Effective Work Samples to Evaluate AI in Competitive Product Intelligence Skills

In today's rapidly evolving marketplace, companies need professionals who can leverage artificial intelligence to gain competitive advantages through product intelligence. The intersection of AI and competitive product intelligence represents a specialized skill set that combines technical AI knowledge with strategic business acumen. Professionals in this space must be able to design AI-driven data collection systems, analyze competitive product features, identify market trends, and translate complex data into actionable business recommendations.

Evaluating candidates for roles requiring AI in competitive product intelligence skills presents unique challenges. Traditional interviews often fail to reveal a candidate's practical abilities in applying AI tools to real-world competitive intelligence scenarios. Technical knowledge alone isn't sufficient—candidates must demonstrate judgment in selecting appropriate AI approaches, interpreting results, and communicating insights effectively to stakeholders.

Work samples provide a window into how candidates actually approach AI-driven competitive intelligence tasks. They reveal not just technical proficiency but also critical thinking, problem-solving methodology, and business acumen. By observing candidates working through realistic scenarios, hiring managers can assess their ability to balance technical sophistication with practical business value.

The following four activities are designed to evaluate different dimensions of AI in competitive product intelligence skills. They range from strategic planning to tactical implementation, testing candidates' abilities to design AI systems, evaluate tools, analyze competitive products, and develop strategic recommendations. Each activity includes guidance for both the company and the candidate, ensuring a structured evaluation process that yields meaningful insights about candidate capabilities.

Activity #1: Competitive Intelligence Data Collection and AI Analysis Plan

This activity assesses a candidate's ability to design a comprehensive strategy for gathering competitive product intelligence using AI tools. It reveals their understanding of data sources, AI capabilities, and strategic planning skills. The exercise tests whether candidates can create a structured approach to competitive intelligence that balances technical feasibility with business objectives.

Directions for the Company:

• Provide the candidate with a brief on your company's product and 2-3 key competitors.
• Include information about your current competitive intelligence challenges and objectives.
• Allocate 45-60 minutes for this exercise.
• Prepare a simple template with sections for data sources, AI tools/techniques, implementation timeline, and expected insights.
• Have a technical team member and a product/business stakeholder present to evaluate different aspects of the plan.

Directions for the Candidate:

• Design a comprehensive plan for collecting and analyzing competitive product intelligence using AI.
• Identify specific data sources (public websites, social media, app stores, review sites, etc.) that would provide valuable competitive insights.
• Specify which AI techniques or tools you would employ (NLP, sentiment analysis, image recognition, etc.) and why.
• Outline how you would implement this system, including approximate timelines and resource requirements.
• Describe the types of insights you expect to generate and how they would inform product strategy.
• Be prepared to present your plan in 10-15 minutes, followed by Q&A.

Feedback Mechanism:

• The interviewer should provide feedback on one strength of the plan (e.g., "Your approach to using sentiment analysis on customer reviews was particularly innovative") and one area for improvement (e.g., "The data collection strategy might benefit from considering alternative sources").
• Give the candidate 5-10 minutes to revise their approach based on the improvement feedback, focusing specifically on that aspect of the plan.
• Observe how receptive the candidate is to feedback and how effectively they incorporate it into their revised approach.

Activity #2: AI Tool Evaluation for Competitive Intelligence

This exercise tests a candidate's ability to critically evaluate AI tools for competitive intelligence purposes. It reveals their technical understanding of AI capabilities, their ability to match tools to business needs, and their practical approach to tool selection. This skill is crucial for ensuring that companies invest in the right AI technologies for their competitive intelligence efforts.

Directions for the Company:

• Create a scenario where your company needs to select an AI tool for competitive product intelligence.
• Provide descriptions of 3-4 fictional AI tools with different capabilities, strengths, and weaknesses (or use real tools if appropriate).
• Include information about your company's budget constraints, technical environment, and specific competitive intelligence needs.
• Prepare evaluation criteria that the candidate should consider.
• Allow 30-45 minutes for this exercise.

Directions for the Candidate:

• Review the descriptions of available AI tools for competitive intelligence.
• Create an evaluation framework with criteria that are important for selecting the right tool (e.g., technical capabilities, ease of integration, cost, scalability, accuracy).
• Score each tool against your evaluation criteria, providing justification for your ratings.
• Make a final recommendation on which tool(s) to adopt, explaining your reasoning.
• Identify potential implementation challenges and how you would address them.
• Prepare a brief presentation (5-10 minutes) of your evaluation and recommendation.

Feedback Mechanism:

• Provide feedback on one strong aspect of the candidate's evaluation (e.g., "Your consideration of data privacy implications was thorough") and one area that could be improved (e.g., "The evaluation might benefit from more consideration of long-term scalability").
• Ask the candidate to spend 5 minutes revising their recommendation based on the improvement feedback.
• Note how well the candidate balances technical and business considerations in their evaluation.

Activity #3: Competitive Product Feature Analysis Using AI

This activity assesses a candidate's ability to apply AI techniques to analyze competitive product features. It tests their technical skills in data analysis, their understanding of product dynamics, and their ability to extract meaningful insights from complex data. This exercise reveals how candidates bridge the gap between AI capabilities and practical product intelligence.

Directions for the Company:

• Prepare a dataset of product features and customer feedback for your product and 2-3 competitors.
• The dataset should include product specifications, customer reviews, ratings, and social media mentions.
• If using real data is not possible, create a simplified mock dataset that reflects realistic product comparisons.
• Provide access to basic analysis tools (spreadsheet software, Python notebook, or similar).
• Allow 60-90 minutes for this exercise.

Directions for the Candidate:

• Analyze the provided dataset to identify key competitive advantages and disadvantages of each product.
• Apply appropriate analytical techniques to extract patterns and insights from the data.
• Identify which features drive positive and negative customer sentiment for each product.
• Create a competitive positioning map based on your analysis.
• Recommend 2-3 specific product improvements that would strengthen competitive position.
• Explain which AI techniques could enhance this analysis if you had more time and resources.
• Prepare a 10-15 minute presentation of your findings and recommendations.

Feedback Mechanism:

• Provide feedback on one strength of the analysis (e.g., "Your identification of the correlation between feature X and customer satisfaction was insightful") and one area for improvement (e.g., "The analysis could benefit from more segmentation of customer feedback by user type").
• Give the candidate 10-15 minutes to refine one aspect of their analysis based on the improvement feedback.
• Evaluate how the candidate balances depth of technical analysis with clarity of business implications.

Activity #4: AI-Driven Competitive Intelligence Strategic Recommendations

This exercise evaluates a candidate's ability to translate AI-derived competitive intelligence into strategic business recommendations. It tests their strategic thinking, business acumen, and communication skills. The activity reveals whether candidates can bridge the gap between technical insights and actionable business strategy.

Directions for the Company:

• Create a scenario where AI analysis has uncovered specific competitive intelligence insights.
• Prepare a brief that includes:
• Key findings from AI analysis of competitor products
• Market trends identified through AI
• Customer sentiment analysis results
• Competitive positioning data
• Include some ambiguity and conflicting data points to test the candidate's judgment.
• Allow 45-60 minutes for preparation.

Directions for the Candidate:

• Review the AI-derived competitive intelligence provided.
• Identify the most significant insights and opportunities revealed by the data.
• Develop 3-5 strategic recommendations based on the competitive intelligence.
• For each recommendation:
• Explain the supporting evidence from the AI analysis
• Outline expected business impact
• Identify potential risks and how to mitigate them
• Suggest implementation approach and timeline
• Prepare a 15-minute executive presentation of your recommendations.
• Be prepared to defend your recommendations and explain how you interpreted the AI-derived insights.

Feedback Mechanism:

• Provide feedback on one strength of the recommendations (e.g., "Your strategy for addressing the competitive gap in feature X was well-supported by the data") and one area for improvement (e.g., "The recommendations could benefit from more consideration of resource constraints").
• Ask the candidate to spend 10 minutes refining one of their recommendations based on the improvement feedback.
• Evaluate how well the candidate translates technical insights into business value and how they handle ambiguity in the data.

Frequently Asked Questions

How technical should these exercises be? Should candidates need to code or use specific AI tools?

These exercises are designed to test applied AI knowledge in competitive intelligence rather than pure technical skills. While candidates should understand AI concepts and applications, the focus is on how they would use AI strategically. For more technical roles, you can modify the exercises to include actual coding or tool usage, but for most competitive intelligence roles, conceptual understanding and strategic application are more important.

What if our company doesn't have real competitive data to share with candidates?

You can create simplified mock data that represents realistic competitive scenarios without revealing sensitive information. The exercises are designed to test thinking processes rather than specific knowledge about your competitors. Alternatively, you can use publicly available information about products in adjacent markets as a proxy.

How do we evaluate candidates who have different approaches to these exercises?

Focus on the quality of thinking rather than specific approaches. Strong candidates will demonstrate clear reasoning, connect AI capabilities to business needs, show awareness of limitations, and communicate effectively. Different approaches can be equally valid if well-justified. Use the evaluation criteria of technical understanding, strategic thinking, practical feasibility, and communication clarity.

Should we expect candidates to have experience with all types of AI mentioned in these exercises?

No, candidates may have deeper experience with some AI applications than others. Look for candidates who understand the capabilities and limitations of different AI approaches, even if they haven't directly implemented all of them. Strong candidates will be transparent about their areas of expertise and show curiosity about new applications.

How can we adapt these exercises for remote interviews?

These exercises work well in remote settings. Provide materials in advance via email or shared documents. Use video conferencing for presentations and discussions. Consider collaborative tools like Miro or Google Docs for real-time collaboration. Allow slightly more time for remote exercises to account for potential technical issues.

What if a candidate has limited experience with competitive intelligence but strong AI skills?

Focus the evaluation on their ability to apply AI concepts to competitive intelligence scenarios. Strong analytical thinking and learning agility can compensate for limited domain experience. Look for candidates who ask insightful questions about the competitive context and show they can quickly grasp the business implications of technical capabilities.

AI in competitive product intelligence represents a powerful capability for companies seeking to gain market advantages. By implementing these work samples in your hiring process, you'll be able to identify candidates who can truly bridge the gap between AI technology and strategic business intelligence. The right talent in this space can transform how your company understands competitors, positions products, and identifies market opportunities.

For more resources to enhance your hiring process, explore Yardstick's suite of AI-powered tools, including our AI Job Descriptions, AI Interview Question Generator, and AI Interview Guide Generator.

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