A sales pipeline with seven stages sounds thorough until a new rep is staring at it, unsure what to actually do next. This episode breaks down a framework used with an enterprise client that cuts the whole thing down to three buckets, changing how a new seller thinks about their entire pipeline.

• The framework came out of watching an enterprise sales team manage huge deals without a clear sense of where anything actually stood.
• Following CRM tasks day to day gives a rep a to-do list, not a real view of their pipeline or control over it.
• The traditional pipeline collapses into three buckets: create, advance, and close. Create covers deals that aren't real yet, advance is where most of the active work happens, and close is where a deal actually converts.

• This isn't a replacement for a professor's existing sales cycle or CRM stages. The full pipeline still exists underneath.
• The three buckets give a rep a mental model on top of that detail, so they always know where a deal sits without getting lost in every individual stage.
• In the advance bucket especially, every deal needs a valid next step. Without one, that deal isn't advancing. It's stalling.

• Give students a real-life scenario, like a prospect stalling during discovery, and have them work out their own strategy for moving that deal forward.
• Students then role-play their strategy with a classmate, practicing the same critical thinking a professional seller uses every day.
• The same exercise works for the close bucket too, using scenarios where a deal is nearly done but something unexpected threatens to derail it.

• BJ shared a story of a VP of sales who forecasted her pipeline within one percent accuracy, a level most sales leaders never come close to.
• That kind of accuracy comes from reps who deeply understand their own individual pipeline, not from a complicated system nobody fully tracks.
• Simplifying the framework for students isn't about dumbing it down. It's about giving them a structure they'll actually use once they're in a real sales role.

• Teach the full pipeline stages students will see in a real CRM, but also teach the conceptual version underneath it: the constant question of what needs to happen to move this deal forward.
• This is the exact thinking a new rep will use with their own accounts, not just a classroom exercise.

"There's so much value in anything you can do to simplify the process for students." — Dr. BJ Allen

• Check out the courseware built with Stukent: Professional Selling and Advanced Selling and Sales Management
• Visit the Sales 101 podcast website for more episodes

What started with students bringing VHS tapes to class has now become AI-powered sales practice.

Mike Martin has been teaching sales for about 24 years, and he has watched technology change almost every part of how students practice. But the goal has stayed the same: give students a chance to practice sales conversations before they have to handle them with a real buyer.

In this episode, Mike shares how he moved from VHS-recorded role-plays to using ChatGPT for cold calls, objection handling, empathy practice, and more. He also explains why AI should support sales education without replacing the human interaction students still need.

• Mike started using recorded role-plays when students had to bring VHS tapes to class.
• Students recorded their sales conversations from a single camera view.
• Mike could review the recordings, while students could also watch themselves and learn from their performance.
• As recording technology changed, the process moved from VHS to digital.
• Generative AI has now created another way for students to practice sales conversations.

• Mike's main use of AI is giving students a chance to practice cold calls.
• Students prepare before starting the conversation:
• Choose a product or topic to sell.
• Define who they are and what they are selling.
• Build a value proposition.
• Identify three or four selling points.
• Prepare for likely objections and responses.
• Students use a shared AI prompt so the exercise is consistent across the class.
• The goal is to get a meeting or earn the opportunity to make a presentation, rather than close the sale.

• Mike can instruct the AI buyer to be more or less resistant.
• A more resistant buyer forces students to work harder during the conversation.
• In one exercise, students had to sell their degree to an AI buyer that was instructed to push back.
• The resistance made students work harder and gave them more practice handling difficult conversations.
• Students can also practice privately instead of making their first attempt in front of their classmates.

• Mike also connected AI role-play to research around empathy in sales.
• Students completed sales calls and then repeated the exercise using more empathetic language.
• This gave them a chance to compare their approaches and think about how they communicate with buyers.
• The exercise shows how AI can create repeated practice around specific sales skills.

• Not every student has the same access to sales or interview experience.
• Mike teaches students in Northwest Kansas, including students who may have fewer opportunities to practice professional conversations outside the classroom.
• AI gives students another way to practice regardless of their location.
• They can make mistakes, review what happened, and try again without needing another person available for every practice session.

• Mike does not see AI as a replacement for real sales conversations.
• Students still practice with other people in class.
• AI provides another practice environment, but students still need to learn how to respond to real people.
• Mike also stresses the importance of trust.
• Students can recognize when AI is being used poorly.
• They need to know the technology is helping them learn, not simply making the professor's work easier.

• Mike learned an important lesson when he first demonstrated the AI exercise himself.
• He had not prepared enough and found that the demonstration was harder than expected.
• His advice to other professors is simple: practice the assignment yourself before giving it to students.
• Test the prompts, work through the exercise, and make changes based on what happens.

Popular quote: “I think you definitely have to figure out where’s the best place and don’t become over-reliant on it.”

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