Essential Work Samples to Evaluate AI Ad Copy and Performance Testing Skills

In today's digital marketing landscape, the ability to leverage AI for creating and testing ad copy variations has become a critical competitive advantage. Professionals skilled in AI ad copy variation and performance testing combine creative copywriting with data-driven optimization, resulting in higher conversion rates and lower acquisition costs. However, identifying candidates who truly possess these specialized skills can be challenging through traditional interviews alone.

Work samples provide a window into how candidates approach real-world AI ad copy challenges. Rather than relying on candidates' self-reported abilities, these exercises reveal their actual process for using AI tools to generate creative variations, their methodology for structuring meaningful tests, and their analytical approach to interpreting results. This practical demonstration offers far more insight than hypothetical discussions about what they might do in certain scenarios.

The most effective AI ad copy specialists balance creative intuition with analytical rigor. They understand how to prompt AI systems effectively, recognize which variations are worth testing, design statistically valid experiments, and extract actionable insights from performance data. These nuanced skills are difficult to assess through resume screening or standard behavioral interviews.

By implementing the following work samples, you'll be able to evaluate candidates' hands-on capabilities with AI copywriting tools, their strategic thinking around test design, their analytical skills for performance evaluation, and their ability to continuously refine approaches based on data. These exercises simulate the actual day-to-day responsibilities of the role, providing a reliable predictor of on-the-job performance.

Activity #1: AI-Assisted Ad Copy Generation

This exercise evaluates a candidate's ability to use AI tools to generate effective ad copy variations while maintaining brand voice and targeting specific customer segments. Success in this role requires not just technical familiarity with AI copywriting tools, but the strategic judgment to guide these tools toward producing high-quality, on-brand content that addresses specific marketing objectives.

Directions for the Company:

• Provide the candidate with your brand guidelines, a specific product/service to advertise, target audience information, and the ad platform (e.g., Facebook, Google, LinkedIn).
• Share access to an AI copywriting tool of your choice (e.g., ChatGPT, Copy.ai, Jasper) or allow them to use their preferred tool.
• Specify the ad format requirements (character limits, number of headlines/descriptions needed).
• Allocate 45-60 minutes for this exercise.
• Prepare a brief on a recent successful campaign as context.

Directions for the Candidate:

• Review the brand guidelines and campaign brief provided.
• Using the AI tool, generate 3-5 distinct ad copy variations that maintain brand voice while appealing to the target audience.
• For each variation, document:
• The prompt you used to guide the AI
• Any modifications you made to the AI-generated content and why
• The strategic thinking behind each variation (what aspect of the value proposition it emphasizes)
• Which customer pain points or desires each variation addresses
• Prepare a brief explanation of how you would set up these variations for testing.

Feedback Mechanism:

• The interviewer should provide feedback on one strength (e.g., "Your variations effectively maintained brand voice while exploring different angles") and one area for improvement (e.g., "The calls-to-action could be more compelling").
• Give the candidate 10 minutes to revise one of their variations based on the feedback, observing how they incorporate the suggestions and whether they can quickly adapt their approach.

Activity #2: A/B Test Design Strategy

This activity assesses the candidate's ability to design a methodologically sound testing strategy for ad copy variations. It reveals their understanding of statistical significance, test duration, audience segmentation, and how to isolate variables for meaningful results—all critical skills for optimizing ad performance through systematic testing.

Directions for the Company:

• Provide a scenario with a specific marketing objective (e.g., increasing demo sign-ups for a SaaS product).
• Include information about typical ad performance metrics: current click-through rates, conversion rates, average daily impressions, and cost per acquisition.
• Supply details about the available budget, timeline constraints, and target audience segments.
• Prepare a template or framework for the test plan if desired.
• Allow 45-60 minutes for this exercise.

Directions for the Candidate:

• Design a comprehensive A/B testing plan for evaluating AI-generated ad copy variations.
• Your plan should include:
• Clear hypothesis statements for what you're testing and why
• Sample size calculations and estimated test duration based on provided metrics
• Methodology for ensuring statistical significance
• Approach to audience segmentation or randomization
• Primary and secondary success metrics
• Control variables to ensure test validity
• Potential confounding factors and how you'll address them
• Create a timeline visualization showing the key phases of your testing approach.
• Explain how you would use AI tools to iterate on the test based on early results.

Feedback Mechanism:

• The interviewer should highlight one strength of the testing strategy (e.g., "Your approach to audience segmentation ensures reliable results") and one area for improvement (e.g., "The sample size calculation doesn't account for weekend performance fluctuations").
• Allow the candidate 10-15 minutes to refine their approach based on the feedback, noting how they incorporate statistical principles and practical constraints into their revised plan.

Activity #3: Performance Analysis and Optimization

This exercise evaluates a candidate's analytical abilities and strategic thinking when interpreting ad performance data. It tests their skill in extracting meaningful insights from complex datasets and translating those insights into actionable optimization strategies using AI tools—essential capabilities for continuous performance improvement.

Directions for the Company:

• Prepare a mock dataset showing performance metrics for 5-8 ad variations across a 2-week period. Include metrics like impressions, clicks, CTR, conversions, CPA, and ROAS.
• Intentionally include some interesting patterns in the data (e.g., variations that perform well initially but decline, differences between audience segments, day-of-week effects).
• Provide context about the campaign objectives and KPIs.
• Include information about the AI tools available for optimization.
• Allow 60 minutes for this exercise.

Directions for the Candidate:

• Analyze the provided performance data for the ad variations.
• Identify the top-performing and underperforming variations.
• Create a brief presentation (3-5 slides) that includes:
• Key performance insights and trends you've identified
• Possible explanations for performance differences between variations
• Recommendations for optimizing the campaign, including:
  • Which variations to scale, modify, or pause
  • New variations to test based on what you've learned
  • How you would use AI to generate these new variations
  • Budget allocation recommendations
• Expected impact of your recommendations on key metrics
• Be prepared to explain your analytical process and how you prioritized different insights.

Feedback Mechanism:

• The interviewer should highlight one strength of the analysis (e.g., "Your analysis effectively identified the correlation between ad copy length and conversion rate") and one area for improvement (e.g., "Your recommendations could more explicitly connect to the patterns in the data").
• Give the candidate 15 minutes to refine one aspect of their analysis or recommendations based on the feedback, observing how they incorporate new perspectives and whether they can quickly adapt their analytical approach.

Activity #4: AI-Assisted Troubleshooting for Underperforming Ads

This activity assesses a candidate's problem-solving abilities when faced with underperforming ad campaigns. It tests their diagnostic skills, creative thinking, and ability to leverage AI tools to identify and address root causes of poor performance—a frequent and high-value responsibility in this role.

Directions for the Company:

• Create a scenario involving an underperforming ad campaign with specific symptoms (e.g., high CTR but low conversion rate, or declining performance over time).
• Provide relevant campaign assets: the current ad copy, landing page screenshots, audience targeting parameters, and performance metrics over time.
• Include competitive examples if relevant.
• Make available information about AI tools that could assist in the troubleshooting process.
• Allow 45-60 minutes for this exercise.

Directions for the Candidate:

• Review the underperforming campaign materials and metrics.
• Develop a structured troubleshooting approach that:
• Identifies 3-5 potential causes for the poor performance
• Outlines a methodology for testing each hypothesis
• Proposes specific AI-assisted solutions for each potential issue
• Create a recovery plan that includes:
• New AI-generated ad copy variations that address the identified issues
• Targeting or placement adjustments
• Testing methodology to validate your solutions
• Timeline for implementation and evaluation
• Expected performance improvements with rationale
• Document how you would use AI tools at each stage of the troubleshooting and recovery process.

Feedback Mechanism:

• The interviewer should highlight one strength of the troubleshooting approach (e.g., "Your systematic elimination of variables would efficiently identify the root cause") and one area for improvement (e.g., "Your solution doesn't fully address the audience-message mismatch you identified").
• Allow the candidate 15 minutes to refine their recovery plan based on the feedback, noting how they incorporate the suggestions and whether they demonstrate adaptability in their problem-solving approach.

Frequently Asked Questions

How long should we allocate for these work samples in our interview process?

Each exercise requires 45-60 minutes for completion, plus 10-15 minutes for feedback and revision. We recommend selecting 1-2 exercises most relevant to your specific needs rather than attempting all four in a single interview session. You might consider having candidates complete one exercise as a take-home assignment before bringing them in for an in-person exercise.

Should we provide real company data for these exercises?

While using real data creates authenticity, it's often better to use modified or synthetic data that resembles your actual campaigns but doesn't reveal sensitive information. This approach protects your business while still testing relevant skills. Ensure the mock data contains enough complexity and patterns to enable meaningful analysis.

What if candidates don't have experience with our specific AI copywriting tools?

Focus on evaluating their process and strategic thinking rather than tool-specific knowledge. Most skilled professionals can quickly adapt to new tools if they understand the underlying principles. Consider allowing candidates to use tools they're familiar with, or provide a brief orientation to your preferred tools before the exercise.

How should we evaluate candidates who take different approaches to these exercises?

Establish evaluation rubrics that focus on the quality of thinking rather than adherence to a specific "correct" approach. Look for evidence of strategic thinking, analytical rigor, creativity, and adaptability. Different approaches can be equally valid if they demonstrate sound methodology and address the core objectives of the exercise.

Should we expect candidates to be experts in both the AI and copywriting aspects of these exercises?

The ideal candidate will have strengths in both areas, but you may find candidates who lean more toward technical AI expertise or creative copywriting skills. Consider your team's current composition and which skill set would most complement existing strengths. The exercises should help you identify where candidates fall on this spectrum.

How can we adapt these exercises for remote interviews?

These exercises work well in remote settings using screen sharing and collaborative tools. For the analysis exercise, provide the data in advance. For copywriting exercises, use collaborative documents where you can observe their process in real-time. Video conferencing tools with breakout rooms allow candidates to work independently before presenting their results.

The ability to effectively leverage AI for ad copy creation and performance testing represents a significant competitive advantage in today's digital marketing landscape. By incorporating these practical work samples into your hiring process, you'll be able to identify candidates who not only understand the theoretical aspects of AI-assisted advertising but can actually execute and optimize campaigns that drive measurable business results.

Finding professionals who can balance creative copywriting with data-driven optimization is challenging but essential for modern marketing teams. These exercises provide a comprehensive evaluation of the technical, analytical, and strategic skills required for success in this specialized field.

For more resources to enhance your hiring process, explore Yardstick's suite of AI-powered hiring tools, including our AI job descriptions generator, interview question generator, and comprehensive interview guide creator.

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