Is generative AI for sales the next big thing?
ChatGPT took the world by storm seemingly overnight. When it happened, it appeared that almost everyone from your favorite LinkedIn influencer to your solution provider also became an AI expert at the same frenetic pace. The phenomenon is so far reaching that it can be difficult at times to find an actual single explanation for what generative AI is.
Here’s how Yann LeCun, Turing Award winning French computer scientist, explains it:
“Generative AI is the ability of machines to create new content, such as images, text, or music. This is in contrast to discriminative AI, which is the ability of machines to classify or predict things. Generative AI is a rapidly growing area of AI research, with applications in a wide range of fields.”
Sales is one of those fields. In fact, it might just be amongst the strongest applications for AI of all.
Generative AI for sales – a perfect match
As pointed out by the Harvard Business Review, sales has often lagged behind other areas of business in digital transformation. That could all change now, thanks to generative AI in sales. As pointed out in the article, the kind of data that sellers work with daily – phone calls, email threads, video interactions with customers – are exactly the kind of unstructured data generative AI can take, learn from, and work with.
This didn’t use to be possible. Sifting through that kind of data took hours and hours of sellers’ time. The big advantage here that has so many sales leaders (not to mention Salesforce itself) excited about is the possibility of removing those hours of manually sifting through this data to come up with new content and giving that time back to the seller to do what sellers do best.
That being selling things. Building relationships. Becoming trusted advisors to their most strategic customers.
What can AI do that sellers can’t?
Despite many mainstream worries about the future of AI, AI isn’t meant to replace human intelligence. As Steven Pinker, Johnstone Family Professor in the Department of Psychology at Harvard University, puts it, viewing human intelligence as something to be replaced is the wrong way of framing the impact of AI.
The right way of framing AI is to see it for what it’s good at – a specific kind of intelligence hyper powerful at a specific range of computation. For this reason, AI can certainly augment specific areas of intelligence, and perform those tasks better than even humans.
For example, we’ve long had computers much more capable of crunching complex mathematical equations, or of playing chess, than humans. Now, we have computers that can research and summarize from that research much, much faster, as well.
But some people get a little freaked out about AI and think it is doing more than it actually is. It is human-like, but not replacing fundamental aspects of what human sellers do.
AI can analyze vast amounts of data quicker than we can
Tools like ChatGPT have been trained on infinite amounts of data to be able to write about virtually any topic as if it were a knowledgeable professor. However, it works in ways vastly different than the human mind. In the words of Steven Pinker:
“We’re dealing with an alien intelligence that’s capable of astonishing feats, but not in the manner of the human mind. We don’t need to be exposed to half a trillion words of text (which, at three words a second, eight hours a day, would take 15,000 years) in order to speak or to solve problems. Nonetheless, it is impressive what you can get out of very, very, very high-order statistical patterns in mammoth data sets.”
While human minds may differ greatly from artificial ones, that doesn’t mean there can’t be interplay between the two. We can use AI to sift through this data and rely on human minds to think strategically and creatively about how to use this information.
What can sellers do that AI can’t?
Well, quite a bit. Even before the release of super advanced chatbots – and despite the rapid digital transformation the world has seen– sellers were indispensable in the buying decision when complex, high stakes sales were on the table. When it comes to these types of sales, it’s relationships that win deals and drive revenue, time and time again. Understanding who the key players are within an account, and what uniquely motivates them, and building relationships to help them achieve their goals is where sellers far outshine AI.
Strategize to analyze customer pain points and motivations
While generative AI is fantastic, it’s important for sales leaders to remember what its limitations exactly are when implementing it. Many companies may be busily touting its effectiveness (and the benefits it can offer are immense),but its shortcomings remain notable.
While chatbots like ChatGPT or the newer Google Bard may deliver customized, well-thought-out answers to complex queries, the models themselves processing this data don’t actually know or understand the information they are producing.
Language models are basically analyzing data and patterns and coming up with a best guess as to what should be said next. It does this so well that it seems to understand the subject and what it is discussing.
Human sellers, however, actually understand what is going on. They understand the context around the account, the people within it, and the problems and motivations therein.
They can gather all of this information in an insight map, and use AI to formulate these insights into actionable steps to lead them on a course to victory in the account.
Find novel solutions to problems buyers didn’t even know they had
Seeing the big picture is exactly where AI falls short. As excited as we should be about AI’s potential to boost productivity and remove mundane processes, we can’t rely on AI to see the big picture inherently.
In our book, Not Just Another Vendor, we highlight the story of Scott Jackson, Senior Director, Sales Enablement, Comcast Business, and how one of his sales reps sought out detailed information within an account. By talking to buyers, he was able to not only find the surface level challenges that they were facing. He was able to find novel, unique answers to hidden motivations that they themselves weren’t fully aware of.
Generative AI can only analyze what is there and extrapolate text or music or images from what it’s trained on.
True genius, however, is not hitting the target that no one else can hit – it’s hitting the target no one else can see. The same goes for greatness in sales. It’s finding those hidden motivations and offering unique solutions.
Talent hits a target no one else can hit; Genius hits a target no one else can see.
Benefits of generative AI for sales
Now that we’ve compared sellers and AI side-by-side, let’s get into some of those exciting benefits of using AI in sales. These include:
Remove administrative tasks
Great sellers provide the most value when they are doing what they do best – selling. Unfortunately, ample amounts of seller’s time aren’t spent on that activity. In fact, sellers are more bogged down with administrative tasks and non-sales activities than ever before. As generative AI grows in popularity, it could ease much of the administrative burden placed on sellers.
Help sellers with formulating customer responses and interactions
While generative AI has become quite strong and able to communicate almost like a human, it still isn’t a human. Perhaps the worst thing a seller could do is copy/paste from a generative AI tool and send it off to a customer without adding their strategic insight.
However, AI can help do a lot of the heavy lifting – researching market trends or company specific data and getting answers to more complex queries. Also, when trained around a specific segment of customers or personas, AI could be a lot more effective in producing sales briefs and responses to customers than a more general solution would be able to do.
Ultimately AI can help boost productivity for salespeople.
According to a recent study done by McKinsey: “AI can boost sales effectiveness and performance by offloading and automating many mundane sales activities, freeing up capacity to spend more time with customers and prospective customers (while reducing cost to serve).”
Also according to the study, 90 percent of commercial leaders expect to utilize generative AI solutions “often” over the next two years.
This boost in productivity could lend a competitive edge to organizations and sales teams that take the jump into working alongside AI as opposed to those that sit on the sidelines.
Personalization at scale
While personalization may come naturally once a relationship is established within an account, it can be hard to apply personalization at scale when dealing with customers in the prospect stage. Here, AI can help. AI can sift through relevant data on contacts gathered within the insight or relationship map and provide personalized messages to those contacts regardless of where they are at in the buying journey.
Ensuring every interaction with buyers is positive is necessary, given the current state of buying, digital channels, and relatively few seller-customer interactions.
Speed up data analysis
Another aspect of a seller’s job that often takes away from the actual “selling” aspect is sifting through data, pulling reports, and summarizing those findings into actionable insights. AI can help with this. Feed it your sales calls, reports, and all relevant data you have on an account and use its insights to inform your strategy, interactions, and even creative sales content.
Additionally, the greater revenue team stands to gain from using generative AI, bolstering their ability to tailor personalized messages in an account based selling environment, or when coming up with marketing to home in on exactly what the ICP is looking for. Using AI, it’s possible we could get much more granular about what goes into personalized messages.
Pitfalls to avoid when implementing generative AI for sales
Again, it’s easy to get excited about the potential of AI. But like with any new innovation, it comes with its own fair share of challenges. For example:
Generative AI for sales is not foolproof
Generative AI tools are incredibly smart, but also capable of baffling fallacies. In the words of Steven Pinker, generative AI’s ability to appear competent “makes its blunders all the more striking. It utters confident confabulations, such as that the U.S. has had four female presidents, including Luci Baines Johnson, 1973-77. And it makes elementary errors of common sense.”
Deciding how to handle the jump to AI is something that sales leaders can’t afford to take lightly.
Already there are stories of times ChatGPT has been used undiscerningly, leading to dire consequences in crucial fields like law. Other than the real possibility of ChatGPT delivering horrendously false or even offensive responses to queries, there is a security element to consider, as well.
Generative AI for sales poses security risks
Guardrails will inevitably need to be set to ensure safety and compliance well before AI is regularly adopted by an organization.
CROs and sales leaders need to consider, however, that even if they haven’t come up with a strategy yet for how AI is used in their organization, sellers could very well be using these tools already.
Generative AI for sales – tools and features to look for
Beyond the hyper popular AI chatbots, another very important AI powered sales tool has arrived – and that’s Einstein GPT from Salesforce.
Just recently made generally available, Einstein GPT is the tool to watch for generative AI in sales. Naturally, as many sellers do the majority of their day-to-day activities in Salesforce, they’ll look for a tool that can seamlessly leverage the data they are already working with natively.
Einstein GPT solves challenges out of reach for general models
Einstein GPT could potentially cover some of the areas ChatGPT is weaker in for corporate workers. It is designed specifically for corporate environments. Also, unlike ChatGPT which is trained on general information, Einstein GPT is trained on your unique customer data, making it so much more helpful at solving unique needs sellers come across in their day-to-day activities.
Additionally, Einstein GPT has access to real-time data, making it a more reliable source of information for current or recent events.
Einstein GPT’s “Trust Layer” could help bridge confidence gap for sales leaders
Finally, there’s one last area that Einstein GPT could excel where other more general models cannot. As previously stated, there is a privacy risk inherent to using generative AI tools in sales. However, Salesforce has added what they call a “Trust Layer” to help business leaders sleep better at night.
In Salesforce’s own words, this trust layer “will enable companies to get started with trusted generative AI faster by optimizing the right model for the right task. It will also provide deployment capabilities for any relevant LLM while helping companies maintain their data privacy, security, residency, and compliance goals.”
If this trust layer is strong enough to do what Salesforce intends it to do, we could see a rapid adoption of generative AI at every level of interactions between sellers and customers.
Salesforce native tools will benefit from Einstein GPT
This significance extends not only to the use of Einstein GPT for sellers – it also impacts tools and applications native to Salesforce. The best sales tool should be able to take advantage of Einstein GPT. For this reason, sales solutions that complement the data found within Salesforce natively are likely to win out against tools that aren’t.
Ultimately, the highest use case for AI in sales is that which applies to insights. Tools that help you gather insights are those that are going to be the most beneficial for sellers.
By sifting through this data, AI can do more than the simple drudge work that sellers don’t want to do anyways – it can help sellers get at that elusive bigger picture that is so incredibly invaluable.