficulty in predicting customer readiness, and how involved that process is. If you have a relatively transactional customer relationship that you’re ultimately trying to sell, it’s easier to apply AI, where you can predict whether that customer is ready or receptive. Whereas if they have a really complex set of needs, somewhat nuanced, somewhat time-bound, if the opportunity is very contextual and event-driven, it’s going to be a lot harder.
But in the end, the biggest obstacle to implementing AI technology in your sales organization might be getting your salespeople on board, he says.
“In a B2B context, salespeople don’t tend to be technology early adopters in a lot of cases,” Winslow says. “They know their industry really well, they have great relationships, and they’re good at solving customer problems. But salespeople aren’t known to always be the most digitally savvy folks.”
The main issue is trust: trusting the predictive model that you provide, and the data you’ve uncovered, versus the data they’ve gone and sourced by themselves.
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“We need channels for relationship management people to interact with AI, with data and AI tools, but what we more importantly need is an onboarding process, outreach, engagement, training, and trust-building around that,” says Winslow. “Otherwise, we can build the best models and provide the best data, but if they don’t trust it, they aren’t going to use it.”
For real-world case studies on the real-world ROI that artificial intelligence can deliver to sales organizations, what it takes to get your organization AI-ready and more, don’t miss this VB Live event.
Don’t miss out!
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Attend this webinar and learn:
- AI fact versus fiction when it comes to sales
- How to build a data- and AI-friendly sales organization
- How leading brands build real results and how they do it
- Which AI tools actually bring results and which are still in development
- What’s next for AI and sales?
Speakers:
- Rick Winslow, VP, Head of Digital Innovation & Transformation, Capital One Commercial Banking
- Jenny Lin, Data Scientist, Yelp
- Ksenia Kouchnirenko, Head of Business Systems, SurveyMonkey
- Marlene Jia, COO & CoFounder, TopBots
- Rachael Brownell, Moderator, VentureBeat