How CaseMaster AI Evaluates Case Interview Performance
CaseMaster AI evaluates your case interview performance by scoring structure, hypothesis, math, communication, and synthesis in real time. It analyzes your responses, identifies weaknesses, and provides detailed, skill-by-skill improvement insights—replicating how consulting firms assess candidates during real case interviews.
How CaseMaster AI Evaluates Case Interview Performance
Case interviews test multiple skills at once: structured thinking, analysis, math, communication, and the ability to synthesize insights quickly. Most candidates struggle because they don’t know how these skills are actually evaluated.
CaseMaster AI solves this by analyzing your performance exactly the way consultants do—through a multi-dimensional evaluation model.
Here’s how it works, broken down clearly.
1. Why Case Interview Evaluation Is Hard for Candidates
Most candidates don’t know:
- what criteria interviewers use
- how much each skill matters
- what a strong vs. weak structure looks like
- how math mistakes are judged
- why communication style affects scoring
- how final recommendations are graded
Without this understanding, candidates keep practicing but don’t improve.
Consultants evaluate how you think, how you speak, and how you solve problems. This is difficult to self-assess without guidance.
2. How CaseMaster AI Replicates Real Consulting Evaluation
CaseMaster AI uses the same evaluation pillars used in top consulting firms:
- Structure
- Hypothesis-driven thinking
- Analysis quality
- Math accuracy
- Business judgment
- Communication
- Synthesis
It listens to your answers, analyzes your logic, and gives a score on each dimension—along with explanations.
This mirrors exactly how real interviewers judge you.
3. The Six Core Scoring Parameters Explained
CaseMaster AI evaluates you using a 6+ dimension model:
1. Structuring
- Is your structure MECE?
- Is it tailored to the case?
- Is it logical and complete?
2. Hypothesis and Reasoning
- Do you propose a clear starting hypothesis?
- Do your insights follow logical progression?
- Are you prioritizing the right areas?
3. Math Performance
- Are your calculations accurate?
- Are your assumptions reasonable?
- Do you explain your steps clearly?
4. Business Judgment
- Are your recommendations realistic?
- Do they match industry logic?
- Do you understand trade-offs?
5. Communication
- Are you concise and clear?
- Do you avoid rambling?
- Do you structure your speech well?
6. Synthesis
- Is your final recommendation crisp?
- Do you tie back to the main question?
- Do you present risks and next steps?
This is the same model used in MBB interviews.
4. How CaseMaster AI Evaluates Your Structure
CaseMaster AI checks if your structure:
- fits the case type
- avoids generic frameworks
- covers both revenue and cost sides (for profitability)
- prioritizes the most relevant areas
- creates a clear roadmap for analysis
If a branch is missing or irrelevant, it flags it immediately.
5. How CaseMaster AI Evaluates Your Math
Math is judged on three fronts:
- Accuracy: Did you get the right number?
- Approach: Did you break the problem correctly?
- Clarity: Did you explain the steps cleanly?
It identifies exactly where errors happened—rounding, logic, or arithmetic.
6. How CaseMaster AI Evaluates Communication
It looks for:
- structured speaking
- concise answers
- clear transitions
- minimal filler words
- executive presence
This helps you sound more confident and consultant-like.
7. How CaseMaster AI Evaluates Synthesis
Synthesis is often the weakest part for candidates.
The AI checks:
- Is your recommendation direct?
- Is it supported by evidence?
- Are risks and next steps included?
- Is it short and clear?
This teaches you how to close cases like a real consultant.
8. Step-By-Step: How CaseMaster AI Evaluation Works
Step 1: You answer a case question
You talk or type through clarifying questions, structure, analysis, math, and recommendation.
Step 2: AI analyzes your responses
It evaluates each component separately.
Step 3: You receive scores for each skill
Scores are on a 0–5 scale.
Step 4: AI highlights strengths and weaknesses
You see exactly which skills need improvement.
Step 5: You receive targeted improvement tips
Practical suggestions for the next case.
Step 6: You track progress across cases
You can see your scores improving over time.
9. Benefits of AI-Based Evaluation
- Unbiased scoring
- Clear, consistent evaluation
- Immediate feedback
- Detailed insights per skill
- Faster improvement cycle
- Data-driven prep
- Transparent progress tracking
- Better understanding of what interviewers look for
This level of evaluation is impossible through self-practice.
10. Short Mock Case Example
Prompt:
A restaurant chain wants to increase profitability. What should they do?
Candidate’s Steps (Evaluated by AI):
- Clarify — Ask about costs vs. revenues.
- Structure — Demand → pricing → costs → operations.
- Math — Calculate average revenue per store.
- Analysis — Identify declining customer traffic.
- Synthesis — Recommend marketing + menu optimization.
CaseMaster AI then scores each step, highlights strengths, and points out gaps in structure or reasoning.
11. FAQs
How accurate is CaseMaster AI’s case interview scoring?
It follows real consulting evaluation criteria, making the scoring highly aligned with MBB and Big 4 standards.
Does the AI give different feedback for different case types?
Yes. Market entry, profitability, M&A, and guesstimates each have tailored evaluation logic.
Can beginners understand the feedback?
Yes. The feedback is simple, clear, and actionable.
Does the AI improve your performance over time?
Yes. It tracks your skills and focuses on your weakest areas.
Is AI evaluation better than peer feedback?
AI feedback is more consistent and analytical, while peers often lack experience or structured evaluation methods.