John Barrows on Creating Urgency: It’s About Uncovering Impact, Not Manufacturing Demand

J

John Barrows

LinkedIn Author

Helping sales leaders decide: replace, rebuild, or retrain your team for the AI era | Founder, JB Sales | 3x LinkedIn Top Voice

In a recent LinkedIn post, sales trainer John Barrows tackles a perennial question in the sales world: how to create urgency. Barrows asserts that while sales professionals cannot truly “create” urgency, they possess the ability to uncover and drive it. He argues that many sales representatives falter because they fail to adequately prepare before client interactions, often losing potential deals before the first meeting even begins.

Barrows elaborates on this point, stating:

“Unfortunately most reps never do because they lose the deal before the first meeting, when they walk in with a company overview and questions they could have easily answered by doing 2 seconds of research using any of the AI platforms.”

According to Barrows, the common pitfall is a lack of deep discovery. He explains that many reps ask surface-level questions like “what are your biggest challenges,” hear a problem, and then immediately pivot to a pitch. This approach, he contends, bypasses the critical step of understanding the problem’s cost and its broader impact on the client’s business. Without a clear understanding of the impact, genuine urgency cannot be established.

The Role of Preparation in Uncovering Urgency

The solution, as Barrows highlights, has always been better preparation. However, he acknowledges the practical challenge: the time commitment required for thorough pre-meeting research. Traditionally, spending two hours per meeting was often necessary, a luxury few sales professionals could afford.

Barrows then introduces a modern approach, leveraging AI to streamline and enhance this crucial preparation phase. He outlines a process where AI assists in researching the industry, company, persona, and even the individual contact. This allows for the development of targeted hypotheses about potential client issues.

AI-Assisted Discovery and Impact Questions

Barrows’s AI-driven methodology focuses on generating hypotheses and crafting impact-focused questions. These questions are designed to probe the cost and consequences of identified problems, preemptively addressing the client’s potential question of “why do you need to know that?” This refined approach, he notes, can condense the preparation time significantly, from two hours to approximately twenty minutes, while simultaneously improving the quality of the questions asked.

“Three hypotheses about what’s probably going on. Impact questions built off the one I pick and a reason for asking assuming the client will ask ‘why do you need to know that?'”

He further explains the benefit of this accelerated and AI-enhanced preparation:

“Then I have it play the role of prospect and I run the call before the real one. It gives me the shallow answer and I have to layer to get to the cost. Twenty minutes instead of two hours and the questions got better.”

This simulation, where AI acts as the prospect, allows Barrows to practice navigating the conversation and digging deeper to uncover the true cost and impact, thereby fostering a more potent sense of urgency based on genuine business needs.

Driving to Close: A Practical Application

Barrows plans to demonstrate this entire process live at an upcoming Learning Lab, a component of his “Driving to Close” training. Attendees will receive the prompt pack he utilizes in his AI-assisted preparation. This initiative underscores his commitment to providing practical, actionable strategies for sales professionals to improve their discovery and closing techniques.

As John Barrows concludes his post, he invites engagement by asking his audience about their go-to discovery questions that effectively uncover root causes and business impact, further emphasizing the importance of this foundational sales skill.

📝 About This Content

This article is based on insights shared by John Barrows on LinkedIn.

📅 Originally posted on September 2, 2026 | View original post on LinkedIn →