AI And Sales, What We Misunderstand

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Based on much of the press, much of it created by vendors of AI solutions, AI is the answer to all the problems we have with sales and marketing. We are presented a brave new world where we can engage the right customers, say exactly the right words at the right time, making sure we ask no more than 4 discovery questions, that our opening pitch(?) is no longer than 9.1 minutes, that…..

All of this, done under the auspices of AI or it’s companion, machine learning (ML) will be the answer to our revenue generation challenges.

Sales execs and sales people breath sighs of relief, “We don’t have to worry any more. AI identifies the customer, gives us all the answers, it even puts the right words in our mouths.”



If that scenario is true, one then can project the perfection of voice technologies, imagining worlds of chatbots engaging customers in the right conversation all the time—why do we need SDRs, AEs any more, why deal with all these people issues, AI/ML is the answer to our revenue prayers.

OK, so I’m exaggerating a little–but not by much–at least when one reads the articles or talks to people anxious about the technology.

Actually, I have great hope for the application of these technologies in marketing and sales. Having co-founded, built, and sold one of the early AI start-ups, and now serving on the boards of several others. I think I understand some of the possibilities. At the same time, I’ve seen many of the challenges and the things that AI just can’t do.

AI offers great promise in helping better identify, segment, and target our prospects. It offers great promise in helping us identify the moment in time when there might be a higher propensity to buy. It gives us insights and helps us identify patterns that would have been impossible to recognize without the technology.

Of course, much of this isn’t new. In some sense it offers us more of what we already have–but aren’t using despite having them.

For example, for years we have had analytic and marketing automation tools to better segment, better tune, and refine our marketing and content outreach to customers. For years we have had the technology to “profile Dave, understand what he is interested in, understand the content that resonates best with him, and get it to him in an impactful way.”

This is nothing new, yet why am I and millions of others inundated with the same meaningless drivel, every day. For some reason, these companies who should know what I want, what I have responded to, feel the need to send me (and you) everything. Much of it seems to be an old advertising mentality where measuring impressions is more important than understanding relevance.



And the phone calls, there is no excuse for anyone not to have a nominal understanding of who I am, what my business is, and what might resonate with me. For years, technology has provided outstanding solutions to help sales people be more relevant in engaging customers and prospects, yet fewer than 10% of the people contacting me appear to be using it. Their only concern is broadcasting their message to see if I respond (of course the right use of the marketing/targeting/segmentation tools should never have put me on most of their call lists.

I can’t help but have more than a little cynicism–not about the technology/tools–but how we implement and leverage them for impact. If we fail to exploit the capabilities of the technologies and tools we have had for years, will we be able to realize the true promise of these new technologies.

I think part of the answer to that lies in the naivete or possible laziness of the people buying them (and somewhat from the messaging of the vendors). One of the great discoveries we made in the AI based enterprise analytics company I co-founded in 2002, was that to exploit our technology we needed really smart people thinking about the right issues (in essence focusing and training the AI/ML) and really smart people to know how to leverage the results we could produce. We started qualifying/disqualifying prospects based on these criteria.

The same applies for today’s technologies. I think too many naively think the technology can do these things, that it does the heavy lifting of figuring things out. (One wonders why data scientists are among the most sought after people if this is true.)

But let me get to what I think the real misunderstanding of these technologies is, at least for the complex B2B buying environment. AI/ML is really bad at a number of things:

  • Understanding context
  • Consciousness
  • Empathy
  • Common sense
  • Sense making

I’ll stop here. While AI/ML can help us understand potential answers and solutions, it can’t help us understand the right answer, because the right answer is always dependent on the customer, their context/experience, and a specific moment in time.



Ironically, the things these technologies are very bad at are the things that great sales people excel at. It’s these abilities that drive engagement and the ability of the sales person to create value with the customer.

These technologies offer great promise, as have past technologies. We have to be smart about how we exploit them. But these technologies fall very short in the things that are most important to our customers in complex B2B buying. We can’t fail to develop the capabilities in our sales people to help our customers.

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