This module focuses on how sales representatives deliver customer demonstrations that reinforce solution relevance and business value. You will examine how effective demos use discovery insights to connect solution capabilities to customer priorities, challenges, and desired outcomes rather than becoming product tours or feature walkthroughs. Using customer-outcome framing approaches such as Working Backwards, you will learn how to select relevant content, organize a clear demo flow, explain business impact, and avoid unnecessary technical detail. Through practical scenarios, you will explore how focused demonstrations can increase clarity, relevance, customer engagement, and momentum. By the end of the module, you will understand how to plan and deliver structured, customer-focused demonstrations aligned to AWS solution value.

This module focuses on how to explain AWS pricing and return on investment (ROI) in a way that supports customer decision-making. ROI compares what a customer invests with the value or measurable benefit they expect to gain. You will explore how usage-based pricing affects cost, how key cost drivers and trade-offs can be explained clearly, and how estimated spend can be connected to customer outcomes without relying on complex financial models. Through practical scenarios, you will examine how structured pricing and ROI conversations can build understanding and confidence by making assumptions, cost implications, and potential value easier to evaluate. By the end of the module, you will be able to explain AWS pricing at a high level, communicate ROI in practical terms, and support customer conversations about cost and value.

This module focuses on how sales representatives use AI-assisted tools to support preparation, communication, and follow-up across the sales workflow. You will examine how AI can generate and refine content such as discovery questions, follow-up messages, and objection responses while accelerating preparation and improving consistency without replacing judgment or decision-making. Within AWS sales environments, AI tools can organize information, generate drafts, and suggest structured outputs based on customer context, and you will explore how these capabilities are applied in practice. The module also focuses on evaluating AI-generated outputs for accuracy, relevance, tone, and alignment with customer needs. You will examine common issues such as generic outputs, incorrect assumptions, and misaligned messaging, and use practical scenarios to explore how AI-assisted workflows can improve efficiency when used appropriately and introduce risk when over-relied on or insufficiently reviewed. By the end of the module, you will understand how to use AI tools to support sales activities and how to evaluate and refine outputs for quality and relevance.

This module focuses on how sales representatives use AI-assisted tools to prepare for customer interactions. You will examine how AI can generate structured outputs such as discovery questions, meeting notes, and draft communications, helping improve preparation speed and consistency while still requiring human judgment for relevance and accuracy. Within AWS sales environments, AI tools can organize customer information and generate initial drafts. The module emphasizes that effective use depends on how requests are structured, with clear context and intent helping produce more useful outputs and reduce unnecessary revision. Through practical scenarios, you will explore how AI can support preparation as a structured assistant rather than replace thinking. By the end of the module, you will understand how to use AI tools for sales preparation and structure inputs to generate useful outputs.