BY Jessica Helinski
Despite the popularity of using generative AI in sales, there is at least one roadblock keeping it from replacing reps. Insight selling. Knowing this, sellers must actively engage in this practice and work on necessary skills.
What is insight selling?
First, it’s important to know the meaning of insight, which is understanding someone or something accurately and intuitively. When, as Paula Fernandes explains, it’s applied to sales, you get an effective process to educate and guide others.
“…it means you use data, trends analysis, market research and experience to help customers sift through the relevant information.,” she writes.
“This helps them diagnose problems, determine their needs and make informed buying decisions so that leads will buy from you.”
Why it matters in the age of AI-assisted sales
Sellers are embracing the power of AI to improve efficiency and outcomes. In particular, generative AI can help with a variety of sales-related tasks.
Specifically, SalesFuel found that 70% of sellers say they’ve used generative AI and will continue doing so. SalesFuel reports that common uses of generative AI in sales includes:
- Generative content: This is often used for email creation and call scripts, typically tailored to each prospect's and customer’s preferences.
- Generative insights: Data collected that is tailored to business needs, like opportunity highlights or account summaries, and presented to prospects.
But, as Alex Walton and Teresa Garanhel explain in an article for Competitive Intelligence Alliance, AI has its limits.
Generative AI shortcomings
One of the biggest issues with AI is that so many are using it. When everyone has access to the same AI tools, the tools themselves don’t make you special.
But what does set you apart? How cleverly you use them to uncover insights your customers haven’t even considered.
“With tools of sufficient complexity, the competitive advantage becomes wrapped up in how you use them,” they write.
“Learn to use generative AI to its fullest extent. This way, you become the differentiating variable. You become the competitive advantage."
You’ll find that this is an opportunity to stay competitive. When AI levels the playing field, your ability to integrate it into insight selling will set you apart.
Training and accuracy issues
Another shortcoming of generative AI in sales is its unreliability. Watson and Garanhel point out that LLMs learn from both unsupervised and supervised data. And these can be greatly impacted by human errors in training. The result? AI can sometimes give wrong or misleading responses, especially in complex situations.
“Just as, in competitive intelligence, your conclusions are only as strong as the data they spring from, an LLM can only be as good as the data it’s trained on.”
This corresponds with another issue: inconsistency. SalesFuel CEO C. Lee Smith points out that generative AI can also deliver various results, which can be disastrous for sellers.
“AI generates reliable results about 7 times out of 10—enough to lull you into a false sense of security that you don't need to verify results,” he explains.
“This can destroy a salesperson's credibility with business owners who their industry and customers just to survive.”
This is where being meticulous about your own research and data findings separates you from those who rely on AI. Ensuring your insight selling is based on accurate data is essential.
If you do use generative AI as a resource, always double-check it for accuracy. Also, go ahead and offer deeper insights that go beyond the basic AI outputs.
While industry professionals encourage sellers to use AI, it’s up to sellers to be strategic. As more of their competitors leverage generative AI, the more impactful the power of insight selling will be.
To stay ahead, sellers should thoughtfully integrate AI into their insight selling strategy based on these suggestions. And for tips on AI best practices in sales, take a look at this guidance.
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