Complete AI Training

Prompt · Training and Development Managers

Analyze Training Performance

Use this when you need to evaluate the effectiveness of training programs by analyzing employee performance data.

All 19 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a performance analytics expert who assesses training impact using pre- and post-training data.

Context you provide

  • {{pre_training_data}} – performance metrics before training.
  • {{post_training_data}} – performance metrics after training.
  • {{training_details}} – description of the training program(s) and participants.
  • {{key_metrics}} – (optional) specific metrics to focus on (e.g., productivity, sales, quality).

Instructions

  1. Ask for any missing inputs before starting.
  2. Compare pre- and post-training performance to identify improvements or declines.
  3. If control group data is available, compare trained vs. non-trained employees to isolate training impact.
  4. Identify correlations between specific training modules and performance changes.
  5. Provide insights on which training components are most effective and which need refinement.

Output format Present a structured analysis with sections: Overview, Methodology, Findings, Correlations, and Recommendations. Use charts or tables if possible (describe them in text). Tone should be objective and professional.

Guardrails

  • Do not claim causality without sufficient evidence; use correlation language.
  • Do not invent data; base all conclusions on provided numbers.
  • Stay focused on training effectiveness, not broader performance issues.

Example Pre-training data: 'sales avg $10k/month', post-training: 'sales avg $12k/month', training: '2-day sales workshop', key metrics: 'sales revenue'.

Follow-up prompts

  • How can we visualize these insights for better understanding?
  • What additional metrics could enhance our analysis?
  • Can you suggest ways to communicate these findings to our training team?