Effective Work Samples for Evaluating AI Sales Call Analysis and Coaching Skills

The ability to analyze sales calls using AI tools and provide effective coaching based on those insights has become a critical skill in modern sales organizations. As AI-powered conversation intelligence platforms become more prevalent, the need for professionals who can interpret this data and translate it into actionable coaching has grown exponentially. Companies investing in these technologies need team members who can not only understand the technical aspects of AI analysis but also apply those insights to improve sales performance.

Evaluating candidates for roles requiring AI sales call analysis skills presents unique challenges. Traditional interviews often fail to reveal a candidate's actual ability to interpret AI-generated insights, identify coaching opportunities, and deliver effective feedback. Without practical assessment, organizations risk hiring individuals who understand the theory but struggle with real-world application.

Work samples and role plays provide a window into how candidates approach AI sales analysis and coaching in authentic scenarios. These exercises reveal critical thinking skills, coaching approaches, and the ability to translate complex data into actionable recommendations. They also demonstrate a candidate's communication style when delivering feedback—a crucial element of effective sales coaching.

The following work samples are designed to evaluate a candidate's proficiency in analyzing AI-generated sales call data, identifying coaching opportunities, and delivering effective feedback. Each exercise simulates real-world scenarios that professionals in this field encounter regularly, providing a comprehensive assessment of the skills required for success in roles involving AI sales call analysis and coaching.

Activity #1: AI Call Analysis and Coaching Opportunity Identification

This activity assesses a candidate's ability to review AI-analyzed sales call data, identify key coaching opportunities, and prioritize areas for improvement. This skill is fundamental for anyone working with AI sales tools, as it demonstrates their capacity to interpret machine learning insights and translate them into actionable coaching points.

Directions for the Company:

• Provide the candidate with a sample AI sales call analysis dashboard or report showing metrics for 3-5 different sales calls (conversion rates, talk-to-listen ratio, question rate, filler word usage, competitor mentions, etc.).
• Include transcripts with AI-highlighted moments for each call (objections, feature discussions, pricing conversations).
• Allow 30 minutes for the candidate to review the materials and prepare their analysis.
• The ideal format is to provide actual screenshots from your AI sales tool with anonymized data, or create a simplified version that resembles your platform.
• Ensure the sample data contains a mix of obvious issues and more subtle coaching opportunities.

Directions for the Candidate:

• Review the provided AI sales call analysis data and transcripts.
• Identify the top three coaching opportunities across all calls, explaining why you've prioritized these areas.
• For each opportunity, note specific moments in the calls (with timestamps or transcript references) that illustrate the issue.
• Prepare to explain how you would approach coaching the sales representative on each identified opportunity.
• Be prepared to discuss how you differentiate between AI-flagged issues that require immediate coaching versus those that may be less critical.

Feedback Mechanism:

• After the candidate presents their analysis, provide feedback on one aspect they did particularly well (e.g., insightful prioritization, nuanced understanding of the data).
• Offer one area for improvement (e.g., missed an important pattern, over-relied on AI flags without context).
• Give the candidate 5-10 minutes to reconsider their analysis based on the feedback and share any adjustments they would make to their coaching priorities.

Activity #2: Live Coaching Role Play Based on AI Insights

This exercise evaluates the candidate's ability to deliver effective coaching based on AI-generated insights. It tests not only their understanding of sales techniques but also their communication skills, empathy, and ability to translate data into actionable guidance.

Directions for the Company:

• Create a scenario where the candidate will coach a "sales rep" (played by an interviewer) based on AI call analysis findings.
• Provide the candidate with:
• A one-page AI analysis summary of the "rep's" recent calls highlighting 2-3 specific issues (e.g., not addressing objections effectively, rushing through discovery, poor closing techniques)
• A brief recording (2-3 minutes) of a sales call demonstrating these issues
• Background on the rep's experience level and previous coaching
• Allow the candidate 20 minutes to prepare their coaching approach.
• The role-playing interviewer should be prepared to respond realistically, occasionally showing resistance or asking clarifying questions.

Directions for the Candidate:

• Review the AI analysis and call recording to understand the rep's strengths and areas for improvement.
• Prepare a 15-minute coaching session that:
• Establishes rapport with the rep
• References specific moments from the call (using timestamps or quotes)
• Provides actionable guidance on how to improve
• Includes practice or role play of a better approach
• During the coaching session, be prepared to adapt based on the rep's responses.
• Focus on being specific and actionable rather than general or theoretical.
• Balance positive reinforcement with constructive feedback.

Feedback Mechanism:

• After the coaching session, provide feedback on one aspect they did particularly well (e.g., effective use of specific examples, strong questioning technique).
• Offer one area for improvement (e.g., could have been more direct about a critical issue, missed an opportunity to demonstrate a technique).
• Allow the candidate 5 minutes to re-do a portion of the coaching session implementing the feedback.

Activity #3: Developing a Data-Driven Coaching Plan

This activity assesses the candidate's ability to analyze trends in AI call data across a team and develop a structured coaching plan. It evaluates strategic thinking, planning skills, and the ability to connect AI insights to long-term performance improvement.

Directions for the Company:

• Provide the candidate with:
• Team-level AI call analysis data showing performance trends across 5-8 sales reps over 3 months
• Key metrics highlighted by the AI (e.g., question rate, talk time, objection handling success, closing techniques)
• Information about team goals and current challenges
• Allow 45 minutes for the candidate to review the materials and develop their plan.
• Create data that shows both team-wide patterns and individual outliers to test the candidate's ability to balance broad initiatives with targeted coaching.

Directions for the Candidate:

• Analyze the provided team data to identify:
• 2-3 team-wide trends that require coaching attention
• 1-2 individual performance outliers (both positive and negative)
• Correlations between specific behaviors and sales outcomes
• Develop a 30-day coaching plan that includes:
• Team-wide initiatives based on common development areas
• Individual coaching approaches for specific reps
• Methods to leverage high performers as examples
• Specific metrics to track for measuring improvement
• A timeline for implementation and follow-up
• Prepare to present your plan and rationale in a 15-minute presentation.

Feedback Mechanism:

• After the presentation, provide feedback on one strong element of the plan (e.g., creative approach to a specific challenge, excellent prioritization).
• Offer one suggestion for improvement (e.g., overlooked an important trend, plan lacks specificity in implementation).
• Give the candidate 10 minutes to revise one section of their plan based on the feedback.

Activity #4: AI Tool Evaluation and Optimization

This exercise tests the candidate's technical understanding of AI sales analysis tools and their ability to optimize these systems for better coaching insights. It evaluates both strategic thinking about technology implementation and tactical knowledge of AI capabilities.

Directions for the Company:

• Create a scenario where your organization is either:
• Evaluating a new AI sales call analysis tool, or
• Looking to optimize the configuration of your existing platform
• Provide the candidate with:
• Documentation about the tool's capabilities and configuration options
• Current challenges the sales team is facing
• Examples of the types of insights currently being generated (or desired)
• Allow 30 minutes for review and preparation.
• If possible, provide access to a demo environment of the actual tool you use.

Directions for the Candidate:

• Review the provided materials to understand the tool's capabilities and current implementation.
• Identify 3-5 specific recommendations for:
• Key metrics or conversation elements the AI should track
• Custom categories or topics to configure for your specific sales process
• Alert thresholds or notification settings for coaching moments
• Integration points with other sales tools or processes
• Training requirements for managers and reps
• For each recommendation, explain:
• The specific coaching benefit it would provide
• How it aligns with the sales team's goals and challenges
• Implementation considerations or potential obstacles
• Prepare to present your recommendations in a 15-minute discussion.

Feedback Mechanism:

• After the presentation, highlight one particularly valuable recommendation the candidate made.
• Provide one area where their approach could be enhanced or a consideration they may have missed.
• Ask the candidate to spend 5 minutes elaborating on how they would address the feedback and refine their most important recommendation.

Frequently Asked Questions

How should we adapt these exercises if we're using a specific AI sales tool that the candidate may not be familiar with?

Focus on evaluating the candidate's analytical approach rather than tool-specific knowledge. Provide a brief overview of your platform's capabilities and interface before the exercise. The core skills of interpreting data, identifying coaching opportunities, and delivering effective feedback transfer across different tools. You can also ask candidates about their experience with similar tools and how they would approach learning a new system.

What if we don't yet have AI call analysis tools implemented but want to hire someone who can help us select and implement one?

Modify Activity #4 to focus more heavily on tool selection criteria and implementation planning. Provide information about your current sales process, challenges, and goals, then ask candidates to outline what they would look for in an AI analysis tool and how they would approach implementation. You can also adapt Activity #3 to focus on how they would establish baseline metrics and a coaching framework in preparation for AI tool adoption.

How do we evaluate candidates who have coaching experience but limited exposure to AI-powered sales tools?

Balance the assessment between technical understanding and coaching ability. For candidates with strong coaching backgrounds but limited AI experience, pay particular attention to how quickly they grasp the value of different metrics and insights in Activities #1 and #3. Strong coaches often transfer their skills effectively to AI-enhanced environments if they demonstrate analytical thinking and openness to technology-driven insights.

Should we customize these exercises based on our specific sales methodology?

Yes, tailoring these activities to reflect your sales methodology will provide more relevant insights. Modify the scenarios, call examples, and metrics to align with your specific approach, whether that's Challenger, SPIN, MEDDIC, or another framework. This customization helps evaluate how well candidates can apply AI insights within your particular sales context and coaching philosophy.

How much time should we allocate for these exercises in our interview process?

Plan for approximately 1.5-2 hours to conduct one of these exercises thoroughly, including preparation time, the activity itself, feedback, and discussion. Rather than trying to fit all four activities into your process, select the 1-2 most relevant to the specific role and your current needs. You might use Activity #1 or #2 for an initial assessment and save Activity #3 or #4 for final-round candidates.

Can these exercises be conducted remotely?

All four activities can be effectively adapted for remote interviews. For remote sessions, ensure candidates receive materials in advance through secure sharing methods, use video conferencing with screen sharing capabilities, and consider extending preparation time slightly to account for potential technical issues. Recording the sessions (with permission) can be particularly valuable for evaluating coaching style and communication skills afterward.

The ability to effectively analyze AI-generated sales call data and translate those insights into impactful coaching represents a significant competitive advantage in today's sales environment. By incorporating these practical work samples into your hiring process, you can identify candidates who not only understand the technical aspects of AI sales tools but can also apply those insights to drive meaningful performance improvements.

As AI continues to transform sales enablement and coaching, the professionals who can bridge the gap between technology and human development will become increasingly valuable. These exercises help you identify those rare individuals who combine analytical thinking, coaching expertise, and technical understanding—the key ingredients for success in roles focused on AI sales call analysis and coaching.

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