Effective Work Samples for Evaluating AI Sales Coaching Skills

The intersection of artificial intelligence and sales coaching represents a transformative frontier in sales performance management. As organizations increasingly adopt AI-powered tools to analyze sales conversations, identify coaching opportunities, and drive performance improvements, the need for professionals who can effectively leverage these technologies becomes critical. These specialists must possess a unique blend of sales expertise, coaching acumen, and technological fluency to translate AI-generated insights into actionable coaching strategies.

Evaluating candidates for AI sales coaching roles presents unique challenges. Traditional interviews may reveal theoretical knowledge but often fail to demonstrate a candidate's practical ability to interpret AI data, deliver effective coaching based on those insights, or design performance improvement strategies. Without seeing these skills in action, hiring managers risk selecting candidates who understand concepts but struggle with real-world application.

Work samples and role plays provide a window into how candidates actually approach AI-driven sales coaching scenarios. They reveal not just what candidates know, but how they apply that knowledge to solve problems, communicate insights, and drive behavioral change among sales teams. These exercises demonstrate a candidate's ability to bridge the gap between technological capabilities and human performance improvement.

The following four activities are designed to evaluate key competencies required for success in AI sales coaching roles. They assess candidates' abilities to analyze AI-generated sales data, deliver coaching based on those insights, design comprehensive performance improvement programs, and effectively implement AI tools within existing sales processes. By observing candidates complete these exercises, hiring managers can make more informed decisions about which individuals possess the right combination of skills to excel in this specialized field.

Activity #1: AI Sales Call Analysis and Coaching Plan

This activity evaluates a candidate's ability to analyze AI-generated sales call data, identify coaching opportunities, and develop a structured coaching plan. Successful AI sales coaches must be able to interpret AI insights, prioritize coaching needs, and translate data into actionable development strategies. This exercise reveals how candidates connect technological insights to human performance improvement.

Directions for the Company:

• Provide the candidate with a sample AI-generated call analysis report for a fictional sales representative. This should include metrics like talk-to-listen ratio, question rate, filler word usage, interruption frequency, and AI-identified moments of interest (objection handling, discovery questions, etc.).
• Include a transcript excerpt with AI-highlighted areas of concern or opportunity.
• Allow the candidate 30 minutes to review the materials and prepare their coaching plan.
• Schedule a 20-minute session where the candidate presents their coaching approach.
• Prepare a role player to act as the sales representative during a portion of the exercise.

Directions for the Candidate:

• Review the AI-generated call analysis report and transcript provided.
• Identify 2-3 key coaching opportunities based on the data.
• Develop a structured coaching plan that includes:
• Specific behaviors to address
• Coaching approach for each behavior
• How you would use the AI data during the coaching conversation
• Measurable outcomes to track improvement
• Be prepared to role-play the first 5 minutes of your coaching conversation with the sales representative.

Feedback Mechanism:

• After the candidate presents their coaching plan and conducts the role play, provide feedback on one aspect they handled effectively and one area for improvement.
• Give the candidate 5 minutes to adjust their approach based on the feedback.
• Allow them to re-do a portion of the coaching conversation incorporating the feedback.

Activity #2: AI Tool Implementation Strategy

This exercise assesses a candidate's ability to strategically implement AI coaching tools within a sales organization. It evaluates their understanding of change management, technology adoption challenges, and how to align AI capabilities with sales performance objectives. This skill is crucial for ensuring AI tools deliver actual performance improvements rather than becoming unused technological investments.

Directions for the Company:

• Create a fictional scenario about a sales organization planning to implement an AI coaching platform.
• Include details about the organization's size, current coaching processes, sales team demographics, and specific performance challenges.
• Provide information about the AI platform's capabilities (call recording analysis, coaching recommendation engine, performance tracking, etc.).
• Allow the candidate 45 minutes to prepare their implementation strategy.
• Schedule a 25-minute presentation and Q&A session.

Directions for the Candidate:

• Review the scenario information provided.
• Develop a comprehensive 90-day implementation strategy that includes:
• Key phases of implementation
• Approach to gaining buy-in from sales leadership and representatives
• Training plan for managers and representatives
• Methods for measuring adoption and effectiveness
• Strategies for overcoming potential resistance
• How you would integrate the AI insights with existing coaching practices
• Prepare a 15-minute presentation of your strategy, leaving 10 minutes for questions.

Feedback Mechanism:

• After the presentation and Q&A, provide feedback on one strength of the implementation strategy and one area that could be improved.
• Give the candidate 10 minutes to revise one section of their implementation plan based on the feedback.
• Have them briefly explain how their revised approach addresses the feedback.

Activity #3: AI-Informed Coaching Role Play

This role play evaluates the candidate's ability to deliver effective coaching based on AI-generated insights. It assesses their coaching skills, ability to reference data appropriately, and effectiveness in driving behavioral change. This activity reveals how well candidates can translate technological insights into meaningful human interactions that improve performance.

Directions for the Company:

• Prepare a detailed AI analysis of a fictional sales representative's performance across multiple calls.
• Include both positive patterns (effective discovery questions, strong closing techniques) and areas for improvement (excessive talking, insufficient needs exploration, weak objection handling).
• Provide the candidate with this analysis 24 hours before the interview.
• Arrange for an experienced sales manager or trainer to play the role of the sales representative.
• Brief the role player on how to respond (initially somewhat defensive, but open to coaching if approached effectively).

Directions for the Candidate:

• Review the AI analysis provided for the fictional sales representative.
• Prepare for a 20-minute coaching session focusing on the most critical improvement opportunities.
• During the role play:
• Establish rapport and set the context for the coaching session
• Reference specific AI-identified patterns without making the conversation overly technical
• Use effective questioning techniques to gain the representative's perspective
• Collaboratively develop improvement strategies
• Establish clear next steps and follow-up mechanisms
• Be prepared to adapt your approach based on the representative's responses.

Feedback Mechanism:

• After the role play, provide feedback on one aspect of the coaching conversation that was particularly effective and one area that could be improved.
• Give the candidate 5 minutes to consider the feedback.
• Allow them to re-do a portion of the conversation (5 minutes) implementing the suggested improvement.

Activity #4: AI Sales Performance Trend Analysis and Program Design

This activity evaluates a candidate's ability to analyze broader AI-identified sales performance trends and design comprehensive improvement programs. It assesses analytical thinking, program design skills, and the ability to connect data insights to practical development initiatives. This exercise reveals how candidates approach systematic performance improvement rather than just individual coaching.

Directions for the Company:

• Create a fictional dataset showing AI-analyzed trends across a sales team of 20 representatives over 3 months.
• Include metrics like conversation quality scores, question rates, talk time ratios, objection handling effectiveness, and closing rates.
• Provide information about the team's current performance against targets and key business objectives.
• Allow the candidate 60 minutes to analyze the data and prepare their program design.
• Schedule a 30-minute presentation and discussion session.

Directions for the Candidate:

• Review the AI-generated performance data provided.
• Identify 3-4 key performance trends or opportunity areas across the team.
• Develop a comprehensive performance improvement program that includes:
• Specific performance objectives based on the data
• Team-wide training or development initiatives
• Individual coaching approaches for different performance profiles
• How AI tools would be used to measure progress
• Timeline and expected outcomes
• Prepare a 20-minute presentation of your analysis and program design, leaving 10 minutes for discussion.

Feedback Mechanism:

• After the presentation, provide feedback on one strength of the analysis and program design and one area that could be enhanced.
• Give the candidate 10 minutes to revise or expand on one element of their program based on the feedback.
• Have them explain how their revised approach improves the overall effectiveness of the program.

Frequently Asked Questions

How long should we allocate for these exercises during the interview process?

Each exercise requires different time allocations. Activity #1 needs about 50 minutes (30 for preparation, 20 for presentation). Activity #2 requires about 70 minutes (45 for preparation, 25 for presentation). Activity #3 needs approximately 30 minutes (20 for the role play, 10 for feedback and adjustment). Activity #4 requires about 90 minutes (60 for analysis and preparation, 30 for presentation). Consider spreading these across multiple interview stages rather than attempting all in one session.

Should we provide the AI data and scenarios ahead of time?

For Activities #1 and #4, providing the materials during the interview with dedicated preparation time works well. For Activity #3 (the coaching role play), providing materials 24 hours in advance is recommended as it mirrors real-world coaching scenarios where coaches review data before sessions. For Activity #2, you could go either way depending on how complex your scenario is.

What if we don't currently use AI coaching tools in our organization?

You can still conduct these exercises by creating fictional AI reports and insights based on what you believe would be valuable. The exercises evaluate a candidate's ability to translate data into coaching and performance improvement strategies, which is valuable even if you're just beginning your AI journey. In fact, these exercises may help you identify candidates who can help lead your AI implementation.

How should we evaluate candidates who have strong coaching skills but limited AI experience?

Focus on their ability to interpret the data provided and translate it into effective coaching approaches. Strong coaches who demonstrate curiosity about the AI insights and ask intelligent questions about the data may quickly adapt to using AI tools. Consider pairing such candidates with technical team members who can support the AI aspects while the coach develops those skills.

How can we make these exercises more relevant to our specific sales context?

Customize the AI reports and scenarios to reflect your industry, sales cycle, and typical challenges. Include terminology, objections, and selling scenarios that your team commonly encounters. If possible, anonymize actual call data from your organization to create realistic scenarios that directly relate to your sales environment.

Should we expect candidates to have experience with specific AI coaching platforms?

While experience with platforms like Gong, Chorus, or similar tools is beneficial, the core skill is the ability to interpret data and translate it into effective coaching. Focus on evaluating this fundamental capability rather than platform-specific knowledge, which can be learned. Ask candidates about any AI or analytics tools they've used for coaching to understand their technological adaptability.

The integration of artificial intelligence into sales coaching represents a significant opportunity to enhance sales performance through data-driven insights and targeted development. By using these work samples and role plays, you can identify candidates who not only understand AI's potential but can effectively leverage it to drive meaningful performance improvements. The ideal candidate will demonstrate the ability to bridge the technological and human elements of sales coaching, using AI as a tool to enhance rather than replace the critical human connections that drive sales success.

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